ASRU 2015

Author Index

Click on a letter below to link to a list of authors with last names beginning with that letter.

A B C D E F G H I J K L M N O P Q R S T V W X Y Z

A

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Adiloglu, Kamil	(pg. 468) T2.10: A CHIME-3 CHALLENGE SYSTEM: LONG-TERM ACOUSTIC FEATURES FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION
Adriani, Mirna	(pg. 175) M3.8: STOCHASTIC GRADIENT VARIATIONAL BAYES FOR DEEP LEARNING-BASED ASR
Alam, Firoj	(Demo) W1.3: AUTOMATIC SUMMARIZATION OF CALL-CENTER CONVERSATIONS
Aleinik, Sergei	(pg. 401) T2.1: ADAPTIVE BEAMFORMING AND ADAPTIVE TRAINING OF DNN ACOUSTIC MODELS FOR ENHANCED MULTICHANNEL NOISY SPEECH RECOGNITION
Ali, Ahmed	(pg. 576) T3.4: MULTI-REFERENCE WER FOR EVALUATING ASR FOR LANGUAGES WITH NO ORTHOGRAPHIC RULES (Demo) W1.4: LAHAJET: A GAME FOR CLASSIFYING DIALECTAL ARABIC SPEECH
Alphonso, Issac	(pg. 45) M1.7: DISCRIMINATIVE TRAINING OF CONTEXT-DEPENDENT LANGUAGE MODEL SCALING FACTORS AND INTERPOLATION WEIGHTS
Anemüller, Jörn	(pg. 468) T2.10: A CHIME-3 CHALLENGE SYSTEM: LONG-TERM ACOUSTIC FEATURES FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION
Araki, Shoko	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Audhkhasi, Kartik	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH

B

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Ba Be Bi Bl Bo Br Bu

Bacchiani, Michiel	(pg. 30) M1.5: SPEAKER LOCATION AND MICROPHONE SPACING INVARIANT ACOUSTIC MODELING FROM RAW MULTICHANNEL WAVEFORMS
Bagchi, Deblin	(pg. 496) T2.14: COMBINING SPECTRAL FEATURE MAPPING AND MULTI-CHANNEL MODEL-BASED SOURCE SEPARATION FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION
Bandi, Padmini	(pg. 111) M2.3: LEARNING CONTINUOUS REPRESENTATION OF TEXT FOR PHONE DURATION MODELING IN STATISTICAL PARAMETRIC SPEECH SYNTHESIS
Bang, Jeesoo	(pg. 771) W2.3: OPEN-DOMAIN PERSONALIZED DIALOG SYSTEM USING USER-INTERESTED TOPICS IN SYSTEM RESPONSES
Bao, Xiao	(pg. 430) T2.5: AN INFORMATION FUSION APPROACH TO RECOGNIZING MICROPHONE ARRAY SPEECH IN THE CHIME-3 CHALLENGE BASED ON A DEEP LEARNING FRAMEWORK
Barker, Jon	(pg. 490) T2.13: EXPLOITING SYNCHRONY SPECTRA AND DEEP NEURAL NETWORKS FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION (pg. 504) T2.15: THE THIRD `CHIME' SPEECH SEPARATION AND RECOGNITION CHALLENGE: DATASET, TASK AND BASELINES
Béchet, Frederic	(pg. 383) R2.6: MULTIMODAL EMBEDDING FUSION FOR ROBUST SPEAKER ROLE RECOGNITION IN VIDEO BROADCAST (Demo) W1.3: AUTOMATIC SUMMARIZATION OF CALL-CENTER CONVERSATIONS
Bell, Peter	(pg. 576) T3.4: MULTI-REFERENCE WER FOR EVALUATING ASR FOR LANGUAGES WITH NO ORTHOGRAPHIC RULES (pg. 675) T4.8: A SYSTEM FOR AUTOMATIC ALIGNMENT OF BROADCAST MEDIA CAPTIONS USING WEIGHTED FINITE-STATE TRANSDUCERS (pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Bendris, Meriem	(pg. 383) R2.6: MULTIMODAL EMBEDDING FUSION FOR ROBUST SPEAKER ROLE RECOGNITION IN VIDEO BROADCAST
Besacier, Laurent	(pg. 267) R1.1: SPOKEN LANGUAGE TRANSLATION GRAPHS RE-DECODING USING AUTOMATIC QUALITY ASSESSMENT
Bigot, Benjamin	(pg. 423) T2.4: SPEECH ENHANCEMENT USING BEAMFORMING AND NON NEGATIVE MATRIX FACTORIZATION FOR ROBUST SPEECH RECOGNITION IN THE CHIME-3 CHALLENGE
Black, Alan W.	(pg. 303) R1.6: UTTERANCE CLASSIFICATION IN SPEECH-TO-SPEECH TRANSLATION FOR ZERO-RESOURCE LANGUAGES IN THE HOSPITAL ADMINISTRATION DOMAIN (Demo) W1.7: A MODULAR OPEN-SOURCE STANDARD-COMPLIANT DIALOG SYSTEM FRAMEWORK WITH VIDEO SUPPORT
Boulianne, Gilles	(pg. 681) T4.9: CRIM AND LIUM APPROACHES FOR MULTI-GENRE BROADCAST MEDIA TRANSCRIPTION
Brown, Guy J.	(pg. 490) T2.13: EXPLOITING SYNCHRONY SPECTRA AND DEEP NEURAL NETWORKS FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION
Burget, Lukas	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS

C

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Ca Ce Ch Cr Cu

Cai, Meng	(pg. 215) M4.4: HIGH-PERFORMANCE SWAHILI KEYWORD SEARCH WITH VERY LIMITED LANGUAGE PACK: THE THUEE SYSTEM FOR THE OPENKWS15 EVALUATION (pg. 230) M4.6: IMPROVED SYSTEM FUSION FOR KEYWORD SEARCH
Celikyilmaz, Asli	(pg. 361) R2.3: A UNIVERSAL MODEL FOR FLEXIBLE ITEM SELECTION IN CONVERSATIONAL DIALOGS (pg. 397) R2.8: NATURAL LANGUAGE UNDERSTANDING FOR PARTIAL QUERIES
Cernocky, Jan Honza	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Chang, Shuangyu	(pg. 45) M1.7: DISCRIMINATIVE TRAINING OF CONTEXT-DEPENDENT LANGUAGE MODEL SCALING FACTORS AND INTERPOLATION WEIGHTS
Chelba, Ciprian	(pg. 8) M1.2: SPARSE NON-NEGATIVE MATRIX LANGUAGE MODELING FOR GEO-ANNOTATED QUERY SESSION DATA
Chen, Berlin	(pg. 207) M4.3: INCORPORATING PARAGRAPH EMBEDDINGS AND DENSITY PEAKS CLUSTERING FOR SPOKEN DOCUMENT SUMMARIZATION
Chen, Guoguo	(pg. 539) T1.5: JHU ASPIRE SYSTEM : ROBUST LVCSR WITH TDNNS, IVECTOR ADAPTATION AND RNN-LMS
Chen, Hu	(pg. 353) R2.2: SEMI-SUPERVISED SLOT TAGGING IN SPOKEN LANGUAGE UNDERSTANDING USING RECURRENT TRANSDUCTIVE SUPPORT VECTOR MACHINES
Chen, Kuan-Yu	(pg. 207) M4.3: INCORPORATING PARAGRAPH EMBEDDINGS AND DENSITY PEAKS CLUSTERING FOR SPOKEN DOCUMENT SUMMARIZATION
Chen, Lei	(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH
Chen, Xie	(pg. 181) M3.9: INVESTIGATION OF BACK-OFF BASED INTERPOLATION BETWEEN RECURRENT NEURAL NETWORK AND N-GRAM LANGUAGE MODELS
Chen, Yun-Nung	(pg. 375) R2.5: DETECTING ACTIONABLE ITEMS IN MEETINGS BY CONVOLUTIONAL DEEP STRUCTURED SEMANTIC MODELS
Chen, Zhuo	(pg. 475) T2.11: THE MERL/SRI SYSTEM FOR THE 3RD CHIME CHALLENGE USING BEAMFORMING, ROBUST FEATURE EXTRACTION, AND ADVANCED SPEECH RECOGNITION (pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Chinaev, Aleksej	(pg. 444) T2.7: BLSTM SUPPORTED GEV BEAMFORMER FRONT-END FOR THE 3RD CHIME CHALLENGE
Chng, Eng Siong	(pg. 423) T2.4: SPEECH ENHANCEMENT USING BEAMFORMING AND NON NEGATIVE MATRIX FACTORIZATION FOR ROBUST SPEECH RECOGNITION IN THE CHIME-3 CHALLENGE (pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Choi, Heeyoul	(pg. 65) M1.10: RNNDROP: A NOVEL DROPOUT FOR RNNS IN ASR
Chowdhury, S.	(Demo) W1.3: AUTOMATIC SUMMARIZATION OF CALL-CENTER CONVERSATIONS
Chung, Cheng-Tao	(pg. 245) M4.8: AN ITERATIVE DEEP LEARNING FRAMEWORK FOR UNSUPERVISED DISCOVERY OF SPEECH FEATURES AND LINGUISTIC UNITS WITH APPLICATIONS ON SPOKEN TERM DETECTION
Cristoforetti, Luca	(pg. 275) R1.2: THE DIRHA-ENGLISH CORPUS AND RELATED TASKS FOR DISTANT-SPEECH RECOGNITION IN DOMESTIC ENVIRONMENTS
Cui, Jia	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Cui, Xiaodong	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH

D

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Da de Di Do Dr Du

Dai, Li-Rong	(pg. 430) T2.5: AN INFORMATION FUSION APPROACH TO RECOGNIZING MICROPHONE ARRAY SPEECH IN THE CHIME-3 CHALLENGE BASED ON A DEEP LEARNING FRAMEWORK
Dalmia, Siddharth	(pg. 482) T2.12: ROBUST ASR USING NEURAL NETWORK BASED SPEECH ENHANCEMENT AND FEATURE SIMULATION
de Chaumont Quitry, Felix	(pg. 604) T3.8: ACOUSTIC MODELLING WITH CD-CTC-SMBR LSTM RNNS
De Leon, Phillip L.	(pg. 569) T3.3: HILBERT SPECTRAL ANALYSIS OF VOWELS USING INTRINSIC MODE FUNCTIONS (Demo) W1.5: VISUALIZATION OF THE HILBERT SPECTRUM
Deena, Salil	(pg. 624) T4.1: THE 2015 SHEFFIELD SYSTEM FOR TRANSCRIPTION OF MULTI-GENRE BROADCAST MEDIA (pg. 632) T4.2: THE 2015 SHEFFIELD SYSTEM FOR LONGITUDINAL DIARISATION OF BROADCAST MEDIA
Delcroix, Marc	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Delecraz, Sebastien	(pg. 383) R2.6: MULTIMODAL EMBEDDING FUSION FOR ROBUST SPEAKER ROLE RECOGNITION IN VIDEO BROADCAST
Deleglise, Paul	(pg. 681) T4.9: CRIM AND LIUM APPROACHES FOR MULTI-GENRE BROADCAST MEDIA TRANSCRIPTION
Dennis, Jonathan	(pg. 518) T1.2: SINGLE AND MULTI-CHANNEL APPROACHES FOR DISTANT SPEECH RECOGNITION UNDER NOISY REVERBERANT CONDITIONS: I2R'S SYSTEM DESCRIPTION FOR THE ASPIRE CHALLENGE
Ding, Chuang	(pg. 98) M2.1: AUTOMATIC PROSODY PREDICTION FOR CHINESE SPEECH SYNTHESIS USING BLSTM-RNN AND EMBEDDING FEATURES
Do, Quoc Truong	(pg. 654) T4.5: THE NAIST ASR SYSTEM FOR THE 2015 MULTI-GENRE BROADCAST CHALLENGE: ON COMBINATION OF DEEP LEARNING SYSTEMS USING A RANK-SCORE FUNCTION
Docio-Fernandez, Laura	(pg. 223) M4.5: PHONETIC UNIT SELECTION FOR CROSS-LINGUAL QUERY-BY-EXAMPLE SPOKEN TERM DETECTION
Doulaty, Mortaza	(pg. 130) M3.2: LATENT DIRICHLET ALLOCATION BASED ORGANISATION OF BROADCAST MEDIA ARCHIVES FOR DEEP NEURAL NETWORK ADAPTATION (pg. 624) T4.1: THE 2015 SHEFFIELD SYSTEM FOR TRANSCRIPTION OF MULTI-GENRE BROADCAST MEDIA (pg. 632) T4.2: THE 2015 SHEFFIELD SYSTEM FOR LONGITUDINAL DIARISATION OF BROADCAST MEDIA
Droppo, Jasha	(pg. 78) M1.12: DEEP BI-DIRECTIONAL RECURRENT NETWORKS OVER SPECTRAL WINDOWS
Drude, Lukas	(pg. 444) T2.7: BLSTM SUPPORTED GEV BEAMFORMER FRONT-END FOR THE 3RD CHIME CHALLENGE
Du, Jun	(pg. 430) T2.5: AN INFORMATION FUSION APPROACH TO RECOGNIZING MICROPHONE ARRAY SPEECH IN THE CHIME-3 CHALLENGE BASED ON A DEEP LEARNING FRAMEWORK
Dufour, Richard	(pg. 346) R2.1: TOPIC-SPACE BASED SETUP OF A NEURAL NETWORK FOR THEME IDENTIFICATION OF HIGHLY IMPERFECT TRANSCRIPTIONS
Duh, Kevin	(pg. 610) T3.9: AUTOMATION OF SYSTEM BUILDING FOR STATE-OF-THE-ART LARGE VOCABULARY SPEECH RECOGNITION USING EVOLUTION STRATEGY
Dumoulin, Benoit	(pg. 45) M1.7: DISCRIMINATIVE TRAINING OF CONTEXT-DEPENDENT LANGUAGE MODEL SCALING FACTORS AND INTERPOLATION WEIGHTS
Dupont, Stéphane	(pg. 124) M3.1: INVESTIGATING SPARSE DEEP NEURAL NETWORKS FOR SPEECH RECOGNITION
Dutoit, Thierry	(pg. 124) M3.1: INVESTIGATING SPARSE DEEP NEURAL NETWORKS FOR SPEECH RECOGNITION

