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 29 | title stringlengths 22 171 | authors listlengths 1 15 | isca_url stringlengths 66 80 | pdf_url stringlengths 65 79 | doi stringlengths 28 30 | pages stringlengths 3 9 | bibtex large_stringlengths 292 614 | abstract large_stringlengths 487 1.62k | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
values |
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li20_interspeech | On the Comparison of Popular End-to-End Models for Large Scale Speech Recognition | [
"Jinyu Li",
"Yu Wu",
"Yashesh Gaur",
"Chengyi Wang",
"Rui Zhao",
"Shujie Liu"
] | https://www.isca-archive.org/interspeech_2020/li20_interspeech.html | https://www.isca-archive.org/interspeech_2020/li20_interspeech.pdf | 10.21437/Interspeech.2020-2846 | 1-5 | @inproceedings{li20_interspeech,
title = {{On the Comparison of Popular End-to-End Models for Large Scale Speech Recognition}},
author = {Jinyu Li and Yu Wu and Yashesh Gaur and Chengyi Wang and Rui Zhao and Shujie Liu},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {1--5},
doi ... | Recently, there has been a strong push to transition from hybrid models
to end-to-end (E2E) models for automatic speech recognition. Currently,
there are three promising E2E methods: recurrent neural network transducer
(RNN-T), RNN attention-based encoder-decoder (AED), and Transformer-AED.
In this study, we conduct an... | 2005.14327 | title_snapshot |
gao20_interspeech | SAN-M: Memory Equipped Self-Attention for End-to-End Speech Recognition | [
"Zhifu Gao",
"Shiliang Zhang",
"Ming Lei",
"Ian McLoughlin"
] | https://www.isca-archive.org/interspeech_2020/gao20_interspeech.html | https://www.isca-archive.org/interspeech_2020/gao20_interspeech.pdf | 10.21437/Interspeech.2020-2471 | 6-10 | @inproceedings{gao20_interspeech,
title = {{SAN-M: Memory Equipped Self-Attention for End-to-End Speech Recognition}},
author = {Zhifu Gao and Shiliang Zhang and Ming Lei and Ian McLoughlin},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {6--10},
doi = {10.21437/Interspeech.... | End-to-end speech recognition has become popular in recent years, since
it can integrate the acoustic, pronunciation and language models into
a single neural network. Among end-to-end approaches, attention-based
methods have emerged as being superior. For example, Transformer,
which adopts an encoder-decoder architect... | 2006.01713 | title_snapshot |
jain20_interspeech | Contextual RNN-T for Open Domain ASR | [
"Mahaveer Jain",
"Gil Keren",
"Jay Mahadeokar",
"Geoffrey Zweig",
"Florian Metze",
"Yatharth Saraf"
] | https://www.isca-archive.org/interspeech_2020/jain20_interspeech.html | https://www.isca-archive.org/interspeech_2020/jain20_interspeech.pdf | 10.21437/Interspeech.2020-2986 | 11-15 | @inproceedings{jain20_interspeech,
title = {{Contextual RNN-T for Open Domain ASR}},
author = {Mahaveer Jain and Gil Keren and Jay Mahadeokar and Geoffrey Zweig and Florian Metze and Yatharth Saraf},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {11--15},
doi = {10.21437/Int... | End-to-end (E2E) systems for automatic speech recognition (ASR), such
as RNN Transducer (RNN-T) and Listen-Attend-Spell (LAS) blend the individual
components of a traditional hybrid ASR system — acoustic model,
language model, pronunciation model — into a single neural network.
While this has some nice advantages, it l... | 2006.03411 | title_snapshot |
pan20_interspeech | ASAPP-ASR: Multistream CNN and Self-Attentive SRU for SOTA Speech Recognition | [
"Jing Pan",
"Joshua Shapiro",
"Jeremy Wohlwend",
"Kyu J. Han",
"Tao Lei",
"Tao Ma"
] | https://www.isca-archive.org/interspeech_2020/pan20_interspeech.html | https://www.isca-archive.org/interspeech_2020/pan20_interspeech.pdf | 10.21437/Interspeech.2020-2947 | 16-20 | @inproceedings{pan20_interspeech,
title = {{ASAPP-ASR: Multistream CNN and Self-Attentive SRU for SOTA Speech Recognition}},
author = {Jing Pan and Joshua Shapiro and Jeremy Wohlwend and Kyu J. Han and Tao Lei and Tao Ma},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {16--20},
do... | In this paper we present state-of-the-art (SOTA) performance on the
LibriSpeech corpus with two novel neural network architectures, a
multistream CNN for acoustic modeling and a self-attentive simple
recurrent unit (SRU) for language modeling. In the hybrid ASR framework,
the multistream CNN acoustic model processes ... | 2005.10469 | title_snapshot |
kadetotad20_interspeech | Compressing LSTM Networks with Hierarchical Coarse-Grain Sparsity | [
"Deepak Kadetotad",
"Jian Meng",
"Visar Berisha",
"Chaitali Chakrabarti",
"Jae-sun Seo"
] | https://www.isca-archive.org/interspeech_2020/kadetotad20_interspeech.html | https://www.isca-archive.org/interspeech_2020/kadetotad20_interspeech.pdf | 10.21437/Interspeech.2020-1270 | 21-25 | @inproceedings{kadetotad20_interspeech,
title = {{Compressing LSTM Networks with Hierarchical Coarse-Grain Sparsity}},
author = {Deepak Kadetotad and Jian Meng and Visar Berisha and Chaitali Chakrabarti and Jae-sun Seo},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {21--25},
doi ... | The long short-term memory (LSTM) network is one of the most widely
used recurrent neural networks (RNNs) for automatic speech recognition
(ASR), but is parametrized by millions of parameters. This makes it
prohibitive for memory-constrained hardware accelerators as the storage
demand causes higher dependence on off-ch... | null | null |
lohrenz20_interspeech | BLSTM-Driven Stream Fusion for Automatic Speech Recognition: Novel Methods and a Multi-Size Window Fusion Example | [
"Timo Lohrenz",
"Tim Fingscheidt"
] | https://www.isca-archive.org/interspeech_2020/lohrenz20_interspeech.html | https://www.isca-archive.org/interspeech_2020/lohrenz20_interspeech.pdf | 10.21437/Interspeech.2020-2560 | 26-30 | @inproceedings{lohrenz20_interspeech,
title = {{BLSTM-Driven Stream Fusion for Automatic Speech Recognition: Novel Methods and a Multi-Size Window Fusion Example}},
author = {Timo Lohrenz and Tim Fingscheidt},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {26--30},
doi = {10... | Optimal fusion of streams for ASR is a nontrivial problem. Recently,
so-called posterior-in-posterior-out (PIPO-)BLSTMs have been proposed
that serve as state sequence enhancers and have highly attractive training
properties. In this work, we adopt the PIPO-BLSTMs and employ them
in the context of stream fusion for ASR... | null | null |
pham20_interspeech | Relative Positional Encoding for Speech Recognition and Direct Translation | [
"Ngoc-Quan Pham",
"Thanh-Le Ha",
"Tuan-Nam Nguyen",
"Thai-Son Nguyen",
"Elizabeth Salesky",
"Sebastian Stüker",
"Jan Niehues",
"Alex Waibel"
] | https://www.isca-archive.org/interspeech_2020/pham20_interspeech.html | https://www.isca-archive.org/interspeech_2020/pham20_interspeech.pdf | 10.21437/Interspeech.2020-2526 | 31-35 | @inproceedings{pham20_interspeech,
title = {{Relative Positional Encoding for Speech Recognition and Direct Translation}},
author = {Ngoc-Quan Pham and Thanh-Le Ha and Tuan-Nam Nguyen and Thai-Son Nguyen and Elizabeth Salesky and Sebastian Stüker and Jan Niehues and Alex Waibel},
year = {2020},
boo... | Transformer models are powerful sequence-to-sequence architectures
that are capable of directly mapping speech inputs to transcriptions
or translations. However, the mechanism for modeling positions in this
model was tailored for text modeling, and thus is less ideal for acoustic
inputs. In this work, we adapt the rela... | 2005.09940 | title_snapshot |
kanda20_interspeech | Joint Speaker Counting, Speech Recognition, and Speaker Identification for Overlapped Speech of any Number of Speakers | [
"Naoyuki Kanda",
"Yashesh Gaur",
"Xiaofei Wang",
"Zhong Meng",
"Zhuo Chen",
"Tianyan Zhou",
"Takuya Yoshioka"
] | https://www.isca-archive.org/interspeech_2020/kanda20_interspeech.html | https://www.isca-archive.org/interspeech_2020/kanda20_interspeech.pdf | 10.21437/Interspeech.2020-1085 | 36-40 | @inproceedings{kanda20_interspeech,
title = {{Joint Speaker Counting, Speech Recognition, and Speaker Identification for Overlapped Speech of any Number of Speakers}},
author = {Naoyuki Kanda and Yashesh Gaur and Xiaofei Wang and Zhong Meng and Zhuo Chen and Tianyan Zhou and Takuya Yoshioka},
year = {... | We propose an end-to-end speaker-attributed automatic speech recognition
model that unifies speaker counting, speech recognition, and speaker
identification on monaural overlapped speech. Our model is built on
serialized output training (SOT) with attention-based encoder-decoder,
a recently proposed method for recogniz... | 2006.10930 | title_snapshot |
fukuda20_interspeech | Implicit Transfer of Privileged Acoustic Information in a Generalized Knowledge Distillation Framework | [
"Takashi Fukuda",
"Samuel Thomas"
] | https://www.isca-archive.org/interspeech_2020/fukuda20_interspeech.html | https://www.isca-archive.org/interspeech_2020/fukuda20_interspeech.pdf | 10.21437/Interspeech.2020-1575 | 41-45 | @inproceedings{fukuda20_interspeech,
title = {{Implicit Transfer of Privileged Acoustic Information in a Generalized Knowledge Distillation Framework}},
author = {Takashi Fukuda and Samuel Thomas},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {41--45},
doi = {10.21437/Inter... | This paper proposes a novel generalized knowledge distillation framework,
with an implicit transfer of privileged information. In our proposed
framework, teacher networks are trained with two input branches on
pairs of time-synchronous lossless and lossy acoustic features. While
one branch of the teacher network proces... | null | null |
park20_interspeech | Effect of Adding Positional Information on Convolutional Neural Networks for End-to-End Speech Recognition | [
"Jinhwan Park",
"Wonyong Sung"
] | https://www.isca-archive.org/interspeech_2020/park20_interspeech.html | https://www.isca-archive.org/interspeech_2020/park20_interspeech.pdf | 10.21437/Interspeech.2020-3163 | 46-50 | @inproceedings{park20_interspeech,
title = {{Effect of Adding Positional Information on Convolutional Neural Networks for End-to-End Speech Recognition}},
author = {Jinhwan Park and Wonyong Sung},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {46--50},
doi = {10.21437/Inters... | Attention-based models with convolutional encoders enable faster training
and inference than recurrent neural network-based ones. However, convolutional
models often require a very large receptive field to achieve high recognition
accuracy, which not only increases the parameter size but also the
computational cost and... | null | null |
li20b_interspeech | Deep Neural Network-Based Generalized Sidelobe Canceller for Robust Multi-Channel Speech Recognition | [
"Guanjun Li",
"Shan Liang",
"Shuai Nie",
"Wenju Liu",
"Zhanlei Yang",
"Longshuai Xiao"
] | https://www.isca-archive.org/interspeech_2020/li20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/li20b_interspeech.pdf | 10.21437/Interspeech.2020-1101 | 51-55 | @inproceedings{li20b_interspeech,
title = {{Deep Neural Network-Based Generalized Sidelobe Canceller for Robust Multi-Channel Speech Recognition}},
author = {Guanjun Li and Shan Liang and Shuai Nie and Wenju Liu and Zhanlei Yang and Longshuai Xiao},
year = {2020},
booktitle = {{Interspeech 2020}},
... | The elastic spatial filter (ESF) proposed in recent years is a popular
multi-channel speech enhancement front end based on deep neural network
(DNN). It is suitable for real-time processing and has shown promising
automatic speech recognition (ASR) results. However, the ESF only utilizes
the knowledge of fixed beamform... | null | null |
xu20_interspeech | Neural Spatio-Temporal Beamformer for Target Speech Separation | [
"Yong Xu",
"Meng Yu",
"Shi-Xiong Zhang",
"Lianwu Chen",
"Chao Weng",
"Jianming Liu",
"Dong Yu"
] | https://www.isca-archive.org/interspeech_2020/xu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/xu20_interspeech.pdf | 10.21437/Interspeech.2020-1458 | 56-60 | @inproceedings{xu20_interspeech,
title = {{Neural Spatio-Temporal Beamformer for Target Speech Separation}},
author = {Yong Xu and Meng Yu and Shi-Xiong Zhang and Lianwu Chen and Chao Weng and Jianming Liu and Dong Yu},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {56--60},
