Interspeech
Collection
Accepted papers for Interspeech (Annual Conference of the International Speech Communication Association), one dataset per year. • 13 items • Updated
paper_id stringlengths 15 35 | title stringlengths 26 182 | authors listlengths 1 25 | isca_url stringlengths 66 86 | pdf_url stringlengths 65 85 | doi stringlengths 27 30 | pages stringlengths 3 9 | bibtex large_stringlengths 294 850 | abstract large_stringlengths 247 1.59k | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
values |
|---|---|---|---|---|---|---|---|---|---|---|
pucher21_interspeech | Conversion of Airborne to Bone-Conducted Speech with Deep Neural Networks | [
"Michael Pucher",
"Thomas Woltron"
] | https://www.isca-archive.org/interspeech_2021/pucher21_interspeech.html | https://www.isca-archive.org/interspeech_2021/pucher21_interspeech.pdf | 10.21437/Interspeech.2021-473 | 1-5 | @inproceedings{pucher21_interspeech,
title = {{Conversion of Airborne to Bone-Conducted Speech with Deep Neural Networks}},
author = {Michael Pucher and Thomas Woltron},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {1--5},
doi = {10.21437/Interspeech.2021-473},
issn ... | It is a common experience of most speakers that the playback of one’s
own voice sounds strange. This can be mainly attributed to the missing
bone-conducted speech signal that is not present in the playback signal.
It was also shown that some phonemes have a high bone-conducted relative
to air-conducted sound transmissi... | null | null |
rezackova21_interspeech | T5G2P: Using Text-to-Text Transfer Transformer for Grapheme-to-Phoneme Conversion | [
"Markéta Řezáčková",
"Jan Švec",
"Daniel Tihelka"
] | https://www.isca-archive.org/interspeech_2021/rezackova21_interspeech.html | https://www.isca-archive.org/interspeech_2021/rezackova21_interspeech.pdf | 10.21437/Interspeech.2021-546 | 6-10 | @inproceedings{rezackova21_interspeech,
title = {{T5G2P: Using Text-to-Text Transfer Transformer for Grapheme-to-Phoneme Conversion}},
author = {Markéta Řezáčková and Jan Švec and Daniel Tihelka},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {6--10},
doi = {10.21437/Intersp... | Despite the increasing popularity of end-to-end text-to-speech (TTS)
systems, the correct grapheme-to-phoneme (G2P) module is still a crucial
part of those relying on a phonetic input. In this paper, we, therefore,
introduce a T5G2P model, a Text-to-Text Transfer Transformer (T5) neural
network model which is able to c... | null | null |
perrotin21_interspeech | Evaluating the Extrapolation Capabilities of Neural Vocoders to Extreme Pitch Values | [
"Olivier Perrotin",
"Hussein El Amouri",
"Gérard Bailly",
"Thomas Hueber"
] | https://www.isca-archive.org/interspeech_2021/perrotin21_interspeech.html | https://www.isca-archive.org/interspeech_2021/perrotin21_interspeech.pdf | 10.21437/Interspeech.2021-1547 | 11-15 | @inproceedings{perrotin21_interspeech,
title = {{Evaluating the Extrapolation Capabilities of Neural Vocoders to Extreme Pitch Values}},
author = {Olivier Perrotin and Hussein El Amouri and Gérard Bailly and Thomas Hueber},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {11--15},
d... | Neural vocoders are systematically evaluated on homogeneous train and
test databases. This kind of evaluation is efficient to compare neural
vocoders in their “comfort zone”, yet it hardly reveals
their limits towards unseen data during training. To compare their
extrapolation capabilities, we introduce a methodology t... | null | null |
do21_interspeech | A Systematic Review and Analysis of Multilingual Data Strategies in Text-to-Speech for Low-Resource Languages | [
"Phat Do",
"Matt Coler",
"Jelske Dijkstra",
"Esther Klabbers"
] | https://www.isca-archive.org/interspeech_2021/do21_interspeech.html | https://www.isca-archive.org/interspeech_2021/do21_interspeech.pdf | 10.21437/Interspeech.2021-1565 | 16-20 | @inproceedings{do21_interspeech,
title = {{A Systematic Review and Analysis of Multilingual Data Strategies in Text-to-Speech for Low-Resource Languages}},
author = {Phat Do and Matt Coler and Jelske Dijkstra and Esther Klabbers},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {16--2... | We provide a systematic review of past studies that use multilingual
data for text-to-speech (TTS) of low-resource languages (LRLs). We
focus on the strategies used by these studies for incorporating multilingual
data and how they affect output speech quality. To investigate the
difference in output quality between cor... | null | null |
talkar21_interspeech | Acoustic Indicators of Speech Motor Coordination in Adults With and Without Traumatic Brain Injury | [
"Tanya Talkar",
"Nancy Pearl Solomon",
"Douglas S. Brungart",
"Stefanie E. Kuchinsky",
"Megan M. Eitel",
"Sara M. Lippa",
"Tracey A. Brickell",
"Louis M. French",
"Rael T. Lange",
"Thomas F. Quatieri"
] | https://www.isca-archive.org/interspeech_2021/talkar21_interspeech.html | https://www.isca-archive.org/interspeech_2021/talkar21_interspeech.pdf | 10.21437/Interspeech.2021-1581 | 21-25 | @inproceedings{talkar21_interspeech,
title = {{Acoustic Indicators of Speech Motor Coordination in Adults With and Without Traumatic Brain Injury}},
author = {Tanya Talkar and Nancy Pearl Solomon and Douglas S. Brungart and Stefanie E. Kuchinsky and Megan M. Eitel and Sara M. Lippa and Tracey A. Brickell and... | A traumatic brain injury (TBI) can lead to various long-term effects
on memory, attention, and mood, as well as the occurrence of headaches,
speech, and hearing problems. There is a need to better understand
the long-term effects of a TBI for objective tracking of an individual’s
recovery, which could be used to determ... | null | null |
vasquezcorrea21_interspeech | On Modeling Glottal Source Information for Phonation Assessment in Parkinson’s Disease | [
"J.C. Vásquez-Correa",
"Julian Fritsch",
"J.R. Orozco-Arroyave",
"Elmar Nöth",
"Mathew Magimai-Doss"
] | https://www.isca-archive.org/interspeech_2021/vasquezcorrea21_interspeech.html | https://www.isca-archive.org/interspeech_2021/vasquezcorrea21_interspeech.pdf | 10.21437/Interspeech.2021-1084 | 26-30 | @inproceedings{vasquezcorrea21_interspeech,
title = {{On Modeling Glottal Source Information for Phonation Assessment in Parkinson’s Disease}},
author = {J.C. Vásquez-Correa and Julian Fritsch and J.R. Orozco-Arroyave and Elmar Nöth and Mathew Magimai-Doss},
year = {2021},
booktitle = {{Interspeech ... | Parkinson’s disease produces several motor symptoms, including
different speech impairments that are known as hypokinetic dysarthria.
Symptoms associated to dysarthria affect different dimensions of speech
such as phonation, articulation, prosody, and intelligibility. Studies
in the literature have mainly focused on th... | null | null |
daoudi21_interspeech | Distortion of Voiced Obstruents for Differential Diagnosis Between Parkinson’s Disease and Multiple System Atrophy | [
"Khalid Daoudi",
"Biswajit Das",
"Solange Milhé de Saint Victor",
"Alexandra Foubert-Samier",
"Anne Pavy-Le Traon",
"Olivier Rascol",
"Wassilios G. Meissner",
"Virginie Woisard"
] | https://www.isca-archive.org/interspeech_2021/daoudi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/daoudi21_interspeech.pdf | 10.21437/Interspeech.2021-223 | 31-35 | @inproceedings{daoudi21_interspeech,
title = {{Distortion of Voiced Obstruents for Differential Diagnosis Between Parkinson’s Disease and Multiple System Atrophy}},
author = {Khalid Daoudi and Biswajit Das and Solange Milhé de Saint Victor and Alexandra Foubert-Samier and Anne Pavy-Le Traon and Olivier Rasco... | Parkinson’s disease (PD) and the parkinsonian variant of Multiple
System Atrophy (MSA-P) are two neurodegenerative diseases which share
similar clinical features, particularly in early disease stages. The
differential diagnosis can be thus very challenging. Dysarthria is
known to be a frequent and early clinical featur... | null | null |
wang21_interspeech | A Study into Pre-Training Strategies for Spoken Language Understanding on Dysarthric Speech | [
"Pu Wang",
"Bagher BabaAli",
"Hugo Van hamme"
] | https://www.isca-archive.org/interspeech_2021/wang21_interspeech.html | https://www.isca-archive.org/interspeech_2021/wang21_interspeech.pdf | 10.21437/Interspeech.2021-1720 | 36-40 | @inproceedings{wang21_interspeech,
title = {{A Study into Pre-Training Strategies for Spoken Language Understanding on Dysarthric Speech}},
author = {Pu Wang and Bagher BabaAli and Hugo {Van hamme}},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {36--40},
doi = {10.21437/Int... | End-to-end (E2E) spoken language understanding (SLU) systems avoid
an intermediate textual representation by mapping speech directly into
intents with slot values. This approach requires considerable domain-specific
training data. In low-resource scenarios this is a major concern, e.g.,
in the present study dealing wit... | 2106.08313 | title_snapshot |
turrisi21_interspeech | EasyCall Corpus: A Dysarthric Speech Dataset | [
"Rosanna Turrisi",
"Arianna Braccia",
"Marco Emanuele",
"Simone Giulietti",
"Maura Pugliatti",
"Mariachiara Sensi",
"Luciano Fadiga",
"Leonardo Badino"
] | https://www.isca-archive.org/interspeech_2021/turrisi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/turrisi21_interspeech.pdf | 10.21437/Interspeech.2021-549 | 41-45 | @inproceedings{turrisi21_interspeech,
title = {{EasyCall Corpus: A Dysarthric Speech Dataset}},
author = {Rosanna Turrisi and Arianna Braccia and Marco Emanuele and Simone Giulietti and Maura Pugliatti and Mariachiara Sensi and Luciano Fadiga and Leonardo Badino},
year = {2021},
booktitle = {{Inters... | This paper introduces a new dysarthric speech command dataset in Italian,
called EasyCall corpus. The dataset consists of 21386 audio recordings
from 24 healthy and 31 dysarthric speakers, whose individual degree
of speech impairment was assessed by neurologists through the Therapy
Outcome Measure. The corpus aims at p... | 2104.02542 | title_snapshot |
bie21_interspeech | A Benchmark of Dynamical Variational Autoencoders Applied to Speech Spectrogram Modeling | [
"Xiaoyu Bie",
"Laurent Girin",
"Simon Leglaive",
"Thomas Hueber",
"Xavier Alameda-Pineda"
] | https://www.isca-archive.org/interspeech_2021/bie21_interspeech.html | https://www.isca-archive.org/interspeech_2021/bie21_interspeech.pdf | 10.21437/Interspeech.2021-256 | 46-50 | @inproceedings{bie21_interspeech,
title = {{A Benchmark of Dynamical Variational Autoencoders Applied to Speech Spectrogram Modeling}},
author = {Xiaoyu Bie and Laurent Girin and Simon Leglaive and Thomas Hueber and Xavier Alameda-Pineda},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | The Variational Autoencoder (VAE) is a powerful deep generative model
that is now extensively used to represent high-dimensional complex
data via a low-dimensional latent space learned in an unsupervised
manner. In the original VAE model, input data vectors are processed
independently. In recent years, a series of pape... | 2106.06500 | title_snapshot |
yurt21_interspeech | Fricative Phoneme Detection Using Deep Neural Networks and its Comparison to Traditional Methods | [
"Metehan Yurt",
"Pavan Kantharaju",
"Sascha Disch",
"Andreas Niedermeier",
"Alberto N. Escalante-B",
"Veniamin I. Morgenshtern"
] | https://www.isca-archive.org/interspeech_2021/yurt21_interspeech.html | https://www.isca-archive.org/interspeech_2021/yurt21_interspeech.pdf | 10.21437/Interspeech.2021-645 | 51-55 | @inproceedings{yurt21_interspeech,
title = {{Fricative Phoneme Detection Using Deep Neural Networks and its Comparison to Traditional Methods}},
author = {Metehan Yurt and Pavan Kantharaju and Sascha Disch and Andreas Niedermeier and Alberto N. Escalante-B and Veniamin I. Morgenshtern},
year = {2021},... | Accurate phoneme detection and processing can enhance speech intelligibility
in hearing aids and audio & speech codecs. As fricative phonemes
have an important part of their energy concentrated in high frequency
bands, frequency lowering algorithms are used in hearing aids to improve
fricative intelligibility for peopl... | null | null |
prasad21_interspeech | Identification of F1 and F2 in Speech Using Modified Zero Frequency Filtering | [
"RaviShankar Prasad",
"Mathew Magimai-Doss"
] | https://www.isca-archive.org/interspeech_2021/prasad21_interspeech.html | https://www.isca-archive.org/interspeech_2021/prasad21_interspeech.pdf | 10.21437/Interspeech.2021-1598 | 56-60 | @inproceedings{prasad21_interspeech,
title = {{Identification of F1 and F2 in Speech Using Modified Zero Frequency Filtering}},
author = {RaviShankar Prasad and Mathew Magimai-Doss},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {56--60},
doi = {10.21437/Interspeech.2021-159... | Formants are major resonances in the vocal tract system. Identification
of formants is important for study of speech. In the literature, formants
are typically identified by first deriving formant frequency candidates
(e.g., using linear prediction) and then applying a tracking mechanism.