E

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El En Er Es

Elyasi Langarani, Mahsa Sadat	(pg. 116) M2.4: SPEAKER INTONATION ADAPTATION FOR TRANSFORMING TEXT-TO-SPEECH SYNTHESIS SPEAKER IDENTITY
Enderli, Cyrille	(pg. 71) M1.11: SPECTRAL LEARNING WITH NON NEGATIVE PROBABILITIES FOR FINITE STATE AUTOMATON
Endo, Takashi	(pg. 416) T2.3: UNIFIED ASR SYSTEM USING LGM-BASED SOURCE SEPARATION, NOISE-ROBUST FEATURE EXTRACTION, AND WORD HYPOTHESIS SELECTION
Erdogan, Hakan	(pg. 475) T2.11: THE MERL/SRI SYSTEM FOR THE 3RD CHIME CHALLENGE USING BEAMFORMING, ROBUST FEATURE EXTRACTION, AND ADVANCED SPEECH RECOGNITION
Espi, Miquel	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Esteve, Yannick	(pg. 681) T4.9: CRIM AND LIUM APPROACHES FOR MULTI-GENRE BROADCAST MEDIA TRANSCRIPTION

F

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Fa Fe Fo Fr Fu

Fabian, Wojciech	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Falavigna, Daniele	(pg. 409) T2.2: BOOSTED ACOUSTIC MODEL LEARNING AND HYPOTHESES RESCORING ON THE CHIME-3 TASK
Favre, Benoit	(pg. 383) R2.6: MULTIMODAL EMBEDDING FUSION FOR ROBUST SPEAKER ROLE RECOGNITION IN VIDEO BROADCAST (Demo) W1.3: AUTOMATIC SUMMARIZATION OF CALL-CENTER CONVERSATIONS
Federico, Marcello	(pg. 296) R1.5: PHONETICALLY-ORIENTED WORD ERROR ALIGNMENT FOR SPEECH RECOGNITION ERROR ANALYSIS IN SPEECH TRANSLATION
Feizollahi, Zhaleh	(pg. 361) R2.3: A UNIVERSAL MODEL FOR FLEXIBLE ITEM SELECTION IN CONVERSATIONAL DIALOGS
Feng, Minwei	(pg. 813) W2.9: APPLYING DEEP LEARNING TO ANSWER SELECTION: A STUDY AND AN OPEN TASK
Fohr, Dominique	(pg. 1) M1.1: DIFFERENT WORD REPRESENTATIONS AND THEIR COMBINATION FOR PROPER NAME RETRIEVAL FROM DIACHRONIC DOCUMENTS
Font, Marc Ferras	(pg. 289) R1.4: TOWARDS UTTERANCE-BASED NEURAL NETWORK ADAPTATION IN ACOUSTIC MODELING
Fosler-Lussier, Eric	(pg. 496) T2.14: COMBINING SPECTRAL FEATURE MAPPING AND MULTI-CHANNEL MODEL-BASED SOURCE SEPARATION FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION
Fraga da Silva, Thiago	(pg. 153) M3.5: IMPROVING DATA SELECTION FOR LOW-RESOURCE STT AND KWS
Franco, Horacio	(pg. 317) R1.8: TIME-FREQUENCY CONVOLUTIONAL NETWORKS FOR ROBUST SPEECH RECOGNITION (pg. 525) T1.3: IMPROVING ROBUSTNESS AGAINST REVERBERATION FOR AUTOMATIC SPEECH RECOGNITION
Fujimoto, Masakiyo	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Fujita, Yusuke	(pg. 416) T2.3: UNIFIED ASR SYSTEM USING LGM-BASED SOURCE SEPARATION, NOISE-ROBUST FEATURE EXTRACTION, AND WORD HYPOTHESIS SELECTION