doi ... | Purely neural network (NN) based speech separation and enhancement
methods, although can achieve good objective scores, inevitably cause
nonlinear speech distortions that are harmful for the automatic speech
recognition (ASR). On the other hand, the minimum variance distortionless
response (MVDR) beamformer with NN-pre... | 2005.03889 | title_snapshot |
li20c_interspeech | Online Directional Speech Enhancement Using Geometrically Constrained Independent Vector Analysis | [
"Li Li",
"Kazuhito Koishida",
"Shoji Makino"
] | https://www.isca-archive.org/interspeech_2020/li20c_interspeech.html | https://www.isca-archive.org/interspeech_2020/li20c_interspeech.pdf | 10.21437/Interspeech.2020-1484 | 61-65 | @inproceedings{li20c_interspeech,
title = {{Online Directional Speech Enhancement Using Geometrically Constrained Independent Vector Analysis}},
author = {Li Li and Kazuhito Koishida and Shoji Makino},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {61--65},
doi = {10.21437/I... | This paper proposes an online dual-microphone system for directional
speech enhancement, which employs geometrically constrained independent
vector analysis (IVA) based on the auxiliary function approach and
vectorwise coordinate descent. Its offline version has recently been
proposed and shown to outperform the conven... | null | null |
yu20_interspeech | End-to-End Multi-Look Keyword Spotting | [
"Meng Yu",
"Xuan Ji",
"Bo Wu",
"Dan Su",
"Dong Yu"
] | https://www.isca-archive.org/interspeech_2020/yu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/yu20_interspeech.pdf | 10.21437/Interspeech.2020-1521 | 66-70 | @inproceedings{yu20_interspeech,
title = {{End-to-End Multi-Look Keyword Spotting}},
author = {Meng Yu and Xuan Ji and Bo Wu and Dan Su and Dong Yu},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {66--70},
doi = {10.21437/Interspeech.2020-1521},
issn = {2958-1796},
} | The performance of keyword spotting (KWS), measured in false alarms
and false rejects, degrades significantly under the far field and noisy
conditions. In this paper, we propose a multi-look neural network modeling
for speech enhancement which simultaneously steers to listen to multiple
sampled look directions. The mul... | 2005.10386 | title_snapshot |
huang20_interspeech | Differential Beamforming for Uniform Circular Array with Directional Microphones | [
"Weilong Huang",
"Jinwei Feng"
] | https://www.isca-archive.org/interspeech_2020/huang20_interspeech.html | https://www.isca-archive.org/interspeech_2020/huang20_interspeech.pdf | 10.21437/Interspeech.2020-1571 | 71-75 | @inproceedings{huang20_interspeech,
title = {{Differential Beamforming for Uniform Circular Array with Directional Microphones}},
author = {Weilong Huang and Jinwei Feng},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {71--75},
doi = {10.21437/Interspeech.2020-1571},
issn ... | Use of omni-directional microphones is commonly assumed in the differential
beamforming with uniform circular arrays. The conventional differential
beamforming with omni-directional elements tends to suffer in low white-noise-gain
(WNG) at the low frequencies and decrease of directivity factor (DF)
at high frequencies.... | null | null |
qi20_interspeech | Exploring Deep Hybrid Tensor-to-Vector Network Architectures for Regression Based Speech Enhancement | [
"Jun Qi",
"Hu Hu",
"Yannan Wang",
"Chao-Han Huck Yang",
"Sabato Marco Siniscalchi",
"Chin-Hui Lee"
] | https://www.isca-archive.org/interspeech_2020/qi20_interspeech.html | https://www.isca-archive.org/interspeech_2020/qi20_interspeech.pdf | 10.21437/Interspeech.2020-1900 | 76-80 | @inproceedings{qi20_interspeech,
title = {{Exploring Deep Hybrid Tensor-to-Vector Network Architectures for Regression Based Speech Enhancement}},
author = {Jun Qi and Hu Hu and Yannan Wang and Chao-Han Huck Yang and Sabato Marco Siniscalchi and Chin-Hui Lee},
year = {2020},
booktitle = {{Interspeec... | This paper investigates different trade-offs between the number of
model parameters and enhanced speech qualities by employing several
deep tensor-to-vector regression models for speech enhancement. We
find that a hybrid architecture, namely CNN-TT, is capable of maintaining
a good quality performance with a reduced mo... | 2007.13024 | title_snapshot |
wu20_interspeech | An End-to-End Architecture of Online Multi-Channel Speech Separation | [
"Jian Wu",
"Zhuo Chen",
"Jinyu Li",
"Takuya Yoshioka",
"Zhili Tan",
"Edward Lin",
"Yi Luo",
"Lei Xie"
] | https://www.isca-archive.org/interspeech_2020/wu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/wu20_interspeech.pdf | 10.21437/Interspeech.2020-1981 | 81-85 | @inproceedings{wu20_interspeech,
title = {{An End-to-End Architecture of Online Multi-Channel Speech Separation}},
author = {Jian Wu and Zhuo Chen and Jinyu Li and Takuya Yoshioka and Zhili Tan and Edward Lin and Yi Luo and Lei Xie},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {81... | Multi-speaker speech recognition has been one of the key challenges
in conversation transcription as it breaks the single active speaker
assumption employed by most state-of-the-art speech recognition systems.
Speech separation is considered as a remedy to this problem. Previously,
we introduced a system, called unmix... | 2009.03141 | title_snapshot |
nakagome20_interspeech | Mentoring-Reverse Mentoring for Unsupervised Multi-Channel Speech Source Separation | [
"Yu Nakagome",
"Masahito Togami",
"Tetsuji Ogawa",
"Tetsunori Kobayashi"
] | https://www.isca-archive.org/interspeech_2020/nakagome20_interspeech.html | https://www.isca-archive.org/interspeech_2020/nakagome20_interspeech.pdf | 10.21437/Interspeech.2020-2082 | 86-90 | @inproceedings{nakagome20_interspeech,
title = {{Mentoring-Reverse Mentoring for Unsupervised Multi-Channel Speech Source Separation}},
author = {Yu Nakagome and Masahito Togami and Tetsuji Ogawa and Tetsunori Kobayashi},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {86--90},
doi... | Mentoring-reverse mentoring, which is a novel knowledge transfer framework
for unsupervised learning, is introduced in multi-channel speech source
separation. This framework aims to improve two different systems, which
are referred to as a senior and a junior system, by mentoring each
other. The senior system, which ... | null | null |
nakatani20_interspeech | Computationally Efficient and Versatile Framework for Joint Optimization of Blind Speech Separation and Dereverberation | [
"Tomohiro Nakatani",
"Rintaro Ikeshita",
"Keisuke Kinoshita",
"Hiroshi Sawada",
"Shoko Araki"
] | https://www.isca-archive.org/interspeech_2020/nakatani20_interspeech.html | https://www.isca-archive.org/interspeech_2020/nakatani20_interspeech.pdf | 10.21437/Interspeech.2020-2138 | 91-95 | @inproceedings{nakatani20_interspeech,
title = {{Computationally Efficient and Versatile Framework for Joint Optimization of Blind Speech Separation and Dereverberation}},
author = {Tomohiro Nakatani and Rintaro Ikeshita and Keisuke Kinoshita and Hiroshi Sawada and Shoko Araki},
year = {2020},
bookt... | This paper proposes new blind signal processing techniques for optimizing
a multi-input multi-output (MIMO) convolutional beamformer (CBF) in
a computationally efficient way to simultaneously perform dereverberation
and source separation. For effective CBF optimization, a conventional
technique factorizes it into a mul... | null | null |
tu20_interspeech | A Space-and-Speaker-Aware Iterative Mask Estimation Approach to Multi-Channel Speech Recognition in the CHiME-6 Challenge | [
"Yan-Hui Tu",
"Jun Du",
"Lei Sun",
"Feng Ma",
"Jia Pan",
"Chin-Hui Lee"
] | https://www.isca-archive.org/interspeech_2020/tu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/tu20_interspeech.pdf | 10.21437/Interspeech.2020-2150 | 96-100 | @inproceedings{tu20_interspeech,
title = {{A Space-and-Speaker-Aware Iterative Mask Estimation Approach to Multi-Channel Speech Recognition in the CHiME-6 Challenge}},
author = {Yan-Hui Tu and Jun Du and Lei Sun and Feng Ma and Jia Pan and Chin-Hui Lee},
year = {2020},
booktitle = {{Interspeech 2020... | We propose a space-and-speaker-aware iterative mask estimation (SSA-IME)
approach to improving complex angular central Gaussian distributions
(cACGMM) based beamforming in an iterative manner by leveraging upon
the complementary information obtained from SSA-based regression. First,
a mask calculated by beamformed spee... | null | null |
youssef20_interspeech | Identifying Causal Relationships Between Behavior and Local Brain Activity During Natural Conversation | [
"Hmamouche Youssef",
"Prévot Laurent",
"Ochs Magalie",
"Chaminade Thierry"
] | https://www.isca-archive.org/interspeech_2020/youssef20_interspeech.html | https://www.isca-archive.org/interspeech_2020/youssef20_interspeech.pdf | 10.21437/Interspeech.2020-2074 | 101-105 | @inproceedings{youssef20_interspeech,
title = {{Identifying Causal Relationships Between Behavior and Local Brain Activity During Natural Conversation}},
author = {Hmamouche Youssef and Prévot Laurent and Ochs Magalie and Chaminade Thierry},
year = {2020},
booktitle = {{Interspeech 2020}},
pages ... | Characterizing precisely neurophysiological activity involved in natural
conversations remains a major challenge. We explore in this paper the
relationship between multimodal conversational behavior and brain activity
during natural conversations. This is challenging due to Functional
Magnetic Resonance Imaging (fMRI) ... | null | null |
zhou20_interspeech | Neural Entrainment to Natural Speech Envelope Based on Subject Aligned EEG Signals | [
"Di Zhou",
"Gaoyan Zhang",
"Jianwu Dang",
"Shuang Wu",
"Zhuo Zhang"
] | https://www.isca-archive.org/interspeech_2020/zhou20_interspeech.html | https://www.isca-archive.org/interspeech_2020/zhou20_interspeech.pdf | 10.21437/Interspeech.2020-1558 | 106-110 | @inproceedings{zhou20_interspeech,
title = {{Neural Entrainment to Natural Speech Envelope Based on Subject Aligned EEG Signals}},
author = {Di Zhou and Gaoyan Zhang and Jianwu Dang and Shuang Wu and Zhuo Zhang},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {106--110},
doi ... | Reconstruction of speech envelope from neural signal is a general way
to study neural entrainment, which helps to understand the neural mechanism
underlying speech processing. Previous neural entrainment studies were
mainly based on single-trial neural activities, and the reconstruction
accuracy of speech envelope is n... | null | null |
lian20_interspeech | Does Lexical Retrieval Deteriorate in Patients with Mild Cognitive Impairment? Analysis of Brain Functional Network Will Tell | [
"Chongyuan Lian",
"Tianqi Wang",
"Mingxiao Gu",
"Manwa L. Ng",
"Feiqi Zhu",
"Lan Wang",
"Nan Yan"
] | https://www.isca-archive.org/interspeech_2020/lian20_interspeech.html | https://www.isca-archive.org/interspeech_2020/lian20_interspeech.pdf | 10.21437/Interspeech.2020-2490 | 111-115 | @inproceedings{lian20_interspeech,
title = {{Does Lexical Retrieval Deteriorate in Patients with Mild Cognitive Impairment? Analysis of Brain Functional Network Will Tell}},
author = {Chongyuan Lian and Tianqi Wang and Mingxiao Gu and Manwa L. Ng and Feiqi Zhu and Lan Wang and Nan Yan},
year = {2020},... | Alterations in speech and language are typical signs of mild cognitive
impairment (MCI), considered to be the prodromal stage of Alzheimer’s
disease (AD). Yet, very few studies have pointed out at what stage
their speech production is disrupted. To bridge this knowledge gap,
the present study focused on lexical retriev... | null | null |
fu20_interspeech | Congruent Audiovisual Speech Enhances Cortical Envelope Tracking During Auditory Selective Attention | [
"Zhen Fu",
"Jing Chen"
] | https://www.isca-archive.org/interspeech_2020/fu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/fu20_interspeech.pdf | 10.21437/Interspeech.2020-1957 | 116-120 | @inproceedings{fu20_interspeech,
title = {{Congruent Audiovisual Speech Enhances Cortical Envelope Tracking During Auditory Selective Attention}},
author = {Zhen Fu and Jing Chen},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {116--120},
doi = {10.21437/Interspeech.2020-195... | Listeners usually have the ability to selectively attend to the target