In this paper, we propose a si... | null | null |
teytaut21_interspeech | Phoneme-to-Audio Alignment with Recurrent Neural Networks for Speaking and Singing Voice | [
"Yann Teytaut",
"Axel Roebel"
] | https://www.isca-archive.org/interspeech_2021/teytaut21_interspeech.html | https://www.isca-archive.org/interspeech_2021/teytaut21_interspeech.pdf | 10.21437/Interspeech.2021-1676 | 61-65 | @inproceedings{teytaut21_interspeech,
title = {{Phoneme-to-Audio Alignment with Recurrent Neural Networks for Speaking and Singing Voice}},
author = {Yann Teytaut and Axel Roebel},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {61--65},
doi = {10.21437/Interspeech.2021-1676}... | Phoneme-to-audio alignment is the task of synchronizing voice recordings
and their related phonetic transcripts. In this work, we introduce
a new system to forced phonetic alignment with Recurrent Neural Networks
(RNN). With the Connectionist Temporal Classification (CTC) loss as
training objective, and an additional r... | null | null |
kim21_interspeech | Adaptive Convolutional Neural Network for Text-Independent Speaker Recognition | [
"Seong-Hu Kim",
"Yong-Hwa Park"
] | https://www.isca-archive.org/interspeech_2021/kim21_interspeech.html | https://www.isca-archive.org/interspeech_2021/kim21_interspeech.pdf | 10.21437/Interspeech.2021-65 | 66-70 | @inproceedings{kim21_interspeech,
title = {{Adaptive Convolutional Neural Network for Text-Independent Speaker Recognition}},
author = {Seong-Hu Kim and Yong-Hwa Park},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {66--70},
doi = {10.21437/Interspeech.2021-65},
issn ... | In text-independent speaker recognition, each speech is composed of
different phonemes depending on spoken text. The conventional neural
networks for speaker recognition are static models, so they do not
reflect this phoneme-varying characteristic well. To tackle this limitation,
we propose an adaptive convolutional ne... | null | null |
qi21_interspeech | Bidirectional Multiscale Feature Aggregation for Speaker Verification | [
"Jiajun Qi",
"Wu Guo",
"Bin Gu"
] | https://www.isca-archive.org/interspeech_2021/qi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/qi21_interspeech.pdf | 10.21437/Interspeech.2021-111 | 71-75 | @inproceedings{qi21_interspeech,
title = {{Bidirectional Multiscale Feature Aggregation for Speaker Verification}},
author = {Jiajun Qi and Wu Guo and Bin Gu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {71--75},
doi = {10.21437/Interspeech.2021-111},
issn = {2958-... | In this paper, we propose a novel bidirectional multiscale feature
aggregation (BMFA) network with attentional fusion modules for text-independent
speaker verification. The feature maps from different stages of the
backbone network are iteratively combined and refined in both a bottom-up
and top-down manner. Furthermor... | 2104.00230 | title_snapshot |
zhang21_interspeech | Improving Time Delay Neural Network Based Speaker Recognition with Convolutional Block and Feature Aggregation Methods | [
"Yu-Jia Zhang",
"Yih-Wen Wang",
"Chia-Ping Chen",
"Chung-Li Lu",
"Bo-Cheng Chan"
] | https://www.isca-archive.org/interspeech_2021/zhang21_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhang21_interspeech.pdf | 10.21437/Interspeech.2021-356 | 76-80 | @inproceedings{zhang21_interspeech,
title = {{Improving Time Delay Neural Network Based Speaker Recognition with Convolutional Block and Feature Aggregation Methods}},
author = {Yu-Jia Zhang and Yih-Wen Wang and Chia-Ping Chen and Chung-Li Lu and Bo-Cheng Chan},
year = {2021},
booktitle = {{Interspe... | In this paper, we develop a system that integrates multiple ideas and
techniques inspired by the convolutional block and feature aggregation
methods. We begin with the state-of-the-art speaker-embedding model
for speaker recognition, namely the model of Emphasized Channel Attention,
Propagation, and Aggregation in Time... | null | null |
wu21_interspeech | Improving Deep CNN Architectures with Variable-Length Training Samples for Text-Independent Speaker Verification | [
"Yanfeng Wu",
"Junan Zhao",
"Chenkai Guo",
"Jing Xu"
] | https://www.isca-archive.org/interspeech_2021/wu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/wu21_interspeech.pdf | 10.21437/Interspeech.2021-559 | 81-85 | @inproceedings{wu21_interspeech,
title = {{Improving Deep CNN Architectures with Variable-Length Training Samples for Text-Independent Speaker Verification}},
author = {Yanfeng Wu and Junan Zhao and Chenkai Guo and Jing Xu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {81--85},
... | Deep Convolutional Neural Network (CNN) based speaker embeddings, such
as r-vectors, have shown great success in text-independent speaker
verification (TI-SV) task. However, previous deep CNN models usually
use fixed-length samples for training and employ variable-length utterances
for speaker embeddings, which generat... | null | null |
zhu21_interspeech | Binary Neural Network for Speaker Verification | [
"Tinglong Zhu",
"Xiaoyi Qin",
"Ming Li"
] | https://www.isca-archive.org/interspeech_2021/zhu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhu21_interspeech.pdf | 10.21437/Interspeech.2021-600 | 86-90 | @inproceedings{zhu21_interspeech,
title = {{Binary Neural Network for Speaker Verification}},
author = {Tinglong Zhu and Xiaoyi Qin and Ming Li},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {86--90},
doi = {10.21437/Interspeech.2021-600},
issn = {2958-1796},
} | Although deep neural networks are successful for many tasks in the
speech domain, the high computational and memory costs of deep neural
networks make it difficult to directly deploy high-performance Neural
Network systems on low-resource embedded devices. There are several
mechanisms to reduce the size of the neural n... | 2104.02306 | title_snapshot |
tu21_interspeech | Mutual Information Enhanced Training for Speaker Embedding | [
"Youzhi Tu",
"Man-Wai Mak"
] | https://www.isca-archive.org/interspeech_2021/tu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tu21_interspeech.pdf | 10.21437/Interspeech.2021-1436 | 91-95 | @inproceedings{tu21_interspeech,
title = {{Mutual Information Enhanced Training for Speaker Embedding}},
author = {Youzhi Tu and Man-Wai Mak},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {91--95},
doi = {10.21437/Interspeech.2021-1436},
issn = {2958-1796},
} | Mutual information (MI) is useful in unsupervised and self-supervised
learning. Maximizing the MI between the low-level features and the
learned embeddings can preserve meaningful information in the embeddings,
which can contribute to performance gains. This strategy is called
deep InfoMax (DIM) in representation learn... | null | null |
zhu21b_interspeech | Y-Vector: Multiscale Waveform Encoder for Speaker Embedding | [
"Ge Zhu",
"Fei Jiang",
"Zhiyao Duan"
] | https://www.isca-archive.org/interspeech_2021/zhu21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhu21b_interspeech.pdf | 10.21437/Interspeech.2021-1707 | 96-100 | @inproceedings{zhu21b_interspeech,
title = {{Y-Vector: Multiscale Waveform Encoder for Speaker Embedding}},
author = {Ge Zhu and Fei Jiang and Zhiyao Duan},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {96--100},
doi = {10.21437/Interspeech.2021-1707},
issn = {2958-1... | State-of-the-art text-independent speaker verification systems typically
use cepstral features or filter bank energies as speech features. Recent
studies attempted to extract speaker embeddings directly from raw waveforms
and have shown competitive results. In this paper, we propose a novel
multi-scale waveform encoder... | 2010.12951 | title_snapshot |
liu21_interspeech | Phoneme-Aware and Channel-Wise Attentive Learning for Text Dependent Speaker Verification | [
"Yan Liu",
"Zheng Li",
"Lin Li",
"Qingyang Hong"
] | https://www.isca-archive.org/interspeech_2021/liu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/liu21_interspeech.pdf | 10.21437/Interspeech.2021-2137 | 101-105 | @inproceedings{liu21_interspeech,
title = {{Phoneme-Aware and Channel-Wise Attentive Learning for Text Dependent Speaker Verification}},
author = {Yan Liu and Zheng Li and Lin Li and Qingyang Hong},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {101--105},
doi = {10.21437/In... | This paper proposes a multi-task learning network with phoneme-aware
and channel-wise attentive learning strategies for text-dependent Speaker
Verification (SV). In the proposed structure, the frame-level multi-task
learning along with the segment-level adversarial learning is adopted
for speaker embedding extraction. ... | 2106.13514 | title_judge |
zhu21c_interspeech | Serialized Multi-Layer Multi-Head Attention for Neural Speaker Embedding | [
"Hongning Zhu",
"Kong Aik Lee",
"Haizhou Li"
] | https://www.isca-archive.org/interspeech_2021/zhu21c_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhu21c_interspeech.pdf | 10.21437/Interspeech.2021-2210 | 106-110 | @inproceedings{zhu21c_interspeech,
title = {{Serialized Multi-Layer Multi-Head Attention for Neural Speaker Embedding}},
author = {Hongning Zhu and Kong Aik Lee and Haizhou Li},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {106--110},
doi = {10.21437/Interspeech.2021-2210},... | This paper proposes a serialized multi-layer multi-head attention for
neural speaker embedding in text-independent speaker verification.