G

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Ga Ge Gh Gi Gl Go Gr Gu

Gales, Mark J. F.	(pg. 160) M3.6: STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES (pg. 181) M3.9: INVESTIGATION OF BACK-OFF BASED INTERPOLATION BETWEEN RECURRENT NEURAL NETWORK AND N-GRAM LANGUAGE MODELS (pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH (pg. 617) T3.10: IMPROVING THE INTERPRETABILITY OF DEEP NEURAL NETWORKS WITH STIMULATED LEARNING (pg. 639) T4.3: CAMBRIDGE UNIVERSITY TRANSCRIPTION SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 647) T4.4: THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY ALIGNMENT SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 660) T4.6: SPEAKER DIARISATION AND LONGITUDINAL LINKING IN MULTI-GENRE BROADCAST DATA (pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Gangashetty, Suryakanth	(pg. 111) M2.3: LEARNING CONTINUOUS REPRESENTATION OF TEXT FOR PHONE DURATION MODELING IN STATISTICAL PARAMETRIC SPEECH SYNTHESIS
Garcia-Mateo, Carmen	(pg. 223) M4.5: PHONETIC UNIT SELECTION FOR CROSS-LINGUAL QUERY-BY-EXAMPLE SPOKEN TERM DETECTION
Garcia-Romero, Daniel	(pg. 92) M1.14: TIME DELAY DEEP NEURAL NETWORK-BASED UNIVERSAL BACKGROUND MODELS FOR SPEAKER RECOGNITION
Gasic, Milica	(pg. 763) W2.2: MULTI-DOMAIN DIALOGUE SUCCESS CLASSIFIERS FOR POLICY TRAINING (pg. 806) W2.8: POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN DIALOGUE SYSTEMS
Gauvain, Jean-Luc	(pg. 153) M3.5: IMPROVING DATA SELECTION FOR LOW-RESOURCE STT AND KWS
Gerlach, Stephan	(pg. 468) T2.10: A CHIME-3 CHALLENGE SYSTEM: LONG-TERM ACOUSTIC FEATURES FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION
Ghanem, Abdurrahman	(Demo) W1.4: LAHAJET: A GAME FOR CLASSIFYING DIALECTAL ARABIC SPEECH
Gimpel, Kevin	(pg. 561) T3.2: DISCRIMINATIVE SEGMENTAL CASCADES FOR FEATURE-RICH PHONE RECOGNITION
Glass, James	(pg. 237) M4.7: DEEP MULTIMODAL SEMANTIC EMBEDDINGS FOR SPEECH AND IMAGES
Glass, Michael	(pg. 813) W2.9: APPLYING DEEP LEARNING TO ANSWER SELECTION: A STUDY AND AN OPEN TASK
Glaude, Hadrien	(pg. 71) M1.11: SPECTRAL LEARNING WITH NON NEGATIVE PROBABILITIES FOR FINITE STATE AUTOMATON
Goetze, Stefan	(pg. 468) T2.10: A CHIME-3 CHALLENGE SYSTEM: LONG-TERM ACOUSTIC FEATURES FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION
Golik, Pavel	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH (pg. 596) T3.7: SPEAKER ADAPTIVE JOINT TRAINING OF GAUSSIAN MIXTURE MODELS AND BOTTLENECK FEATURES
Gong, Yifan	(pg. 187) M3.10: LSTM TIME AND FREQUENCY RECURRENCE FOR AUTOMATIC SPEECH RECOGNITION
Gowayyed, Mohammad	(pg. 167) M3.7: EESEN: END-TO-END SPEECH RECOGNITION USING DEEP RNN MODELS AND WFST-BASED DECODING
Graciarena, Martin	(pg. 525) T1.3: IMPROVING ROBUSTNESS AGAINST REVERBERATION FOR AUTOMATIC SPEECH RECOGNITION
Gretter, Roberto	(pg. 275) R1.2: THE DIRHA-ENGLISH CORPUS AND RELATED TASKS FOR DISