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ORCIDASRU 2015: Scottsdale, AZ, USA
- 2015 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2015, Scottsdale, AZ, USA, December 13-17, 2015. IEEE 2015, ISBN 978-1-4799-7291-3
Automatic Speech Recognition I
- Irina Illina, Dominique Fohr:
Different word representations and their combination for proper name retrieval from diachronic documents. 1-7 - Ciprian Chelba, Noam Shazeer:
Sparse non-negative matrix language modeling for geo-annotated query session data. 8-14 - Naoyuki Kanda, Mitsuyoshi Tachimori, Xugang Lu, Hisashi Kawai:
Training data pseudo-shuffling and direct decoding framework for recurrent neural network based acoustic modeling. 15-21 - Khe Chai Sim:
On constructing and analysing an interpretable brain model for the DNN based on hidden activity patterns. 22-29 - Tara N. Sainath, Ron J. Weiss, Kevin W. Wilson, Arun Narayanan, Michiel Bacchiani, Andrew W. Senior:
Speaker location and microphone spacing invariant acoustic modeling from raw multichannel waveforms. 30-36 - Suman V. Ravuri:
Hybrid DNN-Latent structured SVM acoustic models for continuous speech recognition. 37-44 - Shuangyu Chang, Abhik Lahiri, Issac Alphonso, Barlas Oguz, Michael Levit, Benoît Dumoulin:
Discriminative training of context-dependent language model scaling factors and interpolation weights. 45-51 - Ryu Takeda
, Kazunori Komatani, Kazuhiro Nakadai:
Acoustic model training based on node-wise weight boundary model increasing speed of discrete neural networks. 52-58 - Zhichao Wang, Xingyu Na, Xin Li, Jielin Pan, Yonghong Yan:
Two-stage ASGD framework for parallel training of DNN acoustic models using Ethernet. 59-64 - Taesup Moon, Heeyoul Choi, Hoshik Lee, Inchul Song:
RNNDROP: A novel dropout for RNNS in ASR. 65-70 - Hadrien Glaude, Cyrille Enderli, Olivier Pietquin:
Spectral learning with non negative probabilities for finite state automaton. 71-77 - Abdel-rahman Mohamed, Frank Seide, Dong Yu, Jasha Droppo, Andreas Stolcke, Geoffrey Zweig, Gerald Penn:
Deep bi-directional recurrent networks over spectral windows. 78-83 - Bo-Hsiang Tseng, Hung-yi Lee, Lin-Shan Lee:
Personalizing universal recurrent neural network language model with user characteristic features by social network crowdsourcing. 84-91 - David Snyder, Daniel Garcia-Romero, Daniel Povey:
Time delay deep neural network-based universal background models for speaker recognition. 92-97
Text-to-Speech Systems
- Chuang Ding, Lei Xie, Jie Yan, Weini Zhang, Yang Liu:
Automatic prosody prediction for Chinese speech synthesis using BLSTM-RNN and embedding features. 98-102 - Nichola Lubold, Heather Pon-Barry, Erin Walker:
Naturalness and rapport in a pitch adaptive learning companion. 103-110 - Sai Krishna Rallabandi, Sai Sirisha Rallabandi, Padmini Bandi, Suryakanth V. Gangashetty:
Learning continuous representation of text for phone duration modeling in statistical parametric speech synthesis. 111-115 - Mahsa Sadat Elyasi Langarani, Jan P. H. van Santen:
Speaker intonation adaptation for transforming text-to-speech synthesis speaker identity. 116-123
Automatic Speech Recognition II
- Gueorgui Pironkov, Stéphane Dupont, Thierry Dutoit:
Investigating sparse deep neural networks for speech recognition. 124-129 - Mortaza Doulaty, Oscar Saz, Raymond W. M. Ng, Thomas Hain:
Latent Dirichlet Allocation based organisation of broadcast media archives for deep neural network adaptation. 130-136 - Yi-Hsiu Liao, Hung-yi Lee, Lin-Shan Lee:
Towards structured deep neural network for automatic speech recognition. 137-144 - Lahiru Samarakoon, Khe Chai Sim:
Learning factorized feature transforms for speaker normalization. 145-152 - Thiago Fraga-Silva, Antoine Laurent, Jean-Luc Gauvain, Lori Lamel, Viet Bac Le, Abdelkhalek Messaoudi:
Improving data selection for low-resource STT and KWS. 153-159 - Rogier C. van Dalen, Jingzhou Yang, Haipeng Wang, Anton Ragni, Chao Zhang, Mark J. F. Gales:
Structured discriminative models using deep neural-network features. 160-166 - Yajie Miao, Mohammad Gowayyed, Florian Metze:
EESEN: End-to-end speech recognition using deep RNN models and WFST-based decoding. 167-174 - Andros Tjandra, Sakriani Sakti, Satoshi Nakamura, Mirna Adriani:
Stochastic Gradient Variational Bayes for deep learning-based ASR. 175-180 - Xie Chen, Xunying Liu, Mark J. F. Gales, Philip C. Woodland:
Investigation of back-off based interpolation between recurrent neural network and n-gram language models. 181-186 - Jinyu Li, Abdelrahman Mohamed, Geoffrey Zweig, Yifan Gong:
LSTM time and frequency recurrence for automatic speech recognition. 187-191
Spoken Document Retrieval, Speech Summarization, and Applications
- Scott Novotney, Kevin Jett, Owen Kimball:
Incorporating user feedback to re-rank keyword search results. 192-199 - Nagisa Sakamoto, Kazumasa Yamamoto, Seiichi Nakagawa:
Combination of syllable based N-gram search and word search for spoken term detection through spoken queries and IV/OOV classification. 200-206 - Kuan-Yu Chen, Kai-Wun Shih, Shih-Hung Liu, Berlin Chen, Hsin-Min Wang:
Incorporating paragraph embeddings and density peaks clustering for spoken document summarization. 207-214 - Meng Cai, Zhiqiang Lv, Cheng Lu, Jian Kang, Like Hui, Zhuo Zhang, Jia Liu:
High-performance Swahili keyword search with very limited language pack: The THUEE system for the OpenKWS15 evaluation. 215-222 - Paula Lopez-Otero, Laura Docío Fernández, Carmen García-Mateo:
Phonetic unit selection for cross-lingual query-by-example spoken term detection. 223-229 - Zhiqiang Lv, Meng Cai, Cheng Lu, Jian Kang, Like Hui, Wei-Qiang Zhang, Jia Liu:
Improved system fusion for keyword search. 230-236 - David F. Harwath, James R. Glass:
Deep multimodal semantic embeddings for speech and images. 237-244 - Cheng-Tao Chung, Cheng-Yu Tsai, Hsiang-Hung Lu, Chia-Hsiang Liu, Hung-yi Lee, Lin-Shan Lee:
An iterative deep learning framework for unsupervised discovery of speech features and linguistic units with applications on spoken term detection. 245-251 - Sakriani Sakti, Faiz Ilham, Graham Neubig, Tomoki Toda, Ayu Purwarianti, Satoshi Nakamura:
Incremental sentence compression using LSTM recurrent networks. 252-258 - Jia Cui, Brian Kingsbury, Bhuvana Ramabhadran, Abhinav Sethy, Kartik Audhkhasi, Xiaodong Cui, Ellen Kislal, Lidia Mangu, Markus Nußbaum-Thom, Michael Picheny, Zoltán Tüske, Pavel Golik, Ralf Schlüter, Hermann Ney, Mark J. F. Gales, Kate M. Knill, Anton Ragni, Haipeng Wang, Philip C. Woodland:
Multilingual representations for low resource speech recognition and keyword search. 259-266
Robustness in Automatic Speech Recognition, Speech-to-Speech Translation, and Spontaneous Speech Processing
- Laurent Besacier, Benjamin Lecouteux, Ngoc-Quang Luong, Ngoc-Tien Le:
Spoken language translation graphs re-decoding using automatic quality assessment. 267-274 - Mirco Ravanelli, Luca Cristoforetti, Roberto Gretter, Marco Pellin, Alessandro Sosi, Maurizio Omologo:
The DIRHA-ENGLISH corpus and related tasks for distant-speech recognition in domestic environments. 275-282 - Sri Harish Reddy Mallidi, Tetsuji Ogawa, Hynek Hermansky:
Uncertainty estimation of DNN classifiers. 283-288 - Ivan Himawan, Petr Motlícek, Marc Ferras Font, Srikanth R. Madikeri:
Towards utterance-based neural network adaptation in acoustic modeling. 289-295 - Nicholas Ruiz, Marcello Federico:
Phonetically-oriented word error alignment for speech recognition error analysis in speech translation. 296-302 - Lara J. Martin, Andrew Wilkinson, Sai Sumanth Miryala, Vivian Robison, Alan W. Black:
Utterance classification in speech-to-speech translation for zero-resource languages in the hospital administration domain. 303-309 - Yanmin Qian, Maofan Yin, Yongbin You, Kai Yu:
Multi-task joint-learning of deep neural networks for robust speech recognition. 310-316 - Vikramjit Mitra, Horacio Franco:
Time-frequency convolutional networks for robust speech recognition. 317-323 - Wen Wang, Haibo Li, Heng Ji:
Name-aware language model adaptation and sparse features for statistical machine translation. 324-330 - Shivesh Ranjan, Gang Liu, John H. L. Hansen:
An i-Vector PLDA based gender identification approach for severely distorted and multilingual DARPA RATS data. 331-337 - Zhou Yu, Vikram Ramanarayanan, David Suendermann-Oeft, Xinhao Wang, Klaus Zechner, Lei Chen, Jidong Tao, Aliaksei Ivanou, Yao Qian:
Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech. 338-345
Spoken Language Understanding
- Mohamed Morchid, Richard Dufour, Georges Linarès:
Topic-space based setup of a neural network for theme identification of highly imperfect transcriptions. 346-352 - Yangyang Shi, Kaisheng Yao, Hu Chen, Yi-Cheng Pan, Mei-Yuh Hwang:
Semi-supervised slot tagging in spoken language understanding using recurrent transductive support vector machines. 353-360 - Asli Celikyilmaz, Zhaleh Feizollahi, Dilek Hakkani-Tür, Ruhi Sarikaya:
A universal model for flexible item selection in conversational dialogs. 361-367 - Suman V. Ravuri, Andreas Stolcke:
A comparative study of neural network models for lexical intent classification. 368-374 - Yun-Nung Chen, Dilek Hakkani-Tür, Xiaodong He:
Detecting actionable items in meetings by convolutional deep structured semantic models. 375-382 - Mickael Rouvier, Sebastien Delecraz, Benoît Favre, Meriem Bendris, Frédéric Béchet:
Multimodal embedding fusion for robust speaker role recognition in video broadcast. 383-389 - Marc-Antoine Rondeau, Yi Su:
Recent improvements to NeuroCRFs for named entity recognition. 390-396 - Xiaohu Liu, Asli Celikyilmaz, Ruhi Sarikaya:
Natural language understanding for partial queries. 397-400
3rd Chime Speech Separation and Recognition Challenge
- Alexey Prudnikov, Maxim Korenevsky, Sergei Aleinik:
Adaptive beamforming and adaptive training of DNN acoustic models for enhanced multichannel noisy speech recognition. 401-408 - Shahab Jalalvand, Daniele Falavigna, Marco Matassoni, Piergiorgio Svaizer, Maurizio Omologo:
Boosted acoustic model learning and hypotheses rescoring on the CHiME-3 task. 409-415 - Yusuke Fujita, Ryoichi Takashima, Takeshi Homma, Rintaro Ikeshita, Yohei Kawaguchi, Takashi Sumiyoshi, Takashi Endo, Masahito Togami:
Unified ASR system using LGM-based source separation, noise-robust feature extraction, and word hypothesis selection. 416-422 - Thanh T. Vu, Benjamin Bigot, Engsiong Chng:
Speech enhancement using beamforming and non negative matrix factorization for robust speech recognition in the CHiME-3 challenge. 423-429 - Jun Du, Qing Wang, Yanhui Tu, Xiao Bao, Li-Rong Dai, Chin-Hui Lee:
An information fusion approach to recognizing microphone array speech in the CHiME-3 challenge based on a deep learning framework. 430-435 - Takuya Yoshioka, Nobutaka Ito, Marc Delcroix, Atsunori Ogawa, Keisuke Kinoshita, Masakiyo Fujimoto, Chengzhu Yu, Wojciech J. Fabian, Miquel Espi, Takuya Higuchi, Shoko Araki, Tomohiro Nakatani:
The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices. 436-443 - Jahn Heymann, Lukas Drude, Aleksej Chinaev, Reinhold Haeb-Umbach:
BLSTM supported GEV beamformer front-end for the 3RD CHiME challenge. 444-451 - Lukas Pfeifenberger, Tobias Schrank, Matthias Zöhrer, Martin Hagmüller, Franz Pernkopf:
Multi-channel speech processing architectures for noise robust speech recognition: 3rd CHiME challenge results. 452-459 - Shengkui Zhao, Xiong Xiao, Zhaofeng Zhang, Thi Ngoc Tho Nguyen, Xionghu Zhong, Bo Ren, Longbiao Wang, Douglas L. Jones, Engsiong Chng, Haizhou Li:
Robust speech recognition using beamforming with adaptive microphone gains and multichannel noise reduction. 460-467 - Niko Moritz, Stephan Gerlach, Kamil Adiloglu, Jörn Anemüller, Birger Kollmeier, Stefan Goetze:
A CHiME-3 challenge system: Long-term acoustic features for noise robust automatic speech recognition. 468-474 - Takaaki Hori, Zhuo Chen, Hakan Erdogan, John R. Hershey, Jonathan Le Roux, Vikramjit Mitra, Shinji Watanabe:
The MERL/SRI system for the 3RD CHiME challenge using beamforming, robust feature extraction, and advanced speech recognition. 475-481 - Sunit Sivasankaran, Aditya Arie Nugraha, Emmanuel Vincent, Juan Andres Morales-Cordovilla, Siddharth Dalmia, Irina Illina, Antoine Liutkus:
Robust ASR using neural network based speech enhancement and feature simulation. 482-489 - Ning Ma, Ricard Marxer, Jon Barker, Guy J. Brown:
Exploiting synchrony spectra and deep neural networks for noise-robust automatic speech recognition. 490-495 - Deblin Bagchi, Michael I. Mandel, Zhongqiu Wang, Yanzhang He, Andrew R. Plummer, Eric Fosler-Lussier:
Combining spectral feature mapping and multi-channel model-based source separation for noise-robust automatic speech recognition. 496-503 - Jon Barker, Ricard Marxer, Emmanuel Vincent, Shinji Watanabe:
The third 'CHiME' speech separation and recognition challenge: Dataset, task and baselines. 504-511
Automatic Speech Recognition in Reverberant Environments (ASPIRE)
- Jennifer Melot, Nicolas Malyska, Jessica Ray, Wade Shen:
Analysis of factors affecting system performance in the ASpIRE challenge. 512-517 - Jonathan William Dennis, Tran Huy Dat:
Single and multi-channel approaches for distant speech recognition under noisy reverberant conditions: I2R'S system description for the ASpIRE challenge. 518-524 - Vikramjit Mitra, Julien van Hout, Wen Wang, Martin Graciarena, Mitchell McLaren, Horacio Franco, Dimitra Vergyri:
Improving robustness against reverberation for automatic speech recognition. 525-532 - Roger Hsiao, Jeff Z. Ma, William Hartmann, Martin Karafiát, Frantisek Grézl, Lukás Burget, Igor Szöke, Jan Cernocký, Shinji Watanabe, Zhuo Chen, Sri Harish Reddy Mallidi, Hynek Hermansky, Stavros Tsakalidis, Richard M. Schwartz:
Robust speech recognition in unknown reverberant and noisy conditions. 533-538 - Vijayaditya Peddinti, Guoguo Chen, Vimal Manohar, Tom Ko, Daniel Povey, Sanjeev Khudanpur:
JHU ASpIRE system: Robust LVCSR with TDNNS, iVector adaptation and RNN-LMS. 539-546 - Mary Harper:
The Automatic Speech recogition In Reverberant Environments (ASpIRE) challenge. 547-554
Automatic Speech Recognition III
- Sina Hamidi Ghalehjegh, Richard C. Rose:
Deep bottleneck features for i-vector based text-independent speaker verification. 555-560 - Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
Discriminative segmental cascades for feature-rich phone recognition. 561-568 - Steven Sandoval, Phillip L. De Leon, Julie M. Liss:
Hilbert spectral analysis of vowels using intrinsic mode functions. 569-575 - Ahmed M. Ali, Walid Magdy, Peter Bell, Steve Renals:
Multi-reference WER for evaluating ASR for languages with no orthographic rules. 576-580 - Yuzong Liu, Katrin Kirchhoff:
Acoustic modeling with neural graph embeddings. 581-588 - Olivier Siohan, David Rybach:
Multitask learning and system combination for automatic speech recognition. 589-595 - Zoltán Tüske, Pavel Golik, Ralf Schlüter, Hermann Ney:
Speaker adaptive joint training of Gaussian mixture models and bottleneck features. 596-603 - Andrew W. Senior, Hasim Sak, Felix de Chaumont Quitry, Tara N. Sainath, Kanishka Rao:
Acoustic modelling with CD-CTC-SMBR LSTM RNNS. 604-609 - Takafumi Moriya, Tomohiro Tanaka, Takahiro Shinozaki, Shinji Watanabe, Kevin Duh:
Automation of system building for state-of-the-art large vocabulary speech recognition using evolution strategy. 610-616 - Shawn Tan, Khe Chai Sim, Mark J. F. Gales:
Improving the interpretability of deep neural networks with stimulated learning. 617-623
The MGB Challenge - Recognition of Multi-Genre Broadcast Data
- Oscar Saz, Mortaza Doulaty, Salil Deena, Rosanna Milner, Raymond W. M. Ng, Madina Hasan, Yulan Liu, Thomas Hain:
The 2015 sheffield system for transcription of Multi-Genre Broadcast media. 624-631 - Rosanna Milner, Oscar Saz, Salil Deena, Mortaza Doulaty, Raymond W. M. Ng, Thomas Hain:
The 2015 sheffield system for longitudinal diarisation of broadcast media. 632-638 - Philip C. Woodland, Xunying Liu, Yanmin Qian, Chao Zhang, Mark J. F. Gales, Penny Karanasou, Pierre Lanchantin, Linlin Wang:
Cambridge university transcription systems for the multi-genre broadcast challenge. 639-646 - Pierre Lanchantin, Mark J. F. Gales, Penny Karanasou, Xunying Liu, Yanmin Qian, Linlin Wang, Philip C. Woodland, Chao Zhang:
The development of the cambridge university alignment systems for the multi-genre broadcast challenge. 647-653 - Quoc Truong Do, Michael Heck, Sakriani Sakti, Graham Neubig, Tomoki Toda, Satoshi Nakamura:
The NAIST ASR system for the 2015 Multi-Genre Broadcast challenge: On combination of deep learning systems using a rank-score function. 654-659 - Penny Karanasou, Mark J. F. Gales, Pierre Lanchantin, Xunying Liu, Yanmin Qian, Linlin Wang, Philip C. Woodland, Chao Zhang:
Speaker diarisation and longitudinal linking in multi-genre broadcast data. 660-666 - Jesús Antonio Villalba López, Alfonso Ortega, Antonio Miguel, Eduardo Lleida:
Variational Bayesian PLDA for speaker diarization in the MGB challenge. 667-674 - Peter Bell, Steve Renals:
A system for automatic alignment of broadcast media captions using weighted finite-state transducers. 675-680 - Vishwa Gupta, Paul Deléglise, Gilles Boulianne, Yannick Estève, Sylvain Meignier, Anthony Rousseau:
CRIM and LIUM approaches for multi-genre broadcast media transcription. 681-686 - Peter Bell, Mark J. F. Gales, Thomas Hain, Jonathan Kilgour, Pierre Lanchantin, Xunying Liu, Andrew McParland, Steve Renals, Oscar Saz, Mirjam Wester, Philip C. Woodland:
The MGB challenge: Evaluating multi-genre broadcast media recognition. 687-693
Spoken Dialog Systems
- Lukás Zilka, Filip Jurcícek:
Incremental LSTM-based dialog state tracker. 757-762 - David Vandyke, Pei-hao Su, Milica Gasic, Nikola Mrksic, Tsung-Hsien Wen, Steve J. Young:
Multi-domain dialogue success classifiers for policy training. 763-770 - Jeesoo Bang, Sangdo Han, Kyusong Lee, Gary Geunbae Lee:
Open-domain personalized dialog system using user-interested topics in system responses. 771-776 - Nurul Lubis, Sakriani Sakti, Graham Neubig, Koichiro Yoshino, Tomoki Toda, Satoshi Nakamura:
A study of social-affective communication: Automatic prediction of emotion triggers and responses in television talk shows. 777-783 - Masahiro Mizukami, Hideaki Kizuki, Toshio Nomura, Graham Neubig, Koichiro Yoshino, Sakriani Sakti, Tomoki Toda, Satoshi Nakamura:
Adaptive selection from multiple response candidates in example-based dialogue. 784-790 - Hang Ren, Weiqun Xu, Yonghong Yan:
Optimizing human-interpretable dialog management policy using genetic algorithm. 791-797 - Sangjun Koo, Seonghan Ryu, Gary Geunbae Lee:
Implementation of generic positive-negative tracker in extensible dialog system. 798-805 - Milica Gasic, Nikola Mrksic, Pei-hao Su, David Vandyke, Tsung-Hsien Wen, Steve J. Young:
Policy committee for adaptation in multi-domain spoken dialogue systems. 806-812 - Minwei Feng, Bing Xiang, Michael R. Glass, Lidan Wang, Bowen Zhou:
Applying deep learning to answer selection: A study and an open task. 813-820
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