In prior works, frame-level features from one layer are aggregated
to form an utterance-level representation. Inspired by the Transformer
network, our proposed method utilizes the hie... | 2107.06493 | title_snapshot |
gong21_interspeech | TacoLPCNet: Fast and Stable TTS by Conditioning LPCNet on Mel Spectrogram Predictions | [
"Cheng Gong",
"Longbiao Wang",
"Ju Zhang",
"Shaotong Guo",
"Yuguang Wang",
"Jianwu Dang"
] | https://www.isca-archive.org/interspeech_2021/gong21_interspeech.html | https://www.isca-archive.org/interspeech_2021/gong21_interspeech.pdf | 10.21437/Interspeech.2021-852 | 111-115 | @inproceedings{gong21_interspeech,
title = {{TacoLPCNet: Fast and Stable TTS by Conditioning LPCNet on Mel Spectrogram Predictions}},
author = {Cheng Gong and Longbiao Wang and Ju Zhang and Shaotong Guo and Yuguang Wang and Jianwu Dang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages =... | The combination of the recently proposed LPCNet vocoder and a seq-to-seq
acoustic model, i.e., Tacotron, has successfully achieved lightweight
speech synthesis systems. However, the quality of synthesized speech
is often unstable because the precision of the pitch parameters predicted
by acoustic models is insufficient... | null | null |
bak21_interspeech | FastPitchFormant: Source-Filter Based Decomposed Modeling for Speech Synthesis | [
"Taejun Bak",
"Jae-Sung Bae",
"Hanbin Bae",
"Young-Ik Kim",
"Hoon-Young Cho"
] | https://www.isca-archive.org/interspeech_2021/bak21_interspeech.html | https://www.isca-archive.org/interspeech_2021/bak21_interspeech.pdf | 10.21437/Interspeech.2021-866 | 116-120 | @inproceedings{bak21_interspeech,
title = {{FastPitchFormant: Source-Filter Based Decomposed Modeling for Speech Synthesis}},
author = {Taejun Bak and Jae-Sung Bae and Hanbin Bae and Young-Ik Kim and Hoon-Young Cho},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {116--120},
doi ... | Methods for modeling and controlling prosody with acoustic features
have been proposed for neural text-to-speech (TTS) models. Prosodic
speech can be generated by conditioning acoustic features. However,
synthesized speech with a large pitch-shift scale suffers from audio
quality degradation, and speaker characteristic... | 2106.15123 | title_snapshot |
nakamura21_interspeech | Sequence-to-Sequence Learning for Deep Gaussian Process Based Speech Synthesis Using Self-Attention GP Layer | [
"Taiki Nakamura",
"Tomoki Koriyama",
"Hiroshi Saruwatari"
] | https://www.isca-archive.org/interspeech_2021/nakamura21_interspeech.html | https://www.isca-archive.org/interspeech_2021/nakamura21_interspeech.pdf | 10.21437/Interspeech.2021-896 | 121-125 | @inproceedings{nakamura21_interspeech,
title = {{Sequence-to-Sequence Learning for Deep Gaussian Process Based Speech Synthesis Using Self-Attention GP Layer}},
author = {Taiki Nakamura and Tomoki Koriyama and Hiroshi Saruwatari},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {121--... | This paper presents a speech synthesis method based on deep Gaussian
process (DGP) and sequence-to-sequence (Seq2Seq) learning toward high-quality
end-to-end speech synthesis. Feed-forward and recurrent models using
DGP are known to produce more natural synthetic speech than deep neural
networks (DNNs) because of Bayes... | null | null |
kakegawa21_interspeech | Phonetic and Prosodic Information Estimation from Texts for Genuine Japanese End-to-End Text-to-Speech | [
"Naoto Kakegawa",
"Sunao Hara",
"Masanobu Abe",
"Yusuke Ijima"
] | https://www.isca-archive.org/interspeech_2021/kakegawa21_interspeech.html | https://www.isca-archive.org/interspeech_2021/kakegawa21_interspeech.pdf | 10.21437/Interspeech.2021-914 | 126-130 | @inproceedings{kakegawa21_interspeech,
title = {{Phonetic and Prosodic Information Estimation from Texts for Genuine Japanese End-to-End Text-to-Speech}},
author = {Naoto Kakegawa and Sunao Hara and Masanobu Abe and Yusuke Ijima},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {126--... | The biggest obstacle to develop end-to-end Japanese text-to-speech
(TTS) systems is to estimate phonetic and prosodic information (PPI)
from Japanese texts. The following are the reasons: (1) the Kanji characters
of the Japanese writing system have multiple corresponding pronunciations,
(2) there is no separation mark ... | null | null |
dai21_interspeech | Information Sieve: Content Leakage Reduction in End-to-End Prosody Transfer for Expressive Speech Synthesis | [
"Xudong Dai",
"Cheng Gong",
"Longbiao Wang",
"Kaili Zhang"
] | https://www.isca-archive.org/interspeech_2021/dai21_interspeech.html | https://www.isca-archive.org/interspeech_2021/dai21_interspeech.pdf | 10.21437/Interspeech.2021-1011 | 131-135 | @inproceedings{dai21_interspeech,
title = {{Information Sieve: Content Leakage Reduction in End-to-End Prosody Transfer for Expressive Speech Synthesis}},
author = {Xudong Dai and Cheng Gong and Longbiao Wang and Kaili Zhang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {131--135}... | Expressive neural text-to-speech (TTS) systems incorporate a style
encoder to learn a latent embedding as the style information. However,
this embedding process may encode redundant textual information. This
phenomenon is called content leakage. Researchers have attempted to
resolve this problem by adding an ASR or oth... | 2108.01831 | title_judge |
dou21_interspeech | Deliberation-Based Multi-Pass Speech Synthesis | [
"Qingyun Dou",
"Xixin Wu",
"Moquan Wan",
"Yiting Lu",
"Mark J.F. Gales"
] | https://www.isca-archive.org/interspeech_2021/dou21_interspeech.html | https://www.isca-archive.org/interspeech_2021/dou21_interspeech.pdf | 10.21437/Interspeech.2021-1405 | 136-140 | @inproceedings{dou21_interspeech,
title = {{Deliberation-Based Multi-Pass Speech Synthesis}},
author = {Qingyun Dou and Xixin Wu and Moquan Wan and Yiting Lu and Mark J.F. Gales},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {136--140},
doi = {10.21437/Interspeech.2021-1405... | Sequence-to-sequence (seq2seq) models have achieved state-of-the-art
performance in a wide range of tasks including Neural Machine Translation
(NMT) and Text-To-Speech (TTS). These models are usually trained with
teacher forcing, where the reference back-history is used to predict
the next token. This makes training ef... | null | null |
elias21_interspeech | Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling | [
"Isaac Elias",
"Heiga Zen",
"Jonathan Shen",
"Yu Zhang",
"Ye Jia",
"R.J. Skerry-Ryan",
"Yonghui Wu"
] | https://www.isca-archive.org/interspeech_2021/elias21_interspeech.html | https://www.isca-archive.org/interspeech_2021/elias21_interspeech.pdf | 10.21437/Interspeech.2021-1461 | 141-145 | @inproceedings{elias21_interspeech,
title = {{Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling}},
author = {Isaac Elias and Heiga Zen and Jonathan Shen and Yu Zhang and Ye Jia and R.J. Skerry-Ryan and Yonghui Wu},
year = {2021},
booktitle = {{Interspee... | This paper introduces Parallel Tacotron 2 , a non-autoregressive
neural text-to-speech model with a fully differentiable duration model
which does not require supervised duration signals. The duration model
is based on a novel attention mechanism and an iterative reconstruction
loss based on Soft Dynamic TimeWarping, t... | 2103.14574 | title_snapshot |
wu21b_interspeech | Transformer-Based Acoustic Modeling for Streaming Speech Synthesis | [
"Chunyang Wu",
"Zhiping Xiu",
"Yangyang Shi",
"Ozlem Kalinli",
"Christian Fuegen",
"Thilo Koehler",
"Qing He"
] | https://www.isca-archive.org/interspeech_2021/wu21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/wu21b_interspeech.pdf | 10.21437/Interspeech.2021-1655 | 146-150 | @inproceedings{wu21b_interspeech,
title = {{Transformer-Based Acoustic Modeling for Streaming Speech Synthesis}},
author = {Chunyang Wu and Zhiping Xiu and Yangyang Shi and Ozlem Kalinli and Christian Fuegen and Thilo Koehler and Qing He},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | Transformer models have shown promising results in neural speech synthesis
due to their superior ability to model long-term dependencies compared
to recurrent networks. The computation complexity of transformers increases
quadratically with sequence length, making it impractical for many
real-time applications. To addr... | null | null |
jia21_interspeech | PnG BERT: Augmented BERT on Phonemes and Graphemes for Neural TTS | [
"Ye Jia",
"Heiga Zen",
"Jonathan Shen",
"Yu Zhang",
"Yonghui Wu"
] | https://www.isca-archive.org/interspeech_2021/jia21_interspeech.html | https://www.isca-archive.org/interspeech_2021/jia21_interspeech.pdf | 10.21437/Interspeech.2021-1757 | 151-155 | @inproceedings{jia21_interspeech,
title = {{PnG BERT: Augmented BERT on Phonemes and Graphemes for Neural TTS}},
author = {Ye Jia and Heiga Zen and Jonathan Shen and Yu Zhang and Yonghui Wu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {151--155},
doi = {10.21437/Interspee... | This paper introduces PnG BERT , a new encoder model for neural
TTS. This model is augmented from the original BERT model, by taking
both phoneme and grapheme representations of text as input, as well
as the word-level alignment between them. It can be pre-trained on
a large text corpus in a self-supervised manner, and... | 2103.15060 | title_snapshot |
ge21_interspeech | Speed up Training with Variable Length Inputs by Efficient Batching Strategies | [
"Zhenhao Ge",
"Lakshmish Kaushik",
"Masanori Omote",
"Saket Kumar"
] | https://www.isca-archive.org/interspeech_2021/ge21_interspeech.html | https://www.isca-archive.org/interspeech_2021/ge21_interspeech.pdf | 10.21437/Interspeech.2021-2100 | 156-160 | @inproceedings{ge21_interspeech,
title = {{Speed up Training with Variable Length Inputs by Efficient Batching Strategies}},
author = {Zhenhao Ge and Lakshmish Kaushik and Masanori Omote and Saket Kumar},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {156--160},
doi = {10.21... | In the model training with neural networks, although the model performance
is always the first priority to optimize, training efficiency also
plays an important role in model deployment. There are many ways to
speed up training with minimal performance loss, such as training with
more GPUs, or with mixed precisions, op... | null | null |
sun21_interspeech | Funnel Deep Complex U-Net for Phase-Aware Speech Enhancement | [
"Yuhang Sun",
"Linju Yang",
"Huifeng Zhu",
"Jie Hao"
] | https://www.isca-archive.org/interspeech_2021/sun21_interspeech.html | https://www.isca-archive.org/interspeech_2021/sun21_interspeech.pdf | 10.21437/Interspeech.2021-10 | 161-165 | @inproceedings{sun21_interspeech,
title = {{Funnel Deep Complex U-Net for Phase-Aware Speech Enhancement}},
author = {Yuhang Sun and Linju Yang and Huifeng Zhu and Jie Hao},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {161--165},
doi = {10.21437/Interspeech.2021-10},
iss... | The emergence of deep neural networks has made speech enhancement well
developed. Most of the early models focused on estimating the magnitude
of spectrum while ignoring the phase, this gives the evaluation result
a certain upper limit. Some recent researches proposed deep complex
network, which can handle complex inpu... | null | null |
zhang21b_interspeech | Temporal Convolutional Network with Frequency Dimension Adaptive Attention for Speech Enhancement | [
"Qiquan Zhang",
"Qi Song",
"Aaron Nicolson",
"Tian Lan",
"Haizhou Li"
] | https://www.isca-archive.org/interspeech_2021/zhang21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhang21b_interspeech.pdf | 10.21437/Interspeech.2021-46 | 166-170 | @inproceedings{zhang21b_interspeech,
title = {{Temporal Convolutional Network with Frequency Dimension Adaptive Attention for Speech Enhancement}},
author = {Qiquan Zhang and Qi Song and Aaron Nicolson and Tian Lan and Haizhou Li},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {166-... | Despite much progress, most temporal convolutional networks (TCN) based
speech enhancement models are mainly focused on modeling the long-term
temporal contextual dependencies of speech frames, without taking into
account the distribution information of speech signal in frequency
dimension. In this study, we propose a ... | null | null |
pan21_interspeech | Perceptual Contributions of Vowels and Consonant-Vowel Transitions in Understanding Time-Compressed Mandarin Sentences | [
"Changjie Pan",
"Feng Yang",
"Fei Chen"
] | https://www.isca-archive.org/interspeech_2021/pan21_interspeech.html | https://www.isca-archive.org/interspeech_2021/pan21_interspeech.pdf | 10.21437/Interspeech.2021-58 | 171-175 | @inproceedings{pan21_interspeech,
title = {{Perceptual Contributions of Vowels and Consonant-Vowel Transitions in Understanding Time-Compressed Mandarin Sentences}},
author = {Changjie Pan and Feng Yang and Fei Chen},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {171--175},
doi ... | Many early studies reported the importance of vowels and vowel-consonant
transitions to speech intelligibility. The present work assessed their
perceptual impacts to the understanding of time-compressed sentences,
which could be used to measure the temporal acuity during speech understanding.
Mandarin sentences were ed... | null | null |
biswas21_interspeech | Transfer Learning for Speech Intelligibility Improvement in Noisy Environments | [
"Ritujoy Biswas",
"Karan Nathwani",
"Vinayak Abrol"
] | https://www.isca-archive.org/interspeech_2021/biswas21_interspeech.html | https://www.isca-archive.org/interspeech_2021/biswas21_interspeech.pdf | 10.21437/Interspeech.2021-150 | 176-180 | @inproceedings{biswas21_interspeech,
title = {{Transfer Learning for Speech Intelligibility Improvement in Noisy Environments}},
author = {Ritujoy Biswas and Karan Nathwani and Vinayak Abrol},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {176--180},
doi = {10.21437/Interspe... | In a recent work [1], a novel Delta Function-based Formant Shifting
approach was proposed for speech intelligibility improvement. The underlying
principle is to dynamically relocate the formants based on their occurrence
in the spectrum away from the region of noise. The manner in which
the formants are shifted is deci... | null | null |
yamamoto21_interspeech | Comparison of Remote Experiments Using Crowdsourcing and Laboratory Experiments on Speech Intelligibility | [
"Ayako Yamamoto",
"Toshio Irino",
"Kenichi Arai",
"Shoko Araki",
"Atsunori Ogawa",
"Keisuke Kinoshita",
"Tomohiro Nakatani"
] | https://www.isca-archive.org/interspeech_2021/yamamoto21_interspeech.html | https://www.isca-archive.org/interspeech_2021/yamamoto21_interspeech.pdf | 10.21437/Interspeech.2021-174 | 181-185 | @inproceedings{yamamoto21_interspeech,
title = {{Comparison of Remote Experiments Using Crowdsourcing and Laboratory Experiments on Speech Intelligibility}},
author = {Ayako Yamamoto and Toshio Irino and Kenichi Arai and Shoko Araki and Atsunori Ogawa and Keisuke Kinoshita and Tomohiro Nakatani},
year ... | Many subjective experiments have been performed to develop objective
speech intelligibility measures, but the novel coronavirus outbreak
has made it difficult to conduct experiments in a laboratory. One solution
is to perform remote testing using crowdsourcing; however, because
we cannot control the listening condition... | 2104.10001 | title_snapshot |
liu21b_interspeech | Know Your Enemy, Know Yourself: A Unified Two-Stage Framework for Speech Enhancement | [
"Wenzhe Liu",
"Andong Li",
"Yuxuan Ke",
"Chengshi Zheng",
"Xiaodong Li"
] | https://www.isca-archive.org/interspeech_2021/liu21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/liu21b_interspeech.pdf | 10.21437/Interspeech.2021-238 | 186-190 | @inproceedings{liu21b_interspeech,
title = {{Know Your Enemy, Know Yourself: A Unified Two-Stage Framework for Speech Enhancement}},
author = {Wenzhe Liu and Andong Li and Yuxuan Ke and Chengshi Zheng and Xiaodong Li},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {186--190},
doi ... | Traditional spectral subtraction-type single channel speech enhancement
(SE) algorithms often need to estimate interference components including
noise and/or reverberation before subtracting them while deep neural
network-based SE methods often aim to realize the end-to-end target
mapping. In this paper, we show that b... | null | null |
kong21_interspeech | Speech Enhancement with Weakly Labelled Data from AudioSet | [
"Qiuqiang Kong",
"Haohe Liu",
"Xingjian Du",
"Li Chen",
"Rui Xia",
"Yuxuan Wang"
] | https://www.isca-archive.org/interspeech_2021/kong21_interspeech.html | https://www.isca-archive.org/interspeech_2021/kong21_interspeech.pdf | 10.21437/Interspeech.2021-259 | 191-195 | @inproceedings{kong21_interspeech,
title = {{Speech Enhancement with Weakly Labelled Data from AudioSet}},
author = {Qiuqiang Kong and Haohe Liu and Xingjian Du and Li Chen and Rui Xia and Yuxuan Wang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {191--195},
doi = {10.2143... | Speech enhancement is a task to improve the intelligibility and perceptual
quality of degraded speech signals. Recently, neural network-based
methods have been applied to speech enhancement. However, many neural
network-based methods require users to collect clean speech and background
noise for training, which can be ... | 2102.09971 | title_snapshot |
hsieh21_interspeech | Improving Perceptual Quality by Phone-Fortified Perceptual Loss Using Wasserstein Distance for Speech Enhancement | [
"Tsun-An Hsieh",
"Cheng Yu",
"Szu-Wei Fu",
"Xugang Lu",
"Yu Tsao"
] | https://www.isca-archive.org/interspeech_2021/hsieh21_interspeech.html | https://www.isca-archive.org/interspeech_2021/hsieh21_interspeech.pdf | 10.21437/Interspeech.2021-582 | 196-200 | @inproceedings{hsieh21_interspeech,
title = {{Improving Perceptual Quality by Phone-Fortified Perceptual Loss Using Wasserstein Distance for Speech Enhancement}},
author = {Tsun-An Hsieh and Cheng Yu and Szu-Wei Fu and Xugang Lu and Yu Tsao},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | Speech enhancement (SE) aims to improve speech quality and intelligibility,
which are both related to a smooth transition in speech segments that
may carry linguistic information, e.g. phones and syllables. In this
study, we propose a novel phone-fortified perceptual loss (PFPL) that
takes phonetic information into acc... | 2010.15174 | title_snapshot |
fu21_interspeech | MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement | [
"Szu-Wei Fu",
"Cheng Yu",
"Tsun-An Hsieh",
"Peter Plantinga",
"Mirco Ravanelli",
"Xugang Lu",
"Yu Tsao"
] | https://www.isca-archive.org/interspeech_2021/fu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/fu21_interspeech.pdf | 10.21437/Interspeech.2021-599 | 201-205 | @inproceedings{fu21_interspeech,
title = {{MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement}},
author = {Szu-Wei Fu and Cheng Yu and Tsun-An Hsieh and Peter Plantinga and Mirco Ravanelli and Xugang Lu and Yu Tsao},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {20... | The discrepancy between the cost function used for training a speech
enhancement model and human auditory perception usually makes the quality
of enhanced speech unsatisfactory. Objective evaluation metrics which
consider human perception can hence serve as a bridge to reduce the
gap. Our previously proposed MetricGAN ... | 2104.03538 | title_snapshot |
edraki21_interspeech | A Spectro-Temporal Glimpsing Index (STGI) for Speech Intelligibility Prediction | [
"Amin Edraki",
"Wai-Yip Chan",
"Jesper Jensen",
"Daniel Fogerty"
] | https://www.isca-archive.org/interspeech_2021/edraki21_interspeech.html | https://www.isca-archive.org/interspeech_2021/edraki21_interspeech.pdf | 10.21437/Interspeech.2021-605 | 206-210 | @inproceedings{edraki21_interspeech,
title = {{A Spectro-Temporal Glimpsing Index (STGI) for Speech Intelligibility Prediction}},
author = {Amin Edraki and Wai-Yip Chan and Jesper Jensen and Daniel Fogerty},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {206--210},
doi = {10... | We propose a monaural intrusive speech intelligibility prediction (SIP)
algorithm called STGI based on detecting glimpses in short-time
segments in a spectro-temporal modulation decomposition of the input
speech signals. Unlike existing glimpse-based SIP methods, the application
of STGI is not limited to additive uncor... | null | null |
qiu21_interspeech | Self-Supervised Learning Based Phone-Fortified Speech Enhancement | [
"Yuanhang Qiu",
"Ruili Wang",
"Satwinder Singh",
"Zhizhong Ma",
"Feng Hou"
] | https://www.isca-archive.org/interspeech_2021/qiu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/qiu21_interspeech.pdf | 10.21437/Interspeech.2021-734 | 211-215 | @inproceedings{qiu21_interspeech,
title = {{Self-Supervised Learning Based Phone-Fortified Speech Enhancement}},
author = {Yuanhang Qiu and Ruili Wang and Satwinder Singh and Zhizhong Ma and Feng Hou},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {211--215},
doi = {10.21437... | For speech enhancement, deep complex network based methods have shown
promising performance due to their effectiveness in dealing with complex-valued
spectrums. Recent speech enhancement methods focus on further optimization
of network structures and hyperparameters, however, ignore inherent
speech characteristics (e.g... | null | null |
nayem21_interspeech | Incorporating Embedding Vectors from a Human Mean-Opinion Score Prediction Model for Monaural Speech Enhancement | [
"Khandokar Md. Nayem",
"Donald S. Williamson"
] | https://www.isca-archive.org/interspeech_2021/nayem21_interspeech.html | https://www.isca-archive.org/interspeech_2021/nayem21_interspeech.pdf | 10.21437/Interspeech.2021-1844 | 216-220 | @inproceedings{nayem21_interspeech,
title = {{Incorporating Embedding Vectors from a Human Mean-Opinion Score Prediction Model for Monaural Speech Enhancement}},
author = {Khandokar Md. Nayem and Donald S. Williamson},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {216--220},
doi ... | Objective measures of success, such as the perceptual evaluation of
speech quality (PESQ), signal-to-distortion ratio (SDR), and short-time
objective intelligibility (STOI), have recently been used to optimize
deep-learning based speech enhancement algorithms, in an effort to
incorporate perceptual constraints into the... | null | null |
zhang21c_interspeech | Restoring Degraded Speech via a Modified Diffusion Model | [
"Jianwei Zhang",
"Suren Jayasuriya",
"Visar Berisha"
] | https://www.isca-archive.org/interspeech_2021/zhang21c_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhang21c_interspeech.pdf | 10.21437/Interspeech.2021-1889 | 221-225 | @inproceedings{zhang21c_interspeech,
title = {{Restoring Degraded Speech via a Modified Diffusion Model}},
author = {Jianwei Zhang and Suren Jayasuriya and Visar Berisha},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {221--225},
doi = {10.21437/Interspeech.2021-1889},
iss... | There are many deterministic mathematical operations (e.g. compression,
clipping, downsampling) that degrade speech quality considerably. In
this paper we introduce a neural network architecture, based on a modification
of the DiffWave model, that aims to restore the original speech signal.
DiffWave, a recently publish... | 2104.11347 | title_snapshot |
nguyen21_interspeech | User-Initiated Repetition-Based Recovery in Multi-Utterance Dialogue Systems | [
"Hoang Long Nguyen",
"Vincent Renkens",
"Joris Pelemans",
"Srividya Pranavi Potharaju",
"Anil Kumar Nalamalapu",
"Murat Akbacak"
] | https://www.isca-archive.org/interspeech_2021/nguyen21_interspeech.html | https://www.isca-archive.org/interspeech_2021/nguyen21_interspeech.pdf | 10.21437/Interspeech.2021-1536 | 226-230 | @inproceedings{nguyen21_interspeech,
title = {{User-Initiated Repetition-Based Recovery in Multi-Utterance Dialogue Systems}},
author = {Hoang Long Nguyen and Vincent Renkens and Joris Pelemans and Srividya Pranavi Potharaju and Anil Kumar Nalamalapu and Murat Akbacak},
year = {2021},
booktitle = {{... | Recognition errors are common in human communication. Similar errors
often lead to unwanted behaviour in dialogue systems or virtual assistants.
In human communication, we can recover from them by repeating misrecognized
words or phrases; however in human-machine communication this recovery
mechanism is not available. ... | 2108.01208 | title_snapshot |
chen21_interspeech | Self-Supervised Dialogue Learning for Spoken Conversational Question Answering | [
"Nuo Chen",
"Chenyu You",
"Yuexian Zou"
] | https://www.isca-archive.org/interspeech_2021/chen21_interspeech.html | https://www.isca-archive.org/interspeech_2021/chen21_interspeech.pdf | 10.21437/Interspeech.2021-120 | 231-235 | @inproceedings{chen21_interspeech,
title = {{Self-Supervised Dialogue Learning for Spoken Conversational Question Answering}},
author = {Nuo Chen and Chenyu You and Yuexian Zou},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {231--235},
doi = {10.21437/Interspeech.2021-120},... | In spoken conversational question answering (SCQA), the answer to the
corresponding question is generated by retrieving and then analyzing
a fixed spoken document, including multi-part conversations. Most SCQA
systems have considered only retrieving information from ordered utterances.
However, the sequential order of ... | 2106.02182 | title_snapshot |
su21_interspeech | Act-Aware Slot-Value Predicting in Multi-Domain Dialogue State Tracking | [
"Ruolin Su",
"Ting-Wei Wu",
"Biing-Hwang Juang"
] | https://www.isca-archive.org/interspeech_2021/su21_interspeech.html | https://www.isca-archive.org/interspeech_2021/su21_interspeech.pdf | 10.21437/Interspeech.2021-138 | 236-240 | @inproceedings{su21_interspeech,
title = {{Act-Aware Slot-Value Predicting in Multi-Domain Dialogue State Tracking}},
author = {Ruolin Su and Ting-Wei Wu and Biing-Hwang Juang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {236--240},
doi = {10.21437/Interspeech.2021-138},
... | As an essential component in task-oriented dialogue systems, dialogue
state tracking (DST) aims to track human-machine interactions and generate
state representations for managing the dialogue. Representations of
dialogue states are dependent on the domain ontology and the user’s
goals. In several task-oriented dialogu... | 2208.02462 | title_snapshot |
chiba21_interspeech | Dialogue Situation Recognition for Everyday Conversation Using Multimodal Information | [
"Yuya Chiba",
"Ryuichiro Higashinaka"
] | https://www.isca-archive.org/interspeech_2021/chiba21_interspeech.html | https://www.isca-archive.org/interspeech_2021/chiba21_interspeech.pdf | 10.21437/Interspeech.2021-171 | 241-245 | @inproceedings{chiba21_interspeech,
title = {{Dialogue Situation Recognition for Everyday Conversation Using Multimodal Information}},
author = {Yuya Chiba and Ryuichiro Higashinaka},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {241--245},
doi = {10.21437/Interspeech.2021-... | In recent years, dialogue systems have been applied to daily living.