speech while ignoring competing sounds. The mechanism that top-down
attention modulates the cortical envelope tracking to speech was proposed
to account for this ability. Additional visual input, such as lipreading
was considered beneficial for spee... | null | null |
wang20_interspeech | Contribution of RMS-Level-Based Speech Segments to Target Speech Decoding Under Noisy Conditions | [
"Lei Wang",
"Ed X. Wu",
"Fei Chen"
] | https://www.isca-archive.org/interspeech_2020/wang20_interspeech.html | https://www.isca-archive.org/interspeech_2020/wang20_interspeech.pdf | 10.21437/Interspeech.2020-1652 | 121-124 | @inproceedings{wang20_interspeech,
title = {{Contribution of RMS-Level-Based Speech Segments to Target Speech Decoding Under Noisy Conditions}},
author = {Lei Wang and Ed X. Wu and Fei Chen},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {121--124},
doi = {10.21437/Interspee... | Human listeners can recognize target speech streams in complex auditory
scenes. The cortical activities can robustly track the amplitude fluctuations
of target speech with auditory attentional modulation under a range
of signal-to-masker ratios (SMRs). The root-mean-square (RMS) level
of the speech signal is a crucial ... | null | null |
zhao20_interspeech | Cortical Oscillatory Hierarchy for Natural Sentence Processing | [
"Bin Zhao",
"Jianwu Dang",
"Gaoyan Zhang",
"Masashi Unoki"
] | https://www.isca-archive.org/interspeech_2020/zhao20_interspeech.html | https://www.isca-archive.org/interspeech_2020/zhao20_interspeech.pdf | 10.21437/Interspeech.2020-1633 | 125-129 | @inproceedings{zhao20_interspeech,
title = {{Cortical Oscillatory Hierarchy for Natural Sentence Processing}},
author = {Bin Zhao and Jianwu Dang and Gaoyan Zhang and Masashi Unoki},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {125--129},
doi = {10.21437/Interspeech.2020-1... | Human speech processing, either for listening or oral reading, requires
dynamic cortical activities that are not only driven by sensory stimuli
externally but also influenced by semantic knowledge and speech planning
goals internally. Each of these functions has been known to accompany
specific rhythmic oscillations an... | null | null |
bosch20_interspeech | Comparing EEG Analyses with Different Epoch Alignments in an Auditory Lexical Decision Experiment | [
"Louis ten Bosch",
"Kimberley Mulder",
"Lou Boves"
] | https://www.isca-archive.org/interspeech_2020/bosch20_interspeech.html | https://www.isca-archive.org/interspeech_2020/bosch20_interspeech.pdf | 10.21437/Interspeech.2020-2450 | 130-134 | @inproceedings{bosch20_interspeech,
title = {{Comparing EEG Analyses with Different Epoch Alignments in an Auditory Lexical Decision Experiment}},
author = {Louis ten Bosch and Kimberley Mulder and Lou Boves},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {130--134},
doi = {... | In processing behavioral data from auditory lexical decision, reaction
times (RT) can be defined relative to stimulus onset or relative to
stimulus offset. Using stimulus onset as the reference invokes models
that assumes that relevant processing starts immediately, while stimulus
offset invokes models that assume that... | null | null |
talkar20_interspeech | Detection of Subclinical Mild Traumatic Brain Injury (mTBI) Through Speech and Gait | [
"Tanya Talkar",
"Sophia Yuditskaya",
"James R. Williamson",
"Adam C. Lammert",
"Hrishikesh Rao",
"Daniel Hannon",
"Anne OâBrien",
"Gloria Vergara-Diaz",
"Richard DeLaura",
"Douglas Sturim",
"Gregory Ciccarelli",
"Ross Zafonte",
"Jeffrey Palmer",
"Paolo Bonato",
"Thomas F. Quatieri"
] | https://www.isca-archive.org/interspeech_2020/talkar20_interspeech.html | https://www.isca-archive.org/interspeech_2020/talkar20_interspeech.pdf | 10.21437/Interspeech.2020-2651 | 135-139 | @inproceedings{talkar20_interspeech,
title = {{Detection of Subclinical Mild Traumatic Brain Injury (mTBI) Through Speech and Gait}},
author = {Tanya Talkar and Sophia Yuditskaya and James R. Williamson and Adam C. Lammert and Hrishikesh Rao and Daniel Hannon and Anne OâBrien and Gloria Vergara-Diaz and Ri... | Between 15% to 40% of mild traumatic brain injury (mTBI) patients experience
incomplete recoveries or provide subjective reports of decreased motor
abilities, despite a clinically-determined complete recovery. This
demonstrates a need for objective measures capable of detecting subclinical
residual mTBI, particularly i... | null | null |
shor20_interspeech | Towards Learning a Universal Non-Semantic Representation of Speech | [
"Joel Shor",
"Aren Jansen",
"Ronnie Maor",
"Oran Lang",
"Omry Tuval",
"Félix de Chaumont Quitry",
"Marco Tagliasacchi",
"Ira Shavitt",
"Dotan Emanuel",
"Yinnon Haviv"
] | https://www.isca-archive.org/interspeech_2020/shor20_interspeech.html | https://www.isca-archive.org/interspeech_2020/shor20_interspeech.pdf | 10.21437/Interspeech.2020-1242 | 140-144 | @inproceedings{shor20_interspeech,
title = {{Towards Learning a Universal Non-Semantic Representation of Speech}},
author = {Joel Shor and Aren Jansen and Ronnie Maor and Oran Lang and Omry Tuval and Félix de Chaumont Quitry and Marco Tagliasacchi and Ira Shavitt and Dotan Emanuel and Yinnon Haviv},
year ... | The ultimate goal of transfer learning is to reduce labeled data requirements
by exploiting a pre-existing embedding model trained for different
datasets or tasks. The visual and language communities have established
benchmarks to compare embeddings, but the speech community has yet
to do so. This paper proposes a benc... | 2002.12764 | title_snapshot |
rajan20_interspeech | Poetic Meter Classification Using i-Vector-MTF Fusion | [
"Rajeev Rajan",
"Aiswarya Vinod Kumar",
"Ben P. Babu"
] | https://www.isca-archive.org/interspeech_2020/rajan20_interspeech.html | https://www.isca-archive.org/interspeech_2020/rajan20_interspeech.pdf | 10.21437/Interspeech.2020-1794 | 145-149 | @inproceedings{rajan20_interspeech,
title = {{Poetic Meter Classification Using i-Vector-MTF Fusion}},
author = {Rajeev Rajan and Aiswarya Vinod Kumar and Ben P. Babu},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {145--149},
doi = {10.21437/Interspeech.2020-1794},
issn ... | In this paper, a deep neural network (DNN)-based poetic meter classification
scheme is proposed using a fusion of musical texture features (MTF)
and i-vectors. The experiment is performed in two phases. Initially,
the mel-frequency cepstral coefficient (MFCC) features are fused with
MTF and classification is done using... | null | null |
dai20_interspeech | Formant Tracking Using Dilated Convolutional Networks Through Dense Connection with Gating Mechanism | [
"Wang Dai",
"Jinsong Zhang",
"Yingming Gao",
"Wei Wei",
"Dengfeng Ke",
"Binghuai Lin",
"Yanlu Xie"
] | https://www.isca-archive.org/interspeech_2020/dai20_interspeech.html | https://www.isca-archive.org/interspeech_2020/dai20_interspeech.pdf | 10.21437/Interspeech.2020-1804 | 150-154 | @inproceedings{dai20_interspeech,
title = {{Formant Tracking Using Dilated Convolutional Networks Through Dense Connection with Gating Mechanism}},
author = {Wang Dai and Jinsong Zhang and Yingming Gao and Wei Wei and Dengfeng Ke and Binghuai Lin and Yanlu Xie},
year = {2020},
booktitle = {{Interspe... | Formant tracking is one of the most fundamental problems in speech
processing. Traditionally, formants are estimated using signal processing
methods. Recent studies showed that generic convolutional architectures
can outperform recurrent networks on temporal tasks such as speech
synthesis and machine translation. In th... | 2005.10803 | title_snapshot |
hu20_interspeech | Automatic Analysis of Speech Prosody in Dutch | [
"Na Hu",
"Berit Janssen",
"Judith Hanssen",
"Carlos Gussenhoven",
"Aoju Chen"
] | https://www.isca-archive.org/interspeech_2020/hu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/hu20_interspeech.pdf | 10.21437/Interspeech.2020-2142 | 155-159 | @inproceedings{hu20_interspeech,
title = {{Automatic Analysis of Speech Prosody in Dutch}},
author = {Na Hu and Berit Janssen and Judith Hanssen and Carlos Gussenhoven and Aoju Chen},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {155--159},
doi = {10.21437/Interspeech.2020-... | In this paper we present a publicly available tool for automatic analysis
of speech prosody (AASP) in Dutch. Incorporating the state-of-the-art
analytical frameworks, AASP enables users to analyze prosody at two
levels from different theoretical perspectives. Holistically, by means
of the Functional Principal Component... | null | null |
gresse20_interspeech | Learning Voice Representation Using Knowledge Distillation for Automatic Voice Casting | [
"Adrien Gresse",
"Mathias Quillot",
"Richard Dufour",
"Jean-François Bonastre"
] | https://www.isca-archive.org/interspeech_2020/gresse20_interspeech.html | https://www.isca-archive.org/interspeech_2020/gresse20_interspeech.pdf | 10.21437/Interspeech.2020-2236 | 160-164 | @inproceedings{gresse20_interspeech,
title = {{Learning Voice Representation Using Knowledge Distillation for Automatic Voice Casting}},
author = {Adrien Gresse and Mathias Quillot and Richard Dufour and Jean-François Bonastre},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {160--1... | The search for professional voice-actors for audiovisual productions
is a sensitive task, performed by the artistic directors (ADs). The
ADs have a strong appetite for new talents/voices but cannot perform
large scale auditions. Automatic tools able to suggest the most suited
voices are of a great interest for audiovis... | null | null |
yegnanarayana20_interspeech | Enhancing Formant Information in Spectrographic Display of Speech | [
"B. Yegnanarayana",
"Anand Joseph",
"Vishala Pannala"
] | https://www.isca-archive.org/interspeech_2020/yegnanarayana20_interspeech.html | https://www.isca-archive.org/interspeech_2020/yegnanarayana20_interspeech.pdf | 10.21437/Interspeech.2020-2653 | 165-169 | @inproceedings{yegnanarayana20_interspeech,
title = {{Enhancing Formant Information in Spectrographic Display of Speech}},
author = {B. Yegnanarayana and Anand Joseph and Vishala Pannala},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {165--169},
doi = {10.21437/Interspeech.... | Formants are resonances of the time varying vocal tract system, and
their characteristics are reflected in the response of the system for
a sequence of impulse-like excitation sequence originated at the glottis.
This paper presents a method to enhance the formants information in
the display of spectrogram of the speech... | null | null |
gump20_interspeech | Unsupervised Methods for Evaluating Speech Representations | [
"Michael Gump",
"Wei-Ning Hsu",
"James Glass"
] | https://www.isca-archive.org/interspeech_2020/gump20_interspeech.html | https://www.isca-archive.org/interspeech_2020/gump20_interspeech.pdf | 10.21437/Interspeech.2020-2990 | 170-174 | @inproceedings{gump20_interspeech,
title = {{Unsupervised Methods for Evaluating Speech Representations}},
author = {Michael Gump and Wei-Ning Hsu and James Glass},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {170--174},
doi = {10.21437/Interspeech.2020-2990},
issn ... | Disentanglement is a desired property in representation learning and
a significant body of research has tried to show that it is a useful
representational prior. Evaluating disentanglement is challenging,
particularly for real world data like speech, where ground truth generative
factors are typically not available. Pr... | null | null |
tran20_interspeech | Robust Pitch Regression with Voiced/Unvoiced Classification in Nonstationary Noise Environments | [
"Dung N. Tran",
"Uros Batricevic",
"Kazuhito Koishida"
] | https://www.isca-archive.org/interspeech_2020/tran20_interspeech.html | https://www.isca-archive.org/interspeech_2020/tran20_interspeech.pdf | 10.21437/Interspeech.2020-3019 | 175-179 | @inproceedings{tran20_interspeech,
title = {{Robust Pitch Regression with Voiced/Unvoiced Classification in Nonstationary Noise Environments}},
author = {Dung N. Tran and Uros Batricevic and Kazuhito Koishida},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {175--179},
doi = ... | Accurate voiced/unvoiced information is crucial in estimating the pitch
of a target speech signal in severe nonstationary noise environments.
Nevertheless, state-of-the-art pitch estimators based on deep neural
networks (DNN) lack a dedicated mechanism for robustly detecting voiced
and unvoiced segments in the target s... | null | null |
setlur20_interspeech | Nonlinear ISA with Auxiliary Variables for Learning Speech Representations | [
"Amrith Setlur",
"Barnabás Póczos",
"Alan W. Black"
] | https://www.isca-archive.org/interspeech_2020/setlur20_interspeech.html | https://www.isca-archive.org/interspeech_2020/setlur20_interspeech.pdf | 10.21437/Interspeech.2020-3050 | 180-184 | @inproceedings{setlur20_interspeech,
title = {{Nonlinear ISA with Auxiliary Variables for Learning Speech Representations}},
author = {Amrith Setlur and Barnabás Póczos and Alan W. Black},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {180--184},
doi = {10.21437/Interspeec... | This paper extends recent work on nonlinear Independent Component Analysis
( ica) by introducing a theoretical framework for nonlinear Independent
Subspace Analysis ( isa) in the presence of auxiliary variables. Observed
high dimensional acoustic features like log Mel spectrograms can be
considered as surface level man... | 2007.12948 | title_snapshot |
takeuchi20_interspeech | Harmonic Lowering for Accelerating Harmonic Convolution for Audio Signals | [
"Hirotoshi Takeuchi",
"Kunio Kashino",
"Yasunori Ohishi",
"Hiroshi Saruwatari"
] | https://www.isca-archive.org/interspeech_2020/takeuchi20_interspeech.html | https://www.isca-archive.org/interspeech_2020/takeuchi20_interspeech.pdf | 10.21437/Interspeech.2020-3185 | 185-189 | @inproceedings{takeuchi20_interspeech,
title = {{Harmonic Lowering for Accelerating Harmonic Convolution for Audio Signals}},
author = {Hirotoshi Takeuchi and Kunio Kashino and Yasunori Ohishi and Hiroshi Saruwatari},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {185--189},
doi ... | Convolutional neural networks have been successfully applied to a variety
of audio signal processing tasks including sound source separation,
speech recognition and acoustic scene understanding. Since many pitched
sounds have a harmonic structure, an operation, called harmonic convolution,
has been proposed to take adv... | null | null |
ai20_interspeech | Knowledge-and-Data-Driven Amplitude Spectrum Prediction for Hierarchical Neural Vocoders | [
"Yang Ai",
"Zhen-Hua Ling"
] | https://www.isca-archive.org/interspeech_2020/ai20_interspeech.html | https://www.isca-archive.org/interspeech_2020/ai20_interspeech.pdf | 10.21437/Interspeech.2020-1046 | 190-194 | @inproceedings{ai20_interspeech,
title = {{Knowledge-and-Data-Driven Amplitude Spectrum Prediction for Hierarchical Neural Vocoders}},
author = {Yang Ai and Zhen-Hua Ling},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {190--194},
doi = {10.21437/Interspeech.2020-1046},
is... | In our previous work, we have proposed a neural vocoder called HiNet
which recovers speech waveforms by predicting amplitude and phase spectra
hierarchically from input acoustic features. In HiNet, the amplitude
spectrum predictor (ASP) predicts log amplitude spectra (LAS) from
input acoustic features. This paper propo... | 2004.07832 | title_snapshot |
tian20_interspeech | FeatherWave: An Efficient High-Fidelity Neural Vocoder with Multi-Band Linear Prediction | [
"Qiao Tian",
"Zewang Zhang",
"Heng Lu",
"Ling-Hui Chen",
"Shan Liu"
] | https://www.isca-archive.org/interspeech_2020/tian20_interspeech.html | https://www.isca-archive.org/interspeech_2020/tian20_interspeech.pdf | 10.21437/Interspeech.2020-1156 | 195-199 | @inproceedings{tian20_interspeech,
title = {{FeatherWave: An Efficient High-Fidelity Neural Vocoder with Multi-Band Linear Prediction}},
author = {Qiao Tian and Zewang Zhang and Heng Lu and Ling-Hui Chen and Shan Liu},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {195--199},
doi ... | In this paper, we propose the FeatherWave, yet another variant of WaveRNN
vocoder combining the multi-band signal processing and the linear predictive
coding. The LPCNet, a recently proposed neural vocoder which utilized
the linear predictive characteristic of speech signal in the WaveRNN
architecture, can generate hig... | 2005.05551 | title_snapshot |
yang20_interspeech | VocGAN: A High-Fidelity Real-Time Vocoder with a Hierarchically-Nested Adversarial Network | [
"Jinhyeok Yang",
"Junmo Lee",
"Youngik Kim",
"Hoon-Young Cho",
"Injung Kim"
] | https://www.isca-archive.org/interspeech_2020/yang20_interspeech.html | https://www.isca-archive.org/interspeech_2020/yang20_interspeech.pdf | 10.21437/Interspeech.2020-1238 | 200-204 | @inproceedings{yang20_interspeech,
title = {{VocGAN: A High-Fidelity Real-Time Vocoder with a Hierarchically-Nested Adversarial Network}},
author = {Jinhyeok Yang and Junmo Lee and Youngik Kim and Hoon-Young Cho and Injung Kim},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {200--20... | We present a novel high-fidelity real-time neural vocoder called VocGAN.
A recently developed GAN-based vocoder, MelGAN, produces speech waveforms
in real-time. However, it often produces a waveform that is insufficient
in quality or inconsistent with acoustic characteristics of the input
mel spectrogram. VocGAN is nea... | 2007.15256 | title_snapshot |
kanagawa20_interspeech | Lightweight LPCNet-Based Neural Vocoder with Tensor Decomposition | [
"Hiroki Kanagawa",
"Yusuke Ijima"
] | https://www.isca-archive.org/interspeech_2020/kanagawa20_interspeech.html | https://www.isca-archive.org/interspeech_2020/kanagawa20_interspeech.pdf | 10.21437/Interspeech.2020-1642 | 205-209 | @inproceedings{kanagawa20_interspeech,
title = {{Lightweight LPCNet-Based Neural Vocoder with Tensor Decomposition}},
author = {Hiroki Kanagawa and Yusuke Ijima},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {205--209},
doi = {10.21437/Interspeech.2020-1642},
issn = ... | This paper proposes a lightweight neural vocoder based on LPCNet. The
recently proposed LPCNet exploits linear predictive coding to represent
vocal tract characteristics, and can rapidly synthesize high-quality
waveforms with fewer parameters than WaveRNN. For even greater speeds,
it is necessary to reduce the time-hea... | null | null |
hsu20_interspeech | WG-WaveNet: Real-Time High-Fidelity Speech Synthesis Without GPU | [
"Po-chun Hsu",
"Hung-yi Lee"
] | https://www.isca-archive.org/interspeech_2020/hsu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/hsu20_interspeech.pdf | 10.21437/Interspeech.2020-1736 | 210-214 | @inproceedings{hsu20_interspeech,
title = {{WG-WaveNet: Real-Time High-Fidelity Speech Synthesis Without GPU}},
author = {Po-chun Hsu and Hung-yi Lee},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {210--214},
doi = {10.21437/Interspeech.2020-1736},
issn = {2958-1796}... | In this paper, we propose WG-WaveNet, a fast, lightweight, and high-quality
waveform generation model. WG-WaveNet is composed of a compact flow-based
model and a post-filter. The two components are jointly trained by
maximizing the likelihood of the training data and optimizing loss
functions on the frequency domains. ... | 2005.07412 | title_snapshot |
stephenson20_interspeech | What the Future Brings: Investigating the Impact of Lookahead for Incremental Neural TTS | [
"Brooke Stephenson",
"Laurent Besacier",
"Laurent Girin",
"Thomas Hueber"
] | https://www.isca-archive.org/interspeech_2020/stephenson20_interspeech.html | https://www.isca-archive.org/interspeech_2020/stephenson20_interspeech.pdf | 10.21437/Interspeech.2020-2103 | 215-219 | @inproceedings{stephenson20_interspeech,
title = {{What the Future Brings: Investigating the Impact of Lookahead for Incremental Neural TTS}},
author = {Brooke Stephenson and Laurent Besacier and Laurent Girin and Thomas Hueber},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {215--2... | In incremental text to speech synthesis (iTTS), the synthesizer produces
an audio output before it has access to the entire input sentence.
In this paper, we study the behavior of a neural sequence-to-sequence
TTS system when used in an incremental mode, i.e. when generating speech
output for token n, the system has ac... | 2009.02035 | title_snapshot |
popov20_interspeech | Fast and Lightweight On-Device TTS with Tacotron2 and LPCNet | [
"Vadim Popov",
"Stanislav Kamenev",
"Mikhail Kudinov",
"Sergey Repyevsky",
"Tasnima Sadekova",
"Vitalii Bushaev",
"Vladimir Kryzhanovskiy",
"Denis Parkhomenko"
] | https://www.isca-archive.org/interspeech_2020/popov20_interspeech.html | https://www.isca-archive.org/interspeech_2020/popov20_interspeech.pdf | 10.21437/Interspeech.2020-2169 | 220-224 | @inproceedings{popov20_interspeech,
title = {{Fast and Lightweight On-Device TTS with Tacotron2 and LPCNet}},
author = {Vadim Popov and Stanislav Kamenev and Mikhail Kudinov and Sergey Repyevsky and Tasnima Sadekova and Vitalii Bushaev and Vladimir Kryzhanovskiy and Denis Parkhomenko},
year = {2020},
... | We present a fast and lightweight on-device text-to-speech system based
on state-of-art methods of feature and speech generation i.e. Tacotron2
and LPCNet. We show that modification of the basic pipeline combined
with hardware-specific optimizations and extensive usage of parallelization
enables running TTS service eve... | null | null |
song20_interspeech | Efficient WaveGlow: An Improved WaveGlow Vocoder with Enhanced Speed | [
"Wei Song",
"Guanghui Xu",
"Zhengchen Zhang",
"Chao Zhang",
"Xiaodong He",
"Bowen Zhou"
] | https://www.isca-archive.org/interspeech_2020/song20_interspeech.html | https://www.isca-archive.org/interspeech_2020/song20_interspeech.pdf | 10.21437/Interspeech.2020-2172 | 225-229 | @inproceedings{song20_interspeech,
title = {{Efficient WaveGlow: An Improved WaveGlow Vocoder with Enhanced Speed}},
author = {Wei Song and Guanghui Xu and Zhengchen Zhang and Chao Zhang and Xiaodong He and Bowen Zhou},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {225--229},
doi... | Neural vocoder, such as WaveGlow, has become an important component
in recent high-quality text-to-speech (TTS) systems. In this paper,
we propose Efficient WaveGlow (EWG), a flow-based generative model
serving as an efficient neural vocoder. Similar to WaveGlow, EWG has
a normalizing flow backbone where each flow step... | null | null |
maguer20_interspeech | Can Auditory Nerve Models Tell us What’s Different About WaveNet Vocoded Speech? | [
"Sébastien Le Maguer",
"Naomi Harte"
] | https://www.isca-archive.org/interspeech_2020/maguer20_interspeech.html | https://www.isca-archive.org/interspeech_2020/maguer20_interspeech.pdf | 10.21437/Interspeech.2020-2596 | 230-234 | @inproceedings{maguer20_interspeech,
title = {{Can Auditory Nerve Models Tell us What’s Different About WaveNet Vocoded Speech?}},
author = {Sébastien Le Maguer and Naomi Harte},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {230--234},
doi = {10.21437/Interspeech.2020-2596... | Nowadays, synthetic speech is almost indistinguishable from human speech.
The remarkable quality is mainly due to the displacing of signal processing
based vocoders in favour of neural vocoders and, in particular, the
WaveNet architecture. At the same time, speech synthesis evaluation
is still facing difficulties in ad... | null | null |
paul20_interspeech | Speaker Conditional WaveRNN: Towards Universal Neural Vocoder for Unseen Speaker and Recording Conditions | [
"Dipjyoti Paul",
"Yannis Pantazis",
"Yannis Stylianou"
] | https://www.isca-archive.org/interspeech_2020/paul20_interspeech.html | https://www.isca-archive.org/interspeech_2020/paul20_interspeech.pdf | 10.21437/Interspeech.2020-2786 | 235-239 | @inproceedings{paul20_interspeech,
title = {{Speaker Conditional WaveRNN: Towards Universal Neural Vocoder for Unseen Speaker and Recording Conditions}},
author = {Dipjyoti Paul and Yannis Pantazis and Yannis Stylianou},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {235--239},
do... | Recent advancements in deep learning led to human-level performance
in single-speaker speech synthesis. However, there are still limitations
in terms of speech quality when generalizing those systems into multiple-speaker
models especially for unseen speakers and unseen recording qualities.
For instance, conventional n... | 2008.05289 | title_snapshot |
liu20_interspeech | Neural Homomorphic Vocoder | [
"Zhijun Liu",
"Kuan Chen",
"Kai Yu"
] | https://www.isca-archive.org/interspeech_2020/liu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/liu20_interspeech.pdf | 10.21437/Interspeech.2020-3188 | 240-244 | @inproceedings{liu20_interspeech,
title = {{Neural Homomorphic Vocoder}},
author = {Zhijun Liu and Kuan Chen and Kai Yu},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {240--244},
doi = {10.21437/Interspeech.2020-3188},
issn = {2958-1796},
} | In this paper, we propose the neural homomorphic vocoder (NHV), a source-filter
model based neural vocoder framework. NHV synthesizes speech by filtering
impulse trains and noise with linear time-varying (LTV) filters. A
neural network controls the LTV filters by estimating complex cepstrums
of time-varying impulse res... | null | null |
gretter20_interspeech | Overview of the Interspeech TLT2020 Shared Task on ASR for Non-Native Children’s Speech | [
"Roberto Gretter",
"Marco Matassoni",
"Daniele Falavigna",
"Keelan Evanini",
"Chee Wee Leong"
] | https://www.isca-archive.org/interspeech_2020/gretter20_interspeech.html | https://www.isca-archive.org/interspeech_2020/gretter20_interspeech.pdf | 10.21437/Interspeech.2020-2133 | 245-249 | @inproceedings{gretter20_interspeech,
title = {{Overview of the Interspeech TLT2020 Shared Task on ASR for Non-Native Children’s Speech}},
author = {Roberto Gretter and Marco Matassoni and Daniele Falavigna and Keelan Evanini and Chee Wee Leong},
year = {2020},
booktitle = {{Interspeech 2020}},
pa... | We present an overview of the ASR challenge for non-native children’s
speech organized for a special session at Interspeech 2020. The data
for the challenge was obtained in the context of a spoken language
proficiency assessment administered at Italian schools for students
between the ages of 9 and 16 who were studying... | null | null |
lo20_interspeech | The NTNU System at the Interspeech 2020 Non-Native Children’s Speech ASR Challenge | [
"Tien-Hong Lo",
"Fu-An Chao",
"Shi-Yan Weng",
"Berlin Chen"
] | https://www.isca-archive.org/interspeech_2020/lo20_interspeech.html | https://www.isca-archive.org/interspeech_2020/lo20_interspeech.pdf | 10.21437/Interspeech.2020-1990 | 250-254 | @inproceedings{lo20_interspeech,
title = {{The NTNU System at the Interspeech 2020 Non-Native Children’s Speech ASR Challenge}},
author = {Tien-Hong Lo and Fu-An Chao and Shi-Yan Weng and Berlin Chen},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {250--254},
doi = {10.21437... | This paper describes the NTNU ASR system participating in the Interspeech
2020 Non-Native Children’s Speech ASR Challenge supported by
the SIG-CHILD group of ISCA. This ASR shared task is made much more
challenging due to the coexisting diversity of non-native and children
speaking characteristics. In the setting of cl... | 2005.08433 | title_snapshot |
knill20_interspeech | Non-Native Children’s Automatic Speech Recognition: The INTERSPEECH 2020 Shared Task ALTA Systems | [
"Kate M. Knill",
"Linlin Wang",
"Yu Wang",
"Xixin Wu",
"Mark J.F. Gales"
] | https://www.isca-archive.org/interspeech_2020/knill20_interspeech.html | https://www.isca-archive.org/interspeech_2020/knill20_interspeech.pdf | 10.21437/Interspeech.2020-2154 | 255-259 | @inproceedings{knill20_interspeech,
title = {{Non-Native Children’s Automatic Speech Recognition: The INTERSPEECH 2020 Shared Task ALTA Systems}},
author = {Kate M. Knill and Linlin Wang and Yu Wang and Xixin Wu and Mark J.F. Gales},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {25... | Automatic spoken language assessment (SLA) is a challenging problem
due to the large variations in learner speech combined with limited
resources. These issues are even more problematic when considering
children learning a language, with higher levels of acoustic and lexical
variability, and of code-switching compared ... | null | null |
kathania20_interspeech | Data Augmentation Using Prosody and False Starts to Recognize Non-Native Children’s Speech | [
"Hemant Kathania",
"Mittul Singh",
"Tamás Grósz",
"Mikko Kurimo"
] | https://www.isca-archive.org/interspeech_2020/kathania20_interspeech.html | https://www.isca-archive.org/interspeech_2020/kathania20_interspeech.pdf | 10.21437/Interspeech.2020-2199 | 260-264 | @inproceedings{kathania20_interspeech,
title = {{Data Augmentation Using Prosody and False Starts to Recognize Non-Native Children’s Speech}},
author = {Hemant Kathania and Mittul Singh and Tamás Grósz and Mikko Kurimo},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {260--264},
... | This paper describes AaltoASR’s speech recognition system for
the INTERSPEECH 2020 shared task on Automatic Speech Recognition (ASR)
for non-native children’s speech. The task is to recognize non-native
speech from children of various age groups given a limited amount of
speech. Moreover, the speech being spontaneous h... | 2008.12914 | title_snapshot |
shahin20_interspeech | UNSW System Description for the Shared Task on Automatic Speech Recognition for Non-Native Children’s Speech | [
"Mostafa Shahin",
"Renée Lu",
"Julien Epps",
"Beena Ahmed"
] | https://www.isca-archive.org/interspeech_2020/shahin20_interspeech.html | https://www.isca-archive.org/interspeech_2020/shahin20_interspeech.pdf | 10.21437/Interspeech.2020-3111 | 265-268 | @inproceedings{shahin20_interspeech,
title = {{UNSW System Description for the Shared Task on Automatic Speech Recognition for Non-Native Children’s Speech}},
author = {Mostafa Shahin and Renée Lu and Julien Epps and Beena Ahmed},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {265-... | In this paper we describe our children’s Automatic Speech Recognition
(ASR) system for the first shared task on ASR for English non-native
children’s speech. The acoustic model comprises 6 Convolutional
Neural Network (CNN) layers and 12 Factored Time-Delay Neural Network
(TDNN-F) layers, trained by data from 5 differe... | null | null |
horiguchi20_interspeech | End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors | [
"Shota Horiguchi",
"Yusuke Fujita",
"Shinji Watanabe",
"Yawen Xue",
"Kenji Nagamatsu"
] | https://www.isca-archive.org/interspeech_2020/horiguchi20_interspeech.html | https://www.isca-archive.org/interspeech_2020/horiguchi20_interspeech.pdf | 10.21437/Interspeech.2020-1022 | 269-273 | @inproceedings{horiguchi20_interspeech,
title = {{End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractors}},
author = {Shota Horiguchi and Yusuke Fujita and Shinji Watanabe and Yawen Xue and Kenji Nagamatsu},
year = {2020},
booktitle = {{Interspeech 202... | End-to-end speaker diarization for an unknown number of speakers is
addressed in this paper. Recently proposed end-to-end speaker diarization
outperformed conventional clustering-based speaker diarization, but
it has one drawback: it is less flexible in terms of the number of
speakers. This paper proposes a method for ... | 2005.09921 | title_snapshot |
medennikov20_interspeech | Target-Speaker Voice Activity Detection: A Novel Approach for Multi-Speaker Diarization in a Dinner Party Scenario | [
"Ivan Medennikov",
"Maxim Korenevsky",
"Tatiana Prisyach",
"Yuri Khokhlov",
"Mariya Korenevskaya",
"Ivan Sorokin",
"Tatiana Timofeeva",
"Anton Mitrofanov",
"Andrei Andrusenko",
"Ivan Podluzhny",
"Aleksandr Laptev",
"Aleksei Romanenko"
] | https://www.isca-archive.org/interspeech_2020/medennikov20_interspeech.html | https://www.isca-archive.org/interspeech_2020/medennikov20_interspeech.pdf | 10.21437/Interspeech.2020-1602 | 274-278 | @inproceedings{medennikov20_interspeech,
title = {{Target-Speaker Voice Activity Detection: A Novel Approach for Multi-Speaker Diarization in a Dinner Party Scenario}},
author = {Ivan Medennikov and Maxim Korenevsky and Tatiana Prisyach and Yuri Khokhlov and Mariya Korenevskaya and Ivan Sorokin and Tatiana T... | Speaker diarization for real-life scenarios is an extremely challenging
problem. Widely used clustering-based diarization approaches perform
rather poorly in such conditions, mainly due to the limited ability
to handle overlapping speech. We propose a novel Target-Speaker Voice
Activity Detection (TS-VAD) approach, whi... | 2005.07272 | title_snapshot |
aronowitz20_interspeech | New Advances in Speaker Diarization | [
"Hagai Aronowitz",
"Weizhong Zhu",
"Masayuki Suzuki",
"Gakuto Kurata",
"Ron Hoory"
] | https://www.isca-archive.org/interspeech_2020/aronowitz20_interspeech.html | https://www.isca-archive.org/interspeech_2020/aronowitz20_interspeech.pdf | 10.21437/Interspeech.2020-1879 | 279-283 | @inproceedings{aronowitz20_interspeech,
title = {{New Advances in Speaker Diarization}},
author = {Hagai Aronowitz and Weizhong Zhu and Masayuki Suzuki and Gakuto Kurata and Ron Hoory},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {279--283},
doi = {10.21437/Interspeech.202... | Recently, speaker diarization based on speaker embeddings has shown
excellent results in many works. In this paper we propose several enhancements
throughout the diarization pipeline. This work addresses two clustering
frameworks: agglomerative hierarchical clustering (AHC) and spectral
clustering (SC). First, we use m... | null | null |
lin20_interspeech | Self-Attentive Similarity Measurement Strategies in Speaker Diarization | [
"Qingjian Lin",
"Yu Hou",
"Ming Li"
] | https://www.isca-archive.org/interspeech_2020/lin20_interspeech.html | https://www.isca-archive.org/interspeech_2020/lin20_interspeech.pdf | 10.21437/Interspeech.2020-1908 | 284-288 | @inproceedings{lin20_interspeech,
title = {{Self-Attentive Similarity Measurement Strategies in Speaker Diarization}},
author = {Qingjian Lin and Yu Hou and Ming Li},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {284--288},
doi = {10.21437/Interspeech.2020-1908},
issn ... | Speaker diarization can be described as the process of extracting sequential
speaker embeddings from an audio stream and clustering them according
to speaker identities. Nowadays, deep neural network based approaches
like x-vector have been widely adopted for speaker embedding extraction.
However, in the clustering bac... | null | null |
wang20b_interspeech | Speaker Attribution with Voice Profiles by Graph-Based Semi-Supervised Learning | [
"Jixuan Wang",
"Xiong Xiao",
"Jian Wu",
"Ranjani Ramamurthy",
"Frank Rudzicz",
"Michael Brudno"
] | https://www.isca-archive.org/interspeech_2020/wang20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/wang20b_interspeech.pdf | 10.21437/Interspeech.2020-1950 | 289-293 | @inproceedings{wang20b_interspeech,
title = {{Speaker Attribution with Voice Profiles by Graph-Based Semi-Supervised Learning}},
author = {Jixuan Wang and Xiong Xiao and Jian Wu and Ranjani Ramamurthy and Frank Rudzicz and Michael Brudno},
year = {2020},
booktitle = {{Interspeech 2020}},
pages ... | Speaker attribution is required in many real-world applications, such
as meeting transcription, where speaker identity is assigned to each
utterance according to speaker voice profiles. In this paper, we propose
to solve the speaker attribution problem by using graph-based semi-supervised
learning methods. A graph of s... | 2102.03634 | title_snapshot |
singh20_interspeech | Deep Self-Supervised Hierarchical Clustering for Speaker Diarization | [
"Prachi Singh",
"Sriram Ganapathy"
] | https://www.isca-archive.org/interspeech_2020/singh20_interspeech.html | https://www.isca-archive.org/interspeech_2020/singh20_interspeech.pdf | 10.21437/Interspeech.2020-2297 | 294-298 | @inproceedings{singh20_interspeech,
title = {{Deep Self-Supervised Hierarchical Clustering for Speaker Diarization}},
author = {Prachi Singh and Sriram Ganapathy},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {294--298},
doi = {10.21437/Interspeech.2020-2297},
issn =... | The state-of-the-art speaker diarization systems use agglomerative
hierarchical clustering (AHC) which performs the clustering of previously
learned neural embeddings. While the clustering approach attempts to
identify speaker clusters, the AHC algorithm does not involve any further
learning. In this paper, we propose ... | 2008.03960 | title_snapshot |
chung20_interspeech | Spot the Conversation: Speaker Diarisation in the Wild | [
"Joon Son Chung",
"Jaesung Huh",
"Arsha Nagrani",
"Triantafyllos Afouras",
"Andrew Zisserman"
] | https://www.isca-archive.org/interspeech_2020/chung20_interspeech.html | https://www.isca-archive.org/interspeech_2020/chung20_interspeech.pdf | 10.21437/Interspeech.2020-2337 | 299-303 | @inproceedings{chung20_interspeech,
title = {{Spot the Conversation: Speaker Diarisation in the Wild}},
author = {Joon Son Chung and Jaesung Huh and Arsha Nagrani and Triantafyllos Afouras and Andrew Zisserman},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {299--303},
doi =... | The goal of this paper is speaker diarisation of videos collected ‘in
the wild’. We make three key contributions. First, we propose an automatic
audio-visual diarisation method for YouTube videos. Our method consists
of active speaker detection using audio-visual methods and speaker
verification using self-enrolled spe... | 2007.01216 | title_snapshot |
zhang20_interspeech | Learning Contextual Language Embeddings for Monaural Multi-Talker Speech Recognition | [
"Wangyou Zhang",
"Yanmin Qian"
] | https://www.isca-archive.org/interspeech_2020/zhang20_interspeech.html | https://www.isca-archive.org/interspeech_2020/zhang20_interspeech.pdf | 10.21437/Interspeech.2020-2015 | 304-308 | @inproceedings{zhang20_interspeech,
title = {{Learning Contextual Language Embeddings for Monaural Multi-Talker Speech Recognition}},
author = {Wangyou Zhang and Yanmin Qian},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {304--308},
doi = {10.21437/Interspeech.2020-2015},
... | End-to-end multi-speaker speech recognition has been a popular topic
in recent years, as more and more researches focus on speech processing
in more realistic scenarios. Inspired by the hearing mechanism of human
beings, which enables us to concentrate on the interested speaker from
the multi-speaker mixed speech by ut... | null | null |
du20_interspeech | Double Adversarial Network Based Monaural Speech Enhancement for Robust Speech Recognition | [
"Zhihao Du",
"Jiqing Han",
"Xueliang Zhang"
] | https://www.isca-archive.org/interspeech_2020/du20_interspeech.html | https://www.isca-archive.org/interspeech_2020/du20_interspeech.pdf | 10.21437/Interspeech.2020-1504 | 309-313 | @inproceedings{du20_interspeech,
title = {{Double Adversarial Network Based Monaural Speech Enhancement for Robust Speech Recognition}},
author = {Zhihao Du and Jiqing Han and Xueliang Zhang},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {309--313},
doi = {10.21437/Interspe... | To improve the noise robustness of automatic speech recognition (ASR),
the generative adversarial network (GAN) based enhancement methods
are employed as the front-end processing, which comprise a single adversarial
process of an enhancement model and a discriminator. In this single
adversarial process, the discriminat... | null | null |
bruguier20_interspeech | Anti-Aliasing Regularization in Stacking Layers | [
"Antoine Bruguier",
"Ananya Misra",
"Arun Narayanan",
"Rohit Prabhavalkar"
] | https://www.isca-archive.org/interspeech_2020/bruguier20_interspeech.html | https://www.isca-archive.org/interspeech_2020/bruguier20_interspeech.pdf | 10.21437/Interspeech.2020-1497 | 314-318 | @inproceedings{bruguier20_interspeech,
title = {{Anti-Aliasing Regularization in Stacking Layers}},
author = {Antoine Bruguier and Ananya Misra and Arun Narayanan and Rohit Prabhavalkar},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {314--318},
doi = {10.21437/Interspeech.2... | Shift-invariance is a desirable property of many machine learning models.
It means that delaying the input of a model in time should only result
in delaying its prediction in time. A model that is shift-invariant,
also eliminates undesirable side effects like frequency aliasing. When
building sequence models, not only ... | null | null |
andrusenko20_interspeech | Towards a Competitive End-to-End Speech Recognition for CHiME-6 Dinner Party Transcription | [
"Andrei Andrusenko",
"Aleksandr Laptev",
"Ivan Medennikov"
] | https://www.isca-archive.org/interspeech_2020/andrusenko20_interspeech.html | https://www.isca-archive.org/interspeech_2020/andrusenko20_interspeech.pdf | 10.21437/Interspeech.2020-1074 | 319-323 | @inproceedings{andrusenko20_interspeech,
title = {{Towards a Competitive End-to-End Speech Recognition for CHiME-6 Dinner Party Transcription}},
author = {Andrei Andrusenko and Aleksandr Laptev and Ivan Medennikov},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {319--323},
doi ... | While end-to-end ASR systems have proven competitive with the conventional
hybrid approach, they are prone to accuracy degradation when it comes
to noisy and low-resource conditions. In this paper, we argue that,
even in such difficult cases, some end-to-end approaches show performance
close to the hybrid baseline. To ... | 2004.10799 | title_snapshot |
zhang20b_interspeech | End-to-End Far-Field Speech Recognition with Unified Dereverberation and Beamforming | [
"Wangyou Zhang",
"Aswin Shanmugam Subramanian",
"Xuankai Chang",
"Shinji Watanabe",
"Yanmin Qian"
] | https://www.isca-archive.org/interspeech_2020/zhang20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/zhang20b_interspeech.pdf | 10.21437/Interspeech.2020-2432 | 324-328 | @inproceedings{zhang20b_interspeech,
title = {{End-to-End Far-Field Speech Recognition with Unified Dereverberation and Beamforming}},
author = {Wangyou Zhang and Aswin Shanmugam Subramanian and Xuankai Chang and Shinji Watanabe and Yanmin Qian},
year = {2020},
booktitle = {{Interspeech 2020}},
pa... | Despite successful applications of end-to-end approaches in multi-channel
speech recognition, the performance still degrades severely when the
speech is corrupted by reverberation. In this paper, we integrate the
dereverberation module into the end-to-end multi-channel speech recognition
system and explore two differen... | 2005.10479 | title_snapshot |
qiu20_interspeech | Quaternion Neural Networks for Multi-Channel Distant Speech Recognition | [
"Xinchi Qiu",
"Titouan Parcollet",
"Mirco Ravanelli",
"Nicholas D. Lane",
"Mohamed Morchid"
] | https://www.isca-archive.org/interspeech_2020/qiu20_interspeech.html | https://www.isca-archive.org/interspeech_2020/qiu20_interspeech.pdf | 10.21437/Interspeech.2020-1682 | 329-333 | @inproceedings{qiu20_interspeech,
title = {{Quaternion Neural Networks for Multi-Channel Distant Speech Recognition}},
author = {Xinchi Qiu and Titouan Parcollet and Mirco Ravanelli and Nicholas D. Lane and Mohamed Morchid},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {329--333},
... | Despite the significant progress in automatic speech recognition (ASR),
distant ASR remains challenging due to noise and reverberation. A common
approach to mitigate this issue consists of equipping the recording
devices with multiple microphones that capture the acoustic scene from
different perspectives. These multi-... | 2005.08566 | title_snapshot |
chen20_interspeech | Improved Guided Source Separation Integrated with a Strong Back-End for the CHiME-6 Dinner Party Scenario | [
"Hangting Chen",
"Pengyuan Zhang",
"Qian Shi",
"Zuozhen Liu"
] | https://www.isca-archive.org/interspeech_2020/chen20_interspeech.html | https://www.isca-archive.org/interspeech_2020/chen20_interspeech.pdf | 10.21437/Interspeech.2020-1606 | 334-338 | @inproceedings{chen20_interspeech,
title = {{Improved Guided Source Separation Integrated with a Strong Back-End for the CHiME-6 Dinner Party Scenario}},
author = {Hangting Chen and Pengyuan Zhang and Qian Shi and Zuozhen Liu},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {334--338... | The CHiME-6 dataset presents a difficult task with extreme speech overlap,
severe noise and a natural speaking style. The gap of the word error
rate (WER) is distinct between the audios recorded by the distant microphone
arrays and the individual headset microphones. The official baseline
exhibits a WER gap of approxim... | null | null |
wang20c_interspeech | Neural Speech Separation Using Spatially Distributed Microphones | [
"Dongmei Wang",
"Zhuo Chen",
"Takuya Yoshioka"
] | https://www.isca-archive.org/interspeech_2020/wang20c_interspeech.html | https://www.isca-archive.org/interspeech_2020/wang20c_interspeech.pdf | 10.21437/Interspeech.2020-1089 | 339-343 | @inproceedings{wang20c_interspeech,
title = {{Neural Speech Separation Using Spatially Distributed Microphones}},
author = {Dongmei Wang and Zhuo Chen and Takuya Yoshioka},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {339--343},
doi = {10.21437/Interspeech.2020-1089},
is... | This paper proposes a neural network based speech separation method
using spatially distributed microphones. Unlike with traditional microphone
array settings, neither the number of microphones nor their spatial
arrangement is known in advance, which hinders the use of conventional
multi-channel speech separation neura... | 2004.13670 | title_snapshot |
horiguchi20b_interspeech | Utterance-Wise Meeting Transcription System Using Asynchronous Distributed Microphones | [
"Shota Horiguchi",
"Yusuke Fujita",
"Kenji Nagamatsu"
] | https://www.isca-archive.org/interspeech_2020/horiguchi20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/horiguchi20b_interspeech.pdf | 10.21437/Interspeech.2020-1050 | 344-348 | @inproceedings{horiguchi20b_interspeech,
title = {{Utterance-Wise Meeting Transcription System Using Asynchronous Distributed Microphones}},
author = {Shota Horiguchi and Yusuke Fujita and Kenji Nagamatsu},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {344--348},
doi = {10.... | A novel framework for meeting transcription using asynchronous microphones
is proposed in this paper. It consists of audio synchronization, speaker
diarization, utterance-wise speech enhancement using guided source
separation, automatic speech recognition, and duplication reduction.