Such systems should be able to associate conversations with dialogue
situations, such as a place where a dialogue occurs and the relationship
between participants. In this study, we propose a dialogue situation
recognition method that understands the ... | null | null |
yamazaki21_interspeech | Neural Spoken-Response Generation Using Prosodic and Linguistic Context for Conversational Systems | [
"Yoshihiro Yamazaki",
"Yuya Chiba",
"Takashi Nose",
"Akinori Ito"
] | https://www.isca-archive.org/interspeech_2021/yamazaki21_interspeech.html | https://www.isca-archive.org/interspeech_2021/yamazaki21_interspeech.pdf | 10.21437/Interspeech.2021-381 | 246-250 | @inproceedings{yamazaki21_interspeech,
title = {{Neural Spoken-Response Generation Using Prosodic and Linguistic Context for Conversational Systems}},
author = {Yoshihiro Yamazaki and Yuya Chiba and Takashi Nose and Akinori Ito},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {246--2... | Spoken dialogue systems have become widely used in daily life. Such
a system must interact with the user socially to truly operate as a
partner with humans. In studies of recent dialogue systems, neural
response generation led to natural response generation. However, these
studies have not considered the acoustic aspec... | null | null |
xu21_interspeech | Semantic Transportation Prototypical Network for Few-Shot Intent Detection | [
"Weiyuan Xu",
"Peilin Zhou",
"Chenyu You",
"Yuexian Zou"
] | https://www.isca-archive.org/interspeech_2021/xu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/xu21_interspeech.pdf | 10.21437/Interspeech.2021-548 | 251-255 | @inproceedings{xu21_interspeech,
title = {{Semantic Transportation Prototypical Network for Few-Shot Intent Detection}},
author = {Weiyuan Xu and Peilin Zhou and Chenyu You and Yuexian Zou},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {251--255},
doi = {10.21437/Interspeec... | Few-shot intent detection is a problem that only a few annotated examples
are available for unseen intents, and deep models could suffer from
the overfitting problem because of scarce data. Existing state-of-the-art
few-shot model, Prototypical Network (PN), mainly focus on computing
the similarity between examples in ... | null | null |
tang21_interspeech | Domain-Specific Multi-Agent Dialog Policy Learning in Multi-Domain Task-Oriented Scenarios | [
"Li Tang",
"Yuke Si",
"Longbiao Wang",
"Jianwu Dang"
] | https://www.isca-archive.org/interspeech_2021/tang21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tang21_interspeech.pdf | 10.21437/Interspeech.2021-887 | 256-260 | @inproceedings{tang21_interspeech,
title = {{Domain-Specific Multi-Agent Dialog Policy Learning in Multi-Domain Task-Oriented Scenarios}},
author = {Li Tang and Yuke Si and Longbiao Wang and Jianwu Dang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {256--260},
doi = {10.21... | Traditional dialog policy learning methods train a generic dialog agent
to address all situations. However, when the dialog agent encounters
a complicated task that involves more than one domain, it becomes difficult
to perform concordant actions due to the hybrid information in the
multi-domain ontology. Inspired by a... | null | null |
wang21b_interspeech | Leveraging ASR N-Best in Deep Entity Retrieval | [
"Haoyu Wang",
"John Chen",
"Majid Laali",
"Kevin Durda",
"Jeff King",
"William Campbell",
"Yang Liu"
] | https://www.isca-archive.org/interspeech_2021/wang21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/wang21b_interspeech.pdf | 10.21437/Interspeech.2021-1370 | 261-265 | @inproceedings{wang21b_interspeech,
title = {{Leveraging ASR N-Best in Deep Entity Retrieval}},
author = {Haoyu Wang and John Chen and Majid Laali and Kevin Durda and Jeff King and William Campbell and Yang Liu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {261--265},
doi ... | Entity Retrieval (ER) in spoken dialog systems is a task that retrieves
entities in a catalog for the entity mentions in user utterances. ER
systems are susceptible to upstream errors, with Automatic Speech Recognition
(ASR) errors being particularly troublesome. In this work, we propose
a robust deep learning based ER... | null | null |
zhang21d_interspeech | End-to-End Spelling Correction Conditioned on Acoustic Feature for Code-Switching Speech Recognition | [
"Shuai Zhang",
"Jiangyan Yi",
"Zhengkun Tian",
"Ye Bai",
"Jianhua Tao",
"Xuefei Liu",
"Zhengqi Wen"
] | https://www.isca-archive.org/interspeech_2021/zhang21d_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhang21d_interspeech.pdf | 10.21437/Interspeech.2021-1242 | 266-270 | @inproceedings{zhang21d_interspeech,
title = {{End-to-End Spelling Correction Conditioned on Acoustic Feature for Code-Switching Speech Recognition}},
author = {Shuai Zhang and Jiangyan Yi and Zhengkun Tian and Ye Bai and Jianhua Tao and Xuefei Liu and Zhengqi Wen},
year = {2021},
booktitle = {{Inte... | In this work, we propose a new end-to-end (E2E) spelling correction
method for post-processing of code-switching automatic speech recognition
(ASR). Existing E2E spelling correction models take the hypotheses
of ASR as inputs and annotated text as the targets. Due to the powerful
modeling capabilities of the E2E model,... | null | null |
siminyu21_interspeech | Phoneme Recognition Through Fine Tuning of Phonetic Representations: A Case Study on Luhya Language Varieties | [
"Kathleen Siminyu",
"Xinjian Li",
"Antonios Anastasopoulos",
"David R. Mortensen",
"Michael R. Marlo",
"Graham Neubig"
] | https://www.isca-archive.org/interspeech_2021/siminyu21_interspeech.html | https://www.isca-archive.org/interspeech_2021/siminyu21_interspeech.pdf | 10.21437/Interspeech.2021-1434 | 271-275 | @inproceedings{siminyu21_interspeech,
title = {{Phoneme Recognition Through Fine Tuning of Phonetic Representations: A Case Study on Luhya Language Varieties}},
author = {Kathleen Siminyu and Xinjian Li and Antonios Anastasopoulos and David R. Mortensen and Michael R. Marlo and Graham Neubig},
year = ... | Models pre-trained on multiple languages have shown significant promise
for improving speech recognition, particularly for low-resource languages.
In this work, we focus on phoneme recognition using Allosaurus, a method
for multilingual recognition based on phonetic annotation, which incorporates
phonological knowledge... | 2104.01624 | title_snapshot |
loweimi21_interspeech | Speech Acoustic Modelling Using Raw Source and Filter Components | [
"Erfan Loweimi",
"Zoran Cvetkovic",
"Peter Bell",
"Steve Renals"
] | https://www.isca-archive.org/interspeech_2021/loweimi21_interspeech.html | https://www.isca-archive.org/interspeech_2021/loweimi21_interspeech.pdf | 10.21437/Interspeech.2021-53 | 276-280 | @inproceedings{loweimi21_interspeech,
title = {{Speech Acoustic Modelling Using Raw Source and Filter Components}},
author = {Erfan Loweimi and Zoran Cvetkovic and Peter Bell and Steve Renals},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {276--280},
doi = {10.21437/Intersp... | Source-filter modelling is among the fundamental techniques in speech
processing with a wide range of applications. In acoustic modelling,
features such as MFCC and PLP which parametrise the filter component
are widely employed. In this paper, we investigate the efficacy of
building acoustic models from the raw filter ... | null | null |
fujimoto21_interspeech | Noise Robust Acoustic Modeling for Single-Channel Speech Recognition Based on a Stream-Wise Transformer Architecture | [
"Masakiyo Fujimoto",
"Hisashi Kawai"
] | https://www.isca-archive.org/interspeech_2021/fujimoto21_interspeech.html | https://www.isca-archive.org/interspeech_2021/fujimoto21_interspeech.pdf | 10.21437/Interspeech.2021-225 | 281-285 | @inproceedings{fujimoto21_interspeech,
title = {{Noise Robust Acoustic Modeling for Single-Channel Speech Recognition Based on a Stream-Wise Transformer Architecture}},
author = {Masakiyo Fujimoto and Hisashi Kawai},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {281--285},
doi ... | This paper addresses a noise-robust automatic speech recognition (ASR)
method under the constraints of real-time, one-pass, and single-channel
processing. Under such strong constraints, single-channel speech enhancement
becomes a key technology because methods with multiple-passes or batch
processing, such as acoustic ... | null | null |
ratnarajah21_interspeech | IR-GAN: Room Impulse Response Generator for Far-Field Speech Recognition | [
"Anton Ratnarajah",
"Zhenyu Tang",
"Dinesh Manocha"
] | https://www.isca-archive.org/interspeech_2021/ratnarajah21_interspeech.html | https://www.isca-archive.org/interspeech_2021/ratnarajah21_interspeech.pdf | 10.21437/Interspeech.2021-230 | 286-290 | @inproceedings{ratnarajah21_interspeech,
title = {{IR-GAN: Room Impulse Response Generator for Far-Field Speech Recognition}},
author = {Anton Ratnarajah and Zhenyu Tang and Dinesh Manocha},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {286--290},
doi = {10.21437/Interspeec... | We present a Generative Adversarial Network (GAN) based room impulse
response generator (IR-GAN) for generating realistic synthetic room
impulse responses (RIRs). IR-GAN extracts acoustic parameters from
captured real-world RIRs and uses these parameters to generate new
synthetic RIRs. We use these generated synthetic ... | 2010.13219 | title_snapshot |
chen21b_interspeech | Scaling Sparsemax Based Channel Selection for Speech Recognition with ad-hoc Microphone Arrays | [
"Junqi Chen",
"Xiao-Lei Zhang"
] | https://www.isca-archive.org/interspeech_2021/chen21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/chen21b_interspeech.pdf | 10.21437/Interspeech.2021-419 | 291-295 | @inproceedings{chen21b_interspeech,
title = {{Scaling Sparsemax Based Channel Selection for Speech Recognition with ad-hoc Microphone Arrays}},
author = {Junqi Chen and Xiao-Lei Zhang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {291--295},
doi = {10.21437/Interspeech.202... | Recently, speech recognition with ad-hoc microphone arrays has received
much attention. It is known that channel selection is an important
problem of ad-hoc microphone arrays, however, this topic seems far
from explored in speech recognition yet, particularly with a large-scale
ad-hoc microphone array. To address this ... | 2103.15305 | title_snapshot |
chang21_interspeech | Multi-Channel Transformer Transducer for Speech Recognition | [
"Feng-Ju Chang",
"Martin Radfar",
"Athanasios Mouchtaris",
"Maurizio Omologo"
] | https://www.isca-archive.org/interspeech_2021/chang21_interspeech.html | https://www.isca-archive.org/interspeech_2021/chang21_interspeech.pdf | 10.21437/Interspeech.2021-655 | 296-300 | @inproceedings{chang21_interspeech,
title = {{Multi-Channel Transformer Transducer for Speech Recognition}},
author = {Feng-Ju Chang and Martin Radfar and Athanasios Mouchtaris and Maurizio Omologo},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {296--300},
doi = {10.21437/I... | Multi-channel inputs offer several advantages over single-channel,
to improve the robustness of on-device speech recognition systems.
Recent work on multi-channel transformer, has proposed a way to incorporate
such inputs into end-to-end ASR for improved accuracy. However, this
approach is characterized by a high compu... | 2108.12953 | title_snapshot |
tsunoo21_interspeech | Data Augmentation Methods for End-to-End Speech Recognition on Distant-Talk Scenarios | [
"Emiru Tsunoo",
"Kentaro Shibata",
"Chaitanya Narisetty",
"Yosuke Kashiwagi",
"Shinji Watanabe"
] | https://www.isca-archive.org/interspeech_2021/tsunoo21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tsunoo21_interspeech.pdf | 10.21437/Interspeech.2021-958 | 301-305 | @inproceedings{tsunoo21_interspeech,
title = {{Data Augmentation Methods for End-to-End Speech Recognition on Distant-Talk Scenarios}},
author = {Emiru Tsunoo and Kentaro Shibata and Chaitanya Narisetty and Yosuke Kashiwagi and Shinji Watanabe},
year = {2021},
booktitle = {{Interspeech 2021}},
pag... | Although end-to-end automatic speech recognition (E2E ASR) has achieved
great performance in tasks that have numerous paired data, it is still
challenging to make E2E ASR robust against noisy and low-resource conditions.
In this study, we investigated data augmentation methods for E2E ASR
in distant-talk scenarios. E2E... | 2106.03419 | title_snapshot |
ma21_interspeech | Leveraging Phone Mask Training for Phonetic-Reduction-Robust E2E Uyghur Speech Recognition | [
"Guodong Ma",
"Pengfei Hu",
"Jian Kang",
"Shen Huang",
"Hao Huang"
] | https://www.isca-archive.org/interspeech_2021/ma21_interspeech.html | https://www.isca-archive.org/interspeech_2021/ma21_interspeech.pdf | 10.21437/Interspeech.2021-964 | 306-310 | @inproceedings{ma21_interspeech,
title = {{Leveraging Phone Mask Training for Phonetic-Reduction-Robust E2E Uyghur Speech Recognition}},
author = {Guodong Ma and Pengfei Hu and Jian Kang and Shen Huang and Hao Huang},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {306--310},
doi ... | In Uyghur speech, consonant and vowel reduction are often encountered,
especially in spontaneous speech with high speech rate, which will
cause a degradation of speech recognition performance. To solve this
problem, we propose an effective phone mask training method for Conformer-based
Uyghur end-to-end (E2E) speech re... | 2204.00819 | title_snapshot |
likhomanenko21_interspeech | Rethinking Evaluation in ASR: Are Our Models Robust Enough? | [
"Tatiana Likhomanenko",
"Qiantong Xu",
"Vineel Pratap",
"Paden Tomasello",
"Jacob Kahn",
"Gilad Avidov",
"Ronan Collobert",
"Gabriel Synnaeve"
] | https://www.isca-archive.org/interspeech_2021/likhomanenko21_interspeech.html | https://www.isca-archive.org/interspeech_2021/likhomanenko21_interspeech.pdf | 10.21437/Interspeech.2021-1758 | 311-315 | @inproceedings{likhomanenko21_interspeech,
title = {{Rethinking Evaluation in ASR: Are Our Models Robust Enough?}},
author = {Tatiana Likhomanenko and Qiantong Xu and Vineel Pratap and Paden Tomasello and Jacob Kahn and Gilad Avidov and Ronan Collobert and Gabriel Synnaeve},
year = {2021},
booktitle... | Is pushing numbers on a single benchmark valuable in automatic speech
recognition? Research results in acoustic modeling are typically evaluated
based on performance on a single dataset. While the research community
has coalesced around various benchmarks, we set out to understand generalization
performance in acoustic... | 2010.11745 | title_snapshot |
lam21_interspeech | Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition | [
"Max W.Y. Lam",
"Jun Wang",
"Chao Weng",
"Dan Su",
"Dong Yu"
] | https://www.isca-archive.org/interspeech_2021/lam21_interspeech.html | https://www.isca-archive.org/interspeech_2021/lam21_interspeech.pdf | 10.21437/Interspeech.2021-2084 | 316-320 | @inproceedings{lam21_interspeech,
title = {{Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition}},
author = {Max W.Y. Lam and Jun Wang and Chao Weng and Dan Su and Dong Yu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | End-to-end speech recognition generally uses hand-engineered acoustic
features as input and excludes the feature extraction module from its
joint optimization. To extract learnable and adaptive features and
mitigate information loss, we propose a new encoder that adopts globally
attentive locally recurrent (GALR) netwo... | 2106.04275 | title_snapshot |
hou21_interspeech | Attention-Based Cross-Modal Fusion for Audio-Visual Voice Activity Detection in Musical Video Streams | [
"Yuanbo Hou",
"Zhesong Yu",
"Xia Liang",
"Xingjian Du",
"Bilei Zhu",
"Zejun Ma",
"Dick Botteldooren"
] | https://www.isca-archive.org/interspeech_2021/hou21_interspeech.html | https://www.isca-archive.org/interspeech_2021/hou21_interspeech.pdf | 10.21437/Interspeech.2021-37 | 321-325 | @inproceedings{hou21_interspeech,
title = {{Attention-Based Cross-Modal Fusion for Audio-Visual Voice Activity Detection in Musical Video Streams}},
author = {Yuanbo Hou and Zhesong Yu and Xia Liang and Xingjian Du and Bilei Zhu and Zejun Ma and Dick Botteldooren},
year = {2021},
booktitle = {{Inter... | Many previous audio-visual voice-related works focus on speech, ignoring
the singing voice in the growing number of musical video streams on
the Internet. For processing diverse musical video data, voice activity
detection is a necessary step. This paper attempts to detect the speech
and singing voices of target perfor... | 2106.11411 | title_snapshot |
kim21b_interspeech | Noise-Tolerant Self-Supervised Learning for Audio-Visual Voice Activity Detection | [
"Ui-Hyun Kim"
] | https://www.isca-archive.org/interspeech_2021/kim21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/kim21b_interspeech.pdf | 10.21437/Interspeech.2021-43 | 326-330 | @inproceedings{kim21b_interspeech,
title = {{Noise-Tolerant Self-Supervised Learning for Audio-Visual Voice Activity Detection}},
author = {Ui-Hyun Kim},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {326--330},
doi = {10.21437/Interspeech.2021-43},
issn = {2958-1796}... | Recent audio-visual voice activity detectors based on supervised learning
require large amounts of labeled training data with manual mouth-region
cropping in videos, and the performance is sensitive to a mismatch
between the training and testing noise conditions. This paper introduces
contrastive self-supervised learni... | null | null |
park21_interspeech | Noisy Student-Teacher Training for Robust Keyword Spotting | [
"Hyun-Jin Park",
"Pai Zhu",
"Ignacio Lopez Moreno",
"Niranjan Subrahmanya"
] | https://www.isca-archive.org/interspeech_2021/park21_interspeech.html | https://www.isca-archive.org/interspeech_2021/park21_interspeech.pdf | 10.21437/Interspeech.2021-72 | 331-335 | @inproceedings{park21_interspeech,
title = {{Noisy Student-Teacher Training for Robust Keyword Spotting}},
author = {Hyun-Jin Park and Pai Zhu and Ignacio Lopez Moreno and Niranjan Subrahmanya},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {331--335},
doi = {10.21437/Inters... | We propose self-training with noisy student-teacher approach for streaming
keyword spotting, that can utilize large-scale unlabeled data and aggressive
data augmentation. The proposed method applies aggressive data augmentation
(spectral augmentation) on the input of both student and teacher and
utilize unlabeled data ... | 2106.01604 | title_snapshot |
ichikawa21_interspeech | Multi-Channel VAD for Transcription of Group Discussion | [
"Osamu Ichikawa",
"Kaito Nakano",
"Takahiro Nakayama",
"Hajime Shirouzu"
] | https://www.isca-archive.org/interspeech_2021/ichikawa21_interspeech.html | https://www.isca-archive.org/interspeech_2021/ichikawa21_interspeech.pdf | 10.21437/Interspeech.2021-200 | 336-340 | @inproceedings{ichikawa21_interspeech,
title = {{Multi-Channel VAD for Transcription of Group Discussion}},
author = {Osamu Ichikawa and Kaito Nakano and Takahiro Nakayama and Hajime Shirouzu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {336--340},
doi = {10.21437/Intersp... | Attempts are being made to visualize the learning process by attaching
microphones to students participating in group works conducted in classrooms,
and subsequently, their speech using an automatic speech recognition
(ASR) system. However, the voices of nearby students frequently become
mixed with the output speech da... | null | null |
zhou21_interspeech | Audio-Visual Information Fusion Using Cross-Modal Teacher-Student Learning for Voice Activity Detection in Realistic Environments | [
"Hengshun Zhou",
"Jun Du",
"Hang Chen",
"Zijun Jing",
"Shifu Xiong",
"Chin-Hui Lee"
] | https://www.isca-archive.org/interspeech_2021/zhou21_interspeech.html | https://www.isca-archive.org/interspeech_2021/zhou21_interspeech.pdf | 10.21437/Interspeech.2021-592 | 341-345 | @inproceedings{zhou21_interspeech,
title = {{Audio-Visual Information Fusion Using Cross-Modal Teacher-Student Learning for Voice Activity Detection in Realistic Environments}},
author = {Hengshun Zhou and Jun Du and Hang Chen and Zijun Jing and Shifu Xiong and Chin-Hui Lee},
year = {2021},
booktitl... | We propose an information fusion approach to audio-visual voice activity
detection (AV-VAD) based on cross-modal teacher-student learning leveraging
on factorized bilinear pooling (FBP) and Kullback-Leibler (KL) regularization.
First, we design an audio-visual network by using FBP fusion to fully
utilize the interactio... | null | null |
makishima21_interspeech | Enrollment-Less Training for Personalized Voice Activity Detection | [
"Naoki Makishima",
"Mana Ihori",
"Tomohiro Tanaka",
"Akihiko Takashima",
"Shota Orihashi",
"Ryo Masumura"
] | https://www.isca-archive.org/interspeech_2021/makishima21_interspeech.html | https://www.isca-archive.org/interspeech_2021/makishima21_interspeech.pdf | 10.21437/Interspeech.2021-731 | 346-350 | @inproceedings{makishima21_interspeech,
title = {{Enrollment-Less Training for Personalized Voice Activity Detection}},
author = {Naoki Makishima and Mana Ihori and Tomohiro Tanaka and Akihiko Takashima and Shota Orihashi and Ryo Masumura},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | We present a novel personalized voice activity detection (PVAD) learning
method that does not require enrollment data during training. PVAD
is a task to detect the speech segments of a specific target speaker
at the frame level using enrollment speech of the target speaker. Since
PVAD must learn speakers’ speech variat... | 2106.12132 | title_snapshot |
nonaka21_interspeech | Voice Activity Detection for Live Speech of Baseball Game Based on Tandem Connection with Speech/Noise Separation Model | [
"Yuto Nonaka",
"Chee Siang Leow",
"Akio Kobayashi",
"Takehito Utsuro",
"Hiromitsu Nishizaki"
] | https://www.isca-archive.org/interspeech_2021/nonaka21_interspeech.html | https://www.isca-archive.org/interspeech_2021/nonaka21_interspeech.pdf | 10.21437/Interspeech.2021-792 | 351-355 | @inproceedings{nonaka21_interspeech,
title = {{Voice Activity Detection for Live Speech of Baseball Game Based on Tandem Connection with Speech/Noise Separation Model}},
author = {Yuto Nonaka and Chee Siang Leow and Akio Kobayashi and Takehito Utsuro and Hiromitsu Nishizaki},
year = {2021},
booktitl... | When applying voice activity detection (VAD) to a noisy sound, in general,
noise reduction (speech separation) and VAD are performed separately.
In this case, the noise reduction may suppress the speech, and the
VAD may not work well for the speech after the noise reduction. This
study proposes a VAD model through the ... | null | null |
kwon21_interspeech | FastICARL: Fast Incremental Classifier and Representation Learning with Efficient Budget Allocation in Audio Sensing Applications | [
"Young D. Kwon",
"Jagmohan Chauhan",
"Cecilia Mascolo"
] | https://www.isca-archive.org/interspeech_2021/kwon21_interspeech.html | https://www.isca-archive.org/interspeech_2021/kwon21_interspeech.pdf | 10.21437/Interspeech.2021-1091 | 356-360 | @inproceedings{kwon21_interspeech,
title = {{FastICARL: Fast Incremental Classifier and Representation Learning with Efficient Budget Allocation in Audio Sensing Applications}},
author = {Young D. Kwon and Jagmohan Chauhan and Cecilia Mascolo},
year = {2021},
booktitle = {{Interspeech 2021}},
page... | Various incremental learning (IL) approaches have been proposed to
help deep learning models learn new tasks/classes continuously without
forgetting what was learned previously (i.e., avoid catastrophic forgetting).
With the growing number of deployed audio sensing applications that
need to dynamically incorporate new ... | 2106.07268 | title_snapshot |
wei21_interspeech | End-to-End Transformer-Based Open-Vocabulary Keyword Spotting with Location-Guided Local Attention | [
"Bo Wei",
"Meirong Yang",
"Tao Zhang",
"Xiao Tang",
"Xing Huang",
"Kyuhong Kim",
"Jaeyun Lee",
"Kiho Cho",
"Sung-Un Park"
] | https://www.isca-archive.org/interspeech_2021/wei21_interspeech.html | https://www.isca-archive.org/interspeech_2021/wei21_interspeech.pdf | 10.21437/Interspeech.2021-1335 | 361-365 | @inproceedings{wei21_interspeech,
title = {{End-to-End Transformer-Based Open-Vocabulary Keyword Spotting with Location-Guided Local Attention}},
author = {Bo Wei and Meirong Yang and Tao Zhang and Xiao Tang and Xing Huang and Kyuhong Kim and Jaeyun Lee and Kiho Cho and Sung-Un Park},
year = {2021},
... | Open-vocabulary keyword spotting (KWS) aims to detect arbitrary keywords
from continuous speech, which allows users to define their personal
keywords. In this paper, we propose a novel location guided end-to-end
(E2E) keyword spotting system. Firstly, we predict endpoints of keyword
in the entire speech based on attent... | null | null |
bhati21_interspeech | Segmental Contrastive Predictive Coding for Unsupervised Word Segmentation | [
"Saurabhchand Bhati",
"Jesús Villalba",
"Piotr Żelasko",
"Laureano Moro-Velázquez",
"Najim Dehak"
] | https://www.isca-archive.org/interspeech_2021/bhati21_interspeech.html | https://www.isca-archive.org/interspeech_2021/bhati21_interspeech.pdf | 10.21437/Interspeech.2021-1874 | 366-370 | @inproceedings{bhati21_interspeech,
title = {{Segmental Contrastive Predictive Coding for Unsupervised Word Segmentation}},
author = {Saurabhchand Bhati and Jesús Villalba and Piotr Żelasko and Laureano Moro-Velázquez and Najim Dehak},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {... | Automatic detection of phoneme or word-like units is one of the core
objectives in zero-resource speech processing. Recent attempts employ
self-supervised training methods, such as contrastive predictive coding
(CPC), where the next frame is predicted given past context. However,
CPC only looks at the audio signal’s fr... | 2106.02170 | title_snapshot |
xu21b_interspeech | A Lightweight Framework for Online Voice Activity Detection in the Wild | [
"Xuenan Xu",
"Heinrich Dinkel",
"Mengyue Wu",
"Kai Yu"
] | https://www.isca-archive.org/interspeech_2021/xu21b_interspeech.html | https://www.isca-archive.org/interspeech_2021/xu21b_interspeech.pdf | 10.21437/Interspeech.2021-1977 | 371-375 | @inproceedings{xu21b_interspeech,
title = {{A Lightweight Framework for Online Voice Activity Detection in the Wild}},
author = {Xuenan Xu and Heinrich Dinkel and Mengyue Wu and Kai Yu},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {371--375},
doi = {10.21437/Interspeech.20... | Voice activity detection (VAD) is an essential pre-processing component
for speech-related tasks such as automatic speech recognition (ASR).
Traditional VAD systems require strong frame-level supervision for
training, inhibiting their performance in real-world test scenarios.
Previously, the general-purpose VAD (GPVAD)... | null | null |
chlebowski21_interspeech | “See what I mean, huh?” Evaluating Visual Inspection of F Tracking in Nasal Grunts | [
"Aurélie Chlébowski",
"Nicolas Ballier"
] | https://www.isca-archive.org/interspeech_2021/chlebowski21_interspeech.html | https://www.isca-archive.org/interspeech_2021/chlebowski21_interspeech.pdf | 10.21437/Interspeech.2021-129 | 376-380 | @inproceedings{chlebowski21_interspeech,
title = {{“See what I mean, huh?” Evaluating Visual Inspection of F0 Tracking in Nasal Grunts}},
author = {Aurélie Chlébowski and Nicolas Ballier},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {376--380},
doi = {10.21437/Interspeech.... | This paper proposes to evaluate the method used in Chlébowski
and Ballier [1] for the annotation of F 0 variations in nasal
grunts. We discuss and test issues raised by this kind of approach
exclusively based on visual inspection of the F 0 tracking
in Praat [2]. Results tend to show that consistency in the annotation
... | null | null |
wang21c_interspeech | System Performance as a Function of Calibration Methods, Sample Size and Sampling Variability in Likelihood Ratio-Based Forensic Voice Comparison | [
"Bruce Xiao Wang",
"Vincent Hughes"
] | https://www.isca-archive.org/interspeech_2021/wang21c_interspeech.html | https://www.isca-archive.org/interspeech_2021/wang21c_interspeech.pdf | 10.21437/Interspeech.2021-267 | 381-385 | @inproceedings{wang21c_interspeech,
title = {{System Performance as a Function of Calibration Methods, Sample Size and Sampling Variability in Likelihood Ratio-Based Forensic Voice Comparison}},
author = {Bruce Xiao Wang and Vincent Hughes},
year = {2021},
booktitle = {{Interspeech 2021}},
pages ... | In data-driven forensic voice comparison, sample size is an issue which
can have substantial effects on system output. Numerous calibration
methods have been developed and some have been proposed as solutions
to sample size issues. In this paper, we test four calibration methods
(i.e. logistic regression, regularised l... | null | null |
bonneau21_interspeech | Voicing Assimilations by French Speakers of German in Stop-Fricative Sequences | [
"Anne Bonneau"
] | https://www.isca-archive.org/interspeech_2021/bonneau21_interspeech.html | https://www.isca-archive.org/interspeech_2021/bonneau21_interspeech.pdf | 10.21437/Interspeech.2021-601 | 386-390 | @inproceedings{bonneau21_interspeech,
title = {{Voicing Assimilations by French Speakers of German in Stop-Fricative Sequences}},
author = {Anne Bonneau},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {386--390},
doi = {10.21437/Interspeech.2021-601},
issn = {2958-179... | Voicing assimilations inside groups of obstruents occur in opposite
directions in French and German, where they are respectively regressive
and progressive. The aim of the study is to investigate (1) whether
non native speakers (here French learners of German) are apt to acquire
subtle L2 specificities like assimilatio... | null | null |
chakraborty21_interspeech | The Four-Way Classification of Stops with Voicing and Aspiration for Non-Native Speech Evaluation | [
"Titas Chakraborty",
"Vaishali Patil",
"Preeti Rao"
] | https://www.isca-archive.org/interspeech_2021/chakraborty21_interspeech.html | https://www.isca-archive.org/interspeech_2021/chakraborty21_interspeech.pdf | 10.21437/Interspeech.2021-635 | 391-395 | @inproceedings{chakraborty21_interspeech,
title = {{The Four-Way Classification of Stops with Voicing and Aspiration for Non-Native Speech Evaluation}},
author = {Titas Chakraborty and Vaishali Patil and Preeti Rao},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {391--395},
doi ... | The four-way distinction of plosives in terms of voicing and aspiration
is rare in the world’s languages, but is an important characteristic
of the Indo-Aryan language family. Both perception and production pose
challenges to the language learner whose native tongue does not afford
the specific distinctions. A study of... | null | null |
urooj21_interspeech | Acoustic and Prosodic Correlates of Emotions in Urdu Speech | [
"Saba Urooj",
"Benazir Mumtaz",
"Sarmad Hussain",
"Ehsan ul Haq"
] | https://www.isca-archive.org/interspeech_2021/urooj21_interspeech.html | https://www.isca-archive.org/interspeech_2021/urooj21_interspeech.pdf | 10.21437/Interspeech.2021-910 | 396-400 | @inproceedings{urooj21_interspeech,
title = {{Acoustic and Prosodic Correlates of Emotions in Urdu Speech}},
author = {Saba Urooj and Benazir Mumtaz and Sarmad Hussain and Ehsan ul Haq},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {396--400},
doi = {10.21437/Interspeech.20... | Emotional speech corpora exhibit differences in duration, intensity
and fundamental frequency. We investigated acoustic as well as prosodic
correlates of emotional speech in Urdu. We recorded a corpus of 23
sentences from four speakers of Urdu covering four emotional states.
Main results show that: a) sadness exhibits ... | null | null |
tamim21_interspeech | Voicing Contrasts in the Singleton Stops of Palestinian Arabic: Production and Perception | [
"Nour Tamim",
"Silke Hamann"
] | https://www.isca-archive.org/interspeech_2021/tamim21_interspeech.html | https://www.isca-archive.org/interspeech_2021/tamim21_interspeech.pdf | 10.21437/Interspeech.2021-1079 | 401-405 | @inproceedings{tamim21_interspeech,
title = {{Voicing Contrasts in the Singleton Stops of Palestinian Arabic: Production and Perception}},
author = {Nour Tamim and Silke Hamann},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {401--405},
doi = {10.21437/Interspeech.2021-1079}... | This study investigates the stop voicing contrast in Palestinian Arabic
(PA) by examining Voice Onset Time (VOT) in both production and perception.
An acoustic analysis of the recordings of 8 speakers showed that word-initial
voiced stops in sentence context have an average VOT of -93 msec, and
word-initial voiceless s... | null | null |
coy21_interspeech | A Comparison of the Accuracy of Dissen and Keshet’s (2016) DeepFormants and Traditional LPC Methods for Semi-Automatic Speaker Recognition | [
"Thomas Coy",
"Vincent Hughes",
"Philip Harrison",
"Amelia J. Gully"
] | https://www.isca-archive.org/interspeech_2021/coy21_interspeech.html | https://www.isca-archive.org/interspeech_2021/coy21_interspeech.pdf | 10.21437/Interspeech.2021-1487 | 406-410 | @inproceedings{coy21_interspeech,
title = {{A Comparison of the Accuracy of Dissen and Keshet’s (2016) DeepFormants and Traditional LPC Methods for Semi-Automatic Speaker Recognition}},
author = {Thomas Coy and Vincent Hughes and Philip Harrison and Amelia J. Gully},
year = {2021},
booktitle = {{Int... | There is a growing trend in the field of forensic speech science towards
integrating the vanguard of speech technology with traditional linguistic
methods in pursuit of both scalable (i.e. automatable) and accurate
evidential methods. To this end, this paper investigates DeepFormants,
a DNN formant estimator which its ... | null | null |
jessen21_interspeech | MAP Adaptation Characteristics in Forensic Long-Term Formant Analysis | [
"Michael Jessen"
] | https://www.isca-archive.org/interspeech_2021/jessen21_interspeech.html | https://www.isca-archive.org/interspeech_2021/jessen21_interspeech.pdf | 10.21437/Interspeech.2021-1697 | 411-415 | @inproceedings{jessen21_interspeech,
title = {{MAP Adaptation Characteristics in Forensic Long-Term Formant Analysis}},
author = {Michael Jessen},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {411--415},
doi = {10.21437/Interspeech.2021-1697},
issn = {2958-1796},
} | Forensic data from long-term formant analysis were used as input to
the GMM-UBM approach, which is a way of deriving Likelihood Ratios.
Tests were performed running 22 same-speaker comparisons and 462 different-speaker
comparisons from a corpus of anonymized casework data involving telephone-intercepted
speech. In a fi... | null | null |
lo21_interspeech | Cross-Linguistic Speaker Individuality of Long-Term Formant Distributions: Phonetic and Forensic Perspectives | [
"Justin J.H. Lo"
] | https://www.isca-archive.org/interspeech_2021/lo21_interspeech.html | https://www.isca-archive.org/interspeech_2021/lo21_interspeech.pdf | 10.21437/Interspeech.2021-1699 | 416-420 | @inproceedings{lo21_interspeech,
title = {{Cross-Linguistic Speaker Individuality of Long-Term Formant Distributions: Phonetic and Forensic Perspectives}},
author = {Justin J.H. Lo},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {416--420},
doi = {10.21437/Interspeech.2021-1... | This study considers issues of language- and speaker-specificity in
long-term formant distributions (LTFDs) from phonetic and forensic
perspectives and examines their potential value in cases of cross-language
forensic voice comparison. Acoustic analysis of 60 male English–French
bilinguals revealed systematic differen... | null | null |
soo21_interspeech | Sound Change in Spontaneous Bilingual Speech: A Corpus Study on the Cantonese n-l Merger in Cantonese-English Bilinguals | [
"Rachel Soo",
"Khia A. Johnson",
"Molly Babel"
] | https://www.isca-archive.org/interspeech_2021/soo21_interspeech.html | https://www.isca-archive.org/interspeech_2021/soo21_interspeech.pdf | 10.21437/Interspeech.2021-1754 | 421-425 | @inproceedings{soo21_interspeech,
title = {{Sound Change in Spontaneous Bilingual Speech: A Corpus Study on the Cantonese n-l Merger in Cantonese-English Bilinguals}},
author = {Rachel Soo and Khia A. Johnson and Molly Babel},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {421--425}... | In Cantonese and several other Chinese languages, /n/ is merging with
/l/. The Cantonese merger appears categorical, with /n/ becoming /l/
word-initially. This project aims to describe the status of /n/ and
/l/ in bilingual Cantonese and English speech to better understand
individual differences at the interface of cro... | null | null |
lalhminghlui21_interspeech | Characterizing Voiced and Voiceless Nasals in Mizo | [
"Wendy Lalhminghlui",
"Priyankoo Sarmah"
] | https://www.isca-archive.org/interspeech_2021/lalhminghlui21_interspeech.html | https://www.isca-archive.org/interspeech_2021/lalhminghlui21_interspeech.pdf | 10.21437/Interspeech.2021-2104 | 426-430 | @inproceedings{lalhminghlui21_interspeech,
title = {{Characterizing Voiced and Voiceless Nasals in Mizo}},
author = {Wendy Lalhminghlui and Priyankoo Sarmah},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {426--430},
doi = {10.21437/Interspeech.2021-2104},
issn = {295... | Mizo has voicing contrasts in nasals. This study investigates the acoustic
properties of Mizo voiced and voiceless nasals using nasometric measurements.
The dual channel data obtained for Mizo nasals is separated into oral
and nasal channels and nasalance is calculated at every 10% of the
duration of the nasals. Apart ... | null | null |
schuller21_interspeech | The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates | [
"Björn W. Schuller",
"Anton Batliner",
"Christian Bergler",
"Cecilia Mascolo",
"Jing Han",
"Iulia Lefter",
"Heysem Kaya",
"Shahin Amiriparian",
"Alice Baird",
"Lukas Stappen",
"Sandra Ottl",
"Maurice Gerczuk",
"Panagiotis Tzirakis",
"Chloë Brown",
"Jagmohan Chauhan",
"Andreas Grammenos... | https://www.isca-archive.org/interspeech_2021/schuller21_interspeech.html | https://www.isca-archive.org/interspeech_2021/schuller21_interspeech.pdf | 10.21437/Interspeech.2021-19 | 431-435 | @inproceedings{schuller21_interspeech,
title = {{The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates}},
author = {Björn W. Schuller and Anton Batliner and Christian Bergler and Cecilia Mascolo and Jing Han and Iulia Lefter and Heysem Kaya and S... | The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses
four different problems for the first time in a research competition
under well-defined conditions: In the COVID-19 Cough and COVID-19
Speech Sub-Challenges, a binary classification on COVID-19 infection
has to be made based on coughing sounds and s... | 2102.13468 | title_snapshot |
soleraurena21_interspeech | Transfer Learning-Based Cough Representations for Automatic Detection of COVID-19 | [
"Rubén Solera-Ureña",
"Catarina Botelho",
"Francisco Teixeira",
"Thomas Rolland",
"Alberto Abad",
"Isabel Trancoso"
] | https://www.isca-archive.org/interspeech_2021/soleraurena21_interspeech.html | https://www.isca-archive.org/interspeech_2021/soleraurena21_interspeech.pdf | 10.21437/Interspeech.2021-1702 | 436-440 | @inproceedings{soleraurena21_interspeech,
title = {{Transfer Learning-Based Cough Representations for Automatic Detection of COVID-19}},
author = {Rubén Solera-Ureña and Catarina Botelho and Francisco Teixeira and Thomas Rolland and Alberto Abad and Isabel Trancoso},
year = {2021},
booktitle = {{Int... | In the last months, there has been an increasing interest in developing
reliable, cost-effective, immediate and easy to use machine learning
based tools that can help health care operators, institutions, companies,
etc. to optimize their screening campaigns. In this line, several initiatives
emerged aimed at the automa... | null | null |
klumpp21_interspeech | The Phonetic Footprint of Covid-19? | [
"P. Klumpp",
"T. Bocklet",
"T. Arias-Vergara",
"J.C. Vásquez-Correa",
"P.A. Pérez-Toro",
"S.P. Bayerl",
"J.R. Orozco-Arroyave",
"Elmar Nöth"
] | https://www.isca-archive.org/interspeech_2021/klumpp21_interspeech.html | https://www.isca-archive.org/interspeech_2021/klumpp21_interspeech.pdf | 10.21437/Interspeech.2021-1488 | 441-445 | @inproceedings{klumpp21_interspeech,
title = {{The Phonetic Footprint of Covid-19?}},
author = {P. Klumpp and T. Bocklet and T. Arias-Vergara and J.C. Vásquez-Correa and P.A. Pérez-Toro and S.P. Bayerl and J.R. Orozco-Arroyave and Elmar Nöth},
year = {2021},
booktitle = {{Interspeech 2021}},
pages... | Against the background of the ongoing pandemic, this year’s Computational
Paralinguistics Challenge featured a classification problem to detect
Covid-19 from speech recordings. The presented approach is based on
a phonetic analysis of speech samples, thus it enabled us not only
to discriminate between Covid and non-Cov... | null | null |
casanova21_interspeech | Transfer Learning and Data Augmentation Techniques to the COVID-19 Identification Tasks in ComParE 2021 | [
"Edresson Casanova",
"Arnaldo Candido Jr.",
"Ricardo Corso Fernandes Jr.",
"Marcelo Finger",
"Lucas Rafael Stefanel Gris",
"Moacir Antonelli Ponti",
"Daniel Peixoto Pinto da Silva"
] | https://www.isca-archive.org/interspeech_2021/casanova21_interspeech.html | https://www.isca-archive.org/interspeech_2021/casanova21_interspeech.pdf | 10.21437/Interspeech.2021-1798 | 446-450 | @inproceedings{casanova21_interspeech,
title = {{Transfer Learning and Data Augmentation Techniques to the COVID-19 Identification Tasks in ComParE 2021}},
author = {Edresson Casanova and Arnaldo {Candido Jr.} and Ricardo Corso {Fernandes Jr.} and Marcelo Finger and Lucas Rafael Stefanel Gris and Moacir Anto... | In this work, we propose several techniques to address data scarceness
in ComParE 2021 COVID-19 identification tasks for the application of
deep models such as Convolutional Neural Networks. Data is initially
preprocessed into spectrogram or MFCC-gram formats. After preprocessing,
we combine three different data augmen... | null | null |
illium21_interspeech | Visual Transformers for Primates Classification and Covid Detection | [
"Steffen Illium",
"Robert Müller",
"Andreas Sedlmeier",
"Claudia-Linnhoff Popien"
] | https://www.isca-archive.org/interspeech_2021/illium21_interspeech.html | https://www.isca-archive.org/interspeech_2021/illium21_interspeech.pdf | 10.21437/Interspeech.2021-273 | 451-455 | @inproceedings{illium21_interspeech,
title = {{Visual Transformers for Primates Classification and Covid Detection}},
author = {Steffen Illium and Robert Müller and Andreas Sedlmeier and Claudia-Linnhoff Popien},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {451--455},
doi ... | We apply the vision transformer, a deep machine learning model build
around the attention mechanism, on mel-spectrogram representations
of raw audio recordings. When adding mel-based data augmentation techniques
and sample-weighting, we achieve comparable performance on both (PRS
and CCS challenge) tasks of ComParE21, ... | 2212.10093 | title_snapshot |
pellegrini21_interspeech | Deep-Learning-Based Central African Primate Species Classification with MixUp and SpecAugment | [
"Thomas Pellegrini"
] | https://www.isca-archive.org/interspeech_2021/pellegrini21_interspeech.html | https://www.isca-archive.org/interspeech_2021/pellegrini21_interspeech.pdf | 10.21437/Interspeech.2021-1911 | 456-460 | @inproceedings{pellegrini21_interspeech,
title = {{Deep-Learning-Based Central African Primate Species Classification with MixUp and SpecAugment}},
author = {Thomas Pellegrini},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {456--460},
doi = {10.21437/Interspeech.2021-1911},... | In this paper, we report experiments in which we aim to automatically
classify primate vocalizations according to four primate species of
interest, plus a background category with forest sound events. We compare
several standard deep neural networks architectures: standard deep
convolutional neural networks (CNNs), Mob... | null | null |
muller21_interspeech | A Deep and Recurrent Architecture for Primate Vocalization Classification | [
"Robert Müller",
"Steffen Illium",
"Claudia Linnhoff-Popien"
] | https://www.isca-archive.org/interspeech_2021/muller21_interspeech.html | https://www.isca-archive.org/interspeech_2021/muller21_interspeech.pdf | 10.21437/Interspeech.2021-1274 | 461-465 | @inproceedings{muller21_interspeech,
title = {{A Deep and Recurrent Architecture for Primate Vocalization Classification}},
author = {Robert Müller and Steffen Illium and Claudia Linnhoff-Popien},
year = {2021},
booktitle = {{Interspeech 2021}},
pages = {461--465},
doi = {10.21437/Inte... | Wildlife monitoring is an essential part of most conservation efforts
where one of the many building blocks is acoustic monitoring. Acoustic
monitoring has the advantage of being non-invasive and applicable in
areas of high vegetation. In this work, we present a deep and recurrent
architecture for the classification of... | null | null |
zwerts21_interspeech | Introducing a Central African Primate Vocalisation Dataset for Automated Species Classification | [
"Joeri A. Zwerts",
"Jelle Treep",
"Casper S. Kaandorp",
"Floor Meewis",
"Amparo C. Koot",
"Heysem Kaya"
] | https://www.isca-archive.org/interspeech_2021/zwerts21_interspeech.html | https://www.isca-archive.org/interspeech_2021/zwerts21_interspeech.pdf | 10.21437/Interspeech.2021-154 | 466-470 | @inproceedings{zwerts21_interspeech,
title = {{Introducing a Central African Primate Vocalisation Dataset for Automated Species Classification}},
author = {Joeri A. Zwerts and Jelle Treep and Casper S. Kaandorp and Floor Meewis and Amparo C. Koot and Heysem Kaya},
year = {2021},
booktitle = {{Inters... | Automated classification of animal vocalisations is a potentially powerful
wildlife monitoring tool. Training robust classifiers requires sizable
annotated datasets, which are not easily recorded in the wild. To circumvent
this problem, we recorded four primate species under semi-natural conditions
in a wildlife sanctu... | 2101.10390 | title_snapshot |
rizos21_interspeech | Multi-Attentive Detection of the Spider Monkey Whinny in the (Actual) Wild | [
"Georgios Rizos",
"Jenna Lawson",
"Zhuoda Han",
"Duncan Butler",
"James Rosindell",
"Krystian Mikolajczyk",
"Cristina Banks-Leite",
"Björn W. Schuller"
] | https://www.isca-archive.org/interspeech_2021/rizos21_interspeech.html | https://www.isca-archive.org/interspeech_2021/rizos21_interspeech.pdf | 10.21437/Interspeech.2021-1969 | 471-475 | @inproceedings{rizos21_interspeech,
title = {{Multi-Attentive Detection of the Spider Monkey Whinny in the (Actual) Wild}},
author = {Georgios Rizos and Jenna Lawson and Zhuoda Han and Duncan Butler and James Rosindell and Krystian Mikolajczyk and Cristina Banks-Leite and Björn W. Schuller},
year = {2... | We study deep bioacoustic event detection through multi-head attention
based pooling, exemplified by wildlife monitoring. In the multiple
instance learning framework, a core deep neural network learns a projection
of the input acoustic signal into a sequence of embeddings, each representing
a segment of the input. Sequ... | null | null |
egaslopez21_interspeech | Identifying Conflict Escalation and Primates by Using Ensemble X-Vectors and Fisher Vector Features | [
"José Vicente Egas-López",
"Mercedes Vetráb",
"László Tóth",
"Gábor Gosztolya"
] | https://www.isca-archive.org/interspeech_2021/egaslopez21_interspeech.html | https://www.isca-archive.org/interspeech_2021/egaslopez21_interspeech.pdf | 10.21437/Interspeech.2021-1173 | 476-480 | @inproceedings{egaslopez21_interspeech,
title = {{Identifying Conflict Escalation and Primates by Using Ensemble X-Vectors and Fisher Vector Features}},
author = {José Vicente Egas-López and Mercedes Vetráb and László Tóth and Gábor Gosztolya},
year = {2021},
booktitle = {{Interspeech 2021}},
page... | Computational paralinguistics is concerned with the automatic identification
of non-verbal information in human speech. The Interspeech ComParE
challenge features new paralinguistic tasks each year; this time, among
others, a cross-corpus conflict escalation task and the identification
of primates based solely on audio... | null | null |
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