Doing speaker diarization before spe... | 2007.15868 | title_snapshot |
deadman20_interspeech | Simulating Realistically-Spatialised Simultaneous Speech Using Video-Driven Speaker Detection and the CHiME-5 Dataset | [
"Jack Deadman",
"Jon Barker"
] | https://www.isca-archive.org/interspeech_2020/deadman20_interspeech.html | https://www.isca-archive.org/interspeech_2020/deadman20_interspeech.pdf | 10.21437/Interspeech.2020-2807 | 349-353 | @inproceedings{deadman20_interspeech,
title = {{Simulating Realistically-Spatialised Simultaneous Speech Using Video-Driven Speaker Detection and the CHiME-5 Dataset}},
author = {Jack Deadman and Jon Barker},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {349--353},
doi = {1... | Simulated data plays a crucial role in the development and evaluation
of novel distant microphone ASR techniques. However, the commonly used
simulated datasets adopt uninformed and potentially unrealistic speaker
location distributions. We wish to generate more realistic simulations
driven by recorded human behaviour. ... | null | null |
botelho20_interspeech | Toward Silent Paralinguistics: Speech-to-EMG — Retrieving Articulatory Muscle Activity from Speech | [
"Catarina Botelho",
"Lorenz Diener",
"Dennis Küster",
"Kevin Scheck",
"Shahin Amiriparian",
"Björn W. Schuller",
"Tanja Schultz",
"Alberto Abad",
"Isabel Trancoso"
] | https://www.isca-archive.org/interspeech_2020/botelho20_interspeech.html | https://www.isca-archive.org/interspeech_2020/botelho20_interspeech.pdf | 10.21437/Interspeech.2020-2926 | 354-358 | @inproceedings{botelho20_interspeech,
title = {{Toward Silent Paralinguistics: Speech-to-EMG — Retrieving Articulatory Muscle Activity from Speech}},
author = {Catarina Botelho and Lorenz Diener and Dennis Küster and Kevin Scheck and Shahin Amiriparian and Björn W. Schuller and Tanja Schultz and Alberto Ab... | Electromyographic (EMG) signals recorded during speech production encode
information on articulatory muscle activity and also on the facial
expression of emotion, thus representing a speech-related biosignal
with strong potential for paralinguistic applications. In this work,
we estimate the electrical activity of the ... | null | null |
zhang20c_interspeech | Multimodal Deception Detection Using Automatically Extracted Acoustic, Visual, and Lexical Features | [
"Jiaxuan Zhang",
"Sarah Ita Levitan",
"Julia Hirschberg"
] | https://www.isca-archive.org/interspeech_2020/zhang20c_interspeech.html | https://www.isca-archive.org/interspeech_2020/zhang20c_interspeech.pdf | 10.21437/Interspeech.2020-2320 | 359-363 | @inproceedings{zhang20c_interspeech,
title = {{Multimodal Deception Detection Using Automatically Extracted Acoustic, Visual, and Lexical Features}},
author = {Jiaxuan Zhang and Sarah Ita Levitan and Julia Hirschberg},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {359--363},
doi ... | Deception detection in conversational dialogue has attracted much attention
in recent years. Yet existing methods for this rely heavily on human-labeled
annotations that are costly and potentially inaccurate. In this work,
we present an automated system that utilizes multimodal features for
conversational deception det... | null | null |
pan20b_interspeech | Multi-Modal Attention for Speech Emotion Recognition | [
"Zexu Pan",
"Zhaojie Luo",
"Jichen Yang",
"Haizhou Li"
] | https://www.isca-archive.org/interspeech_2020/pan20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/pan20b_interspeech.pdf | 10.21437/Interspeech.2020-1653 | 364-368 | @inproceedings{pan20b_interspeech,
title = {{Multi-Modal Attention for Speech Emotion Recognition}},
author = {Zexu Pan and Zhaojie Luo and Jichen Yang and Haizhou Li},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {364--368},
doi = {10.21437/Interspeech.2020-1653},
issn ... | Emotion represents an essential aspect of human speech that is manifested
in speech prosody. Speech, visual, and textual cues are complementary
in human communication. In this paper, we study a hybrid fusion method,
referred to as multi-modal attention network (MMAN) to makes use of
visual and textual cues in speech em... | 2009.04107 | title_snapshot |
shen20_interspeech | WISE: Word-Level Interaction-Based Multimodal Fusion for Speech Emotion Recognition | [
"Guang Shen",
"Riwei Lai",
"Rui Chen",
"Yu Zhang",
"Kejia Zhang",
"Qilong Han",
"Hongtao Song"
] | https://www.isca-archive.org/interspeech_2020/shen20_interspeech.html | https://www.isca-archive.org/interspeech_2020/shen20_interspeech.pdf | 10.21437/Interspeech.2020-3131 | 369-373 | @inproceedings{shen20_interspeech,
title = {{WISE: Word-Level Interaction-Based Multimodal Fusion for Speech Emotion Recognition}},
author = {Guang Shen and Riwei Lai and Rui Chen and Yu Zhang and Kejia Zhang and Qilong Han and Hongtao Song},
year = {2020},
booktitle = {{Interspeech 2020}},
pages ... | While having numerous real-world applications, speech emotion recognition
is still a technically challenging problem. How to effectively leverage
the inherent multiple modalities in speech data (e.g., audio and text)
is key to accurate classification. Existing studies normally choose
to fuse multimodal features at the ... | null | null |
chen20b_interspeech | A Multi-Scale Fusion Framework for Bimodal Speech Emotion Recognition | [
"Ming Chen",
"Xudong Zhao"
] | https://www.isca-archive.org/interspeech_2020/chen20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/chen20b_interspeech.pdf | 10.21437/Interspeech.2020-3156 | 374-378 | @inproceedings{chen20b_interspeech,
title = {{A Multi-Scale Fusion Framework for Bimodal Speech Emotion Recognition}},
author = {Ming Chen and Xudong Zhao},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {374--378},
doi = {10.21437/Interspeech.2020-3156},
issn = {2958-... | Speech emotion recognition (SER) is a challenging task that requires
to learn suitable features for achieving good performance. The development
of deep learning techniques makes it possible to automatically extract
features rather than construct hand-crafted features. In this paper,
a multi-scale fusion framework named... | null | null |
liu20b_interspeech | Group Gated Fusion on Attention-Based Bidirectional Alignment for Multimodal Emotion Recognition | [
"Pengfei Liu",
"Kun Li",
"Helen Meng"
] | https://www.isca-archive.org/interspeech_2020/liu20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/liu20b_interspeech.pdf | 10.21437/Interspeech.2020-2067 | 379-383 | @inproceedings{liu20b_interspeech,
title = {{Group Gated Fusion on Attention-Based Bidirectional Alignment for Multimodal Emotion Recognition}},
author = {Pengfei Liu and Kun Li and Helen Meng},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {379--383},
doi = {10.21437/Inters... | Emotion recognition is a challenging and actively-studied research
area that plays a critical role in emotion-aware human-computer interaction
systems. In a multimodal setting, temporal alignment between different
modalities has not been well investigated yet. This paper presents
a new model named as Gated Bidirectiona... | 2201.06309 | title_snapshot |
khare20_interspeech | Multi-Modal Embeddings Using Multi-Task Learning for Emotion Recognition | [
"Aparna Khare",
"Srinivas Parthasarathy",
"Shiva Sundaram"
] | https://www.isca-archive.org/interspeech_2020/khare20_interspeech.html | https://www.isca-archive.org/interspeech_2020/khare20_interspeech.pdf | 10.21437/Interspeech.2020-1827 | 384-388 | @inproceedings{khare20_interspeech,
title = {{Multi-Modal Embeddings Using Multi-Task Learning for Emotion Recognition}},
author = {Aparna Khare and Srinivas Parthasarathy and Shiva Sundaram},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {384--388},
doi = {10.21437/Interspe... | General embeddings like word2vec, GloVe and ELMo have shown a lot of
success in natural language tasks. The embeddings are typically extracted
from models that are built on general tasks such as skip-gram models
and natural language generation. In this paper, we extend the work
from natural language understanding to mu... | 2009.05019 | title_snapshot |
li20d_interspeech | Using Speaker-Aligned Graph Memory Block in Multimodally Attentive Emotion Recognition Network | [
"Jeng-Lin Li",
"Chi-Chun Lee"
] | https://www.isca-archive.org/interspeech_2020/li20d_interspeech.html | https://www.isca-archive.org/interspeech_2020/li20d_interspeech.pdf | 10.21437/Interspeech.2020-1688 | 389-393 | @inproceedings{li20d_interspeech,
title = {{Using Speaker-Aligned Graph Memory Block in Multimodally Attentive Emotion Recognition Network}},
author = {Jeng-Lin Li and Chi-Chun Lee},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {389--393},
doi = {10.21437/Interspeech.2020-1... | Integrating multimodal emotion sensing modules in realizing human-centered
technologies is rapidly growing. Despite recent advancement of deep
architectures in improving recognition performances, inability to handle
individual differences in the expressive cues creates a major hurdle
for real world applications. In thi... | null | null |
lian20b_interspeech | Context-Dependent Domain Adversarial Neural Network for Multimodal Emotion Recognition | [
"Zheng Lian",
"Jianhua Tao",
"Bin Liu",
"Jian Huang",
"Zhanlei Yang",
"Rongjun Li"
] | https://www.isca-archive.org/interspeech_2020/lian20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/lian20b_interspeech.pdf | 10.21437/Interspeech.2020-1705 | 394-398 | @inproceedings{lian20b_interspeech,
title = {{Context-Dependent Domain Adversarial Neural Network for Multimodal Emotion Recognition}},
author = {Zheng Lian and Jianhua Tao and Bin Liu and Jian Huang and Zhanlei Yang and Rongjun Li},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {39... | Emotion recognition remains a complex task due to speaker variations
and low-resource training samples. To address these difficulties, we
focus on the domain adversarial neural networks (DANN) for emotion
recognition. The primary task is to predict emotion labels. The secondary
task is to learn a common representation ... | null | null |
yang20b_interspeech | ATCSpeech: A Multilingual Pilot-Controller Speech Corpus from Real Air Traffic Control Environment | [
"Bo Yang",
"Xianlong Tan",
"Zhengmao Chen",
"Bing Wang",
"Min Ruan",
"Dan Li",
"Zhongping Yang",
"Xiping Wu",
"Yi Lin"
] | https://www.isca-archive.org/interspeech_2020/yang20b_interspeech.html | https://www.isca-archive.org/interspeech_2020/yang20b_interspeech.pdf | 10.21437/Interspeech.2020-1020 | 399-403 | @inproceedings{yang20b_interspeech,
title = {{ATCSpeech: A Multilingual Pilot-Controller Speech Corpus from Real Air Traffic Control Environment}},
author = {Bo Yang and Xianlong Tan and Zhengmao Chen and Bing Wang and Min Ruan and Dan Li and Zhongping Yang and Xiping Wu and Yi Lin},
year = {2020},
... | Automatic Speech Recognition (ASR) technique has been greatly developed
in recent years, which expedites many applications in other fields.
For the ASR research, speech corpus is always an essential foundation,
especially for the vertical industry, such as Air Traffic Control (ATC).
There are some speech corpora for co... | 1911.11365 | title_snapshot |
gutkin20_interspeech | Developing an Open-Source Corpus of Yoruba Speech | [
"Alexander Gutkin",
"IÅın DemirÅahin",
"Oddur Kjartansson",
"Clara Rivera",
"Kọ́lá Túbọ̀sún"
] | https://www.isca-archive.org/interspeech_2020/gutkin20_interspeech.html | https://www.isca-archive.org/interspeech_2020/gutkin20_interspeech.pdf | 10.21437/Interspeech.2020-1096 | 404-408 | @inproceedings{gutkin20_interspeech,
title = {{Developing an Open-Source Corpus of Yoruba Speech}},
author = {Alexander Gutkin and IÅın DemirÅahin and Oddur Kjartansson and Clara Rivera and Kọ́lá Túbọ̀sún},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {404--408},
doi ... | This paper introduces an open-source speech dataset for Yoruba —
one of the largest low-resource West African languages spoken by at
least 22 million people. Yoruba is one of the official languages of
Nigeria, Benin and Togo, and is spoken in other neighboring African
countries and beyond. The corpus consists of over f... | null | null |
ha20_interspeech | ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers | [
"Jung-Woo Ha",
"Kihyun Nam",
"Jingu Kang",
"Sang-Woo Lee",
"Sohee Yang",
"Hyunhoon Jung",
"Hyeji Kim",
"Eunmi Kim",
"Soojin Kim",
"Hyun Ah Kim",
"Kyoungtae Doh",
"Chan Kyu Lee",
"Nako Sung",
"Sunghun Kim"
] | https://www.isca-archive.org/interspeech_2020/ha20_interspeech.html | https://www.isca-archive.org/interspeech_2020/ha20_interspeech.pdf | 10.21437/Interspeech.2020-1136 | 409-413 | @inproceedings{ha20_interspeech,
title = {{ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers}},
author = {Jung-Woo Ha and Kihyun Nam and Jingu Kang and Sang-Woo Lee and Sohee Yang and Hyunhoon Jung and Hyeji Kim and Eunmi Kim and Soojin Kim and Hyun Ah K... | Automatic speech recognition (ASR) via call is essential for various
applications, including AI for contact center (AICC) services. Despite
the advancement of ASR, however, most publicly available call-based
speech corpora such as Switchboard are old-fashioned. Also, most existing
call corpora are in English and mainly... | 2004.09367 | title_snapshot |
wang20d_interspeech | LAIX Corpus of Chinese Learner English: Towards a Benchmark for L2 English ASR | [
"Yanhong Wang",
"Huan Luan",
"Jiahong Yuan",
"Bin Wang",
"Hui Lin"
] | https://www.isca-archive.org/interspeech_2020/wang20d_interspeech.html | https://www.isca-archive.org/interspeech_2020/wang20d_interspeech.pdf | 10.21437/Interspeech.2020-1677 | 414-418 | @inproceedings{wang20d_interspeech,
title = {{LAIX Corpus of Chinese Learner English: Towards a Benchmark for L2 English ASR}},
author = {Yanhong Wang and Huan Luan and Jiahong Yuan and Bin Wang and Hui Lin},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {414--418},
doi = {1... | This paper introduces a corpus of Chinese Learner English containing
82 hours of L2 English speech by Chinese learners from all major dialect
regions, collected through mobile apps developed by LAIX Inc. The LAIX
corpus was created to serve as a benchmark dataset for evaluating Automatic
Speech Recognition (ASR) perfor... | null | null |
ramanarayanan20_interspeech | Design and Development of a Human-Machine Dialog Corpus for the Automated Assessment of Conversational English Proficiency | [
"Vikram Ramanarayanan"
] | https://www.isca-archive.org/interspeech_2020/ramanarayanan20_interspeech.html | https://www.isca-archive.org/interspeech_2020/ramanarayanan20_interspeech.pdf | 10.21437/Interspeech.2020-1988 | 419-423 | @inproceedings{ramanarayanan20_interspeech,
title = {{Design and Development of a Human-Machine Dialog Corpus for the Automated Assessment of Conversational English Proficiency}},
author = {Vikram Ramanarayanan},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {419--423},
doi ... | This paper presents a carefully designed corpus of scored spoken conversations
between English language learners and a dialog system to facilitate
research and development of both human and machine scoring of dialog
interactions. We collected speech, demographic and user experience
data from non-native speakers of Engl... | null | null |
ng20_interspeech | CUCHILD: A Large-Scale Cantonese Corpus of Child Speech for Phonology and Articulation Assessment | [
"Si-Ioi Ng",
"Cymie Wing-Yee Ng",
"Jiarui Wang",
"Tan Lee",
"Kathy Yuet-Sheung Lee",
"Michael Chi-Fai Tong"
] | https://www.isca-archive.org/interspeech_2020/ng20_interspeech.html | https://www.isca-archive.org/interspeech_2020/ng20_interspeech.pdf | 10.21437/Interspeech.2020-2148 | 424-428 | @inproceedings{ng20_interspeech,
title = {{CUCHILD: A Large-Scale Cantonese Corpus of Child Speech for Phonology and Articulation Assessment}},
author = {Si-Ioi Ng and Cymie Wing-Yee Ng and Jiarui Wang and Tan Lee and Kathy Yuet-Sheung Lee and Michael Chi-Fai Tong},
year = {2020},
booktitle = {{Inte... | This paper describes the design and development of CUCHILD, a large-scale
Cantonese corpus of child speech. The corpus contains spoken words
collected from 1,986 child speakers aged from 3 to 6 years old. The
speech materials include 130 words of 1 to 4 syllables in length. The
speakers cover both typically developing ... | 2008.03188 | title_snapshot |
leino20_interspeech | FinChat: Corpus and Evaluation Setup for Finnish Chat Conversations on Everyday Topics | [
"Katri Leino",
"Juho Leinonen",
"Mittul Singh",
"Sami Virpioja",
"Mikko Kurimo"
] | https://www.isca-archive.org/interspeech_2020/leino20_interspeech.html | https://www.isca-archive.org/interspeech_2020/leino20_interspeech.pdf | 10.21437/Interspeech.2020-2511 | 429-433 | @inproceedings{leino20_interspeech,
title = {{FinChat: Corpus and Evaluation Setup for Finnish Chat Conversations on Everyday Topics}},
author = {Katri Leino and Juho Leinonen and Mittul Singh and Sami Virpioja and Mikko Kurimo},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {429--4... | Creating open-domain chatbots requires large amounts of conversational
data and related benchmark tasks to evaluate them. Standardized evaluation
tasks are crucial for creating automatic evaluation metrics for model
development; otherwise, comparing the models would require resource-expensive
human evaluation. While ch... | 2008.08315 | title_snapshot |
segbroeck20_interspeech | DiPCo — Dinner Party Corpus | [
"Maarten Van Segbroeck",
"Ahmed Zaid",
"Ksenia Kutsenko",
"Cirenia Huerta",
"Tinh Nguyen",
"Xuewen Luo",
"Björn Hoffmeister",
"Jan Trmal",
"Maurizio Omologo",
"Roland Maas"
] | https://www.isca-archive.org/interspeech_2020/segbroeck20_interspeech.html | https://www.isca-archive.org/interspeech_2020/segbroeck20_interspeech.pdf | 10.21437/Interspeech.2020-2800 | 434-436 | @inproceedings{segbroeck20_interspeech,
title = {{DiPCo — Dinner Party Corpus}},
author = {Maarten Van Segbroeck and Ahmed Zaid and Ksenia Kutsenko and Cirenia Huerta and Tinh Nguyen and Xuewen Luo and Björn Hoffmeister and Jan Trmal and Maurizio Omologo and Roland Maas},
year = {2020},
booktitle =... | We present a speech data corpus that simulates a “dinner party”
scenario taking place in an everyday home environment. The corpus was
created by recording multiple groups of four Amazon employee volunteers
having a natural conversation in English around a dining table. The
participants were recorded by a single-channel... | 1909.13447 | title_snapshot |
wang20e_interspeech | Learning to Detect Bipolar Disorder and Borderline Personality Disorder with Language and Speech in Non-Clinical Interviews | [
"Bo Wang",
"Yue Wu",
"Niall Taylor",
"Terry Lyons",
"Maria Liakata",
"Alejo J. Nevado-Holgado",
"Kate E.A. Saunders"
] | https://www.isca-archive.org/interspeech_2020/wang20e_interspeech.html | https://www.isca-archive.org/interspeech_2020/wang20e_interspeech.pdf | 10.21437/Interspeech.2020-3040 | 437-441 | @inproceedings{wang20e_interspeech,
title = {{Learning to Detect Bipolar Disorder and Borderline Personality Disorder with Language and Speech in Non-Clinical Interviews}},
author = {Bo Wang and Yue Wu and Niall Taylor and Terry Lyons and Maria Liakata and Alejo J. Nevado-Holgado and Kate E.A. Saunders},
y... | Bipolar disorder (BD) and borderline personality disorder (BPD) are
both chronic psychiatric disorders. However, their overlapping symptoms
and common comorbidity make it challenging for the clinicians to distinguish
the two conditions on the basis of a clinical interview. In this work,
we first present a new multi-mod... | 2008.03408 | title_snapshot |
kirkedal20_interspeech | FT Speech: Danish Parliament Speech Corpus | [
"Andreas Kirkedal",
"Marija StepanoviÄ",
"Barbara Plank"
] | https://www.isca-archive.org/interspeech_2020/kirkedal20_interspeech.html | https://www.isca-archive.org/interspeech_2020/kirkedal20_interspeech.pdf | 10.21437/Interspeech.2020-3164 | 442-446 | @inproceedings{kirkedal20_interspeech,
title = {{ FT Speech: Danish Parliament Speech Corpus}},
author = {Andreas Kirkedal and Marija StepanoviÄ and Barbara Plank},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {442--446},
doi = {10.21437/Interspeech.2020-3164},
issn ... | This paper introduces FT Speech, a new speech corpus created from
the recorded meetings of the Danish Parliament, otherwise known as
the Folketing (FT). The corpus contains over 1,800 hours of transcribed
speech by a total of 434 speakers. It is significantly larger in duration,
vocabulary, and amount of spontaneous ... | 2005.12368 | title_snapshot |
duroselle20_interspeech | Metric Learning Loss Functions to Reduce Domain Mismatch in the x-Vector Space for Language Recognition | [
"Raphaël Duroselle",
"Denis Jouvet",
"Irina Illina"
] | https://www.isca-archive.org/interspeech_2020/duroselle20_interspeech.html | https://www.isca-archive.org/interspeech_2020/duroselle20_interspeech.pdf | 10.21437/Interspeech.2020-1708 | 447-451 | @inproceedings{duroselle20_interspeech,
title = {{Metric Learning Loss Functions to Reduce Domain Mismatch in the x-Vector Space for Language Recognition}},
author = {Raphaël Duroselle and Denis Jouvet and Irina Illina},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {447--451},
d... | State-of-the-art language recognition systems are based on discriminative
embeddings called x-vectors. Channel and gender distortions produce
mismatch in such x-vector space where embeddings corresponding to
the same language are not grouped in an unique cluster. To control
this mismatch, we propose to train the x-v... | null | null |
li20e_interspeech | The XMUSPEECH System for the AP19-OLR Challenge | [
"Zheng Li",
"Miao Zhao",
"Jing Li",
"Yiming Zhi",
"Lin Li",
"Qingyang Hong"
] | https://www.isca-archive.org/interspeech_2020/li20e_interspeech.html | https://www.isca-archive.org/interspeech_2020/li20e_interspeech.pdf | 10.21437/Interspeech.2020-1923 | 452-456 | @inproceedings{li20e_interspeech,
title = {{The XMUSPEECH System for the AP19-OLR Challenge}},
author = {Zheng Li and Miao Zhao and Jing Li and Yiming Zhi and Lin Li and Qingyang Hong},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {452--456},
doi = {10.21437/Interspeech.202... | In this paper, we present our XMUSPEECH system for the oriental language
recognition (OLR) challenge, AP19-OLR. The challenge this year contained
three tasks: (1) short-utterance LID, (2) cross-channel LID, and (3)
zero-resource LID. We leveraged the system pipeline from three aspects,
including front-end training, bac... | null | null |
li20f_interspeech | On the Usage of Multi-Feature Integration for Speaker Verification and Language Identification | [
"Zheng Li",
"Miao Zhao",
"Jing Li",
"Lin Li",
"Qingyang Hong"
] | https://www.isca-archive.org/interspeech_2020/li20f_interspeech.html | https://www.isca-archive.org/interspeech_2020/li20f_interspeech.pdf | 10.21437/Interspeech.2020-1960 | 457-461 | @inproceedings{li20f_interspeech,
title = {{On the Usage of Multi-Feature Integration for Speaker Verification and Language Identification}},
author = {Zheng Li and Miao Zhao and Jing Li and Lin Li and Qingyang Hong},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {457--461},
doi ... | In this paper, we study the technology of multiple acoustic feature
integration for the applications of Automatic Speaker Verification
(ASV) and Language Identification (LID). In contrast to score level
fusion, a common method for integrating subsystems built upon various
acoustic features, we explore a new integration... | null | null |
chowdhury20_interspeech | What Does an End-to-End Dialect Identification Model Learn About Non-Dialectal Information? | [
"Shammur A. Chowdhury",
"Ahmed Ali",
"Suwon Shon",
"James Glass"
] | https://www.isca-archive.org/interspeech_2020/chowdhury20_interspeech.html | https://www.isca-archive.org/interspeech_2020/chowdhury20_interspeech.pdf | 10.21437/Interspeech.2020-2235 | 462-466 | @inproceedings{chowdhury20_interspeech,
title = {{What Does an End-to-End Dialect Identification Model Learn About Non-Dialectal Information?}},
author = {Shammur A. Chowdhury and Ahmed Ali and Suwon Shon and James Glass},
year = {2020},
booktitle = {{Interspeech 2020}},
pages = {462--466},
... | An end-to-end dialect identification system generates the likelihood
of each dialect, given a speech utterance. The performance relies on
its capabilities to discriminate the acoustic properties between the
different dialects, even though the input signal contains non-dialectal
information such as speaker and channel. ... | null | null |
lindgren20_interspeech | Releasing a Toolkit and Comparing the Performance of Language Embeddings Across Various Spoken Language Identification Datasets | [
"Matias Lindgren",
"Tommi Jauhiainen",
"Mikko Kurimo"
] | https://www.isca-archive.org/interspeech_2020/lindgren20_interspeech.html | https://www.isca-archive.org/interspeech_2020/lindgren20_interspeech.pdf | 10.21437/Interspeech.2020-2706 | 467-471 | @inproceedings{lindgren20_interspeech,
title = {{Releasing a Toolkit and Comparing the Performance of Language Embeddings Across Various Spoken Language Identification Datasets}},
author = {Matias Lindgren and Tommi Jauhiainen and Mikko Kurimo},
year = {2020},
booktitle = {{Interspeech 2020}},
pag... | In this paper, we propose a software toolkit for easier end-to-end
training of deep learning based spoken language identification models
across several speech datasets. We apply our toolkit to implement three
baseline models, one speaker recognition model, and three x-vector
architecture variations, which are trained o... | null | null |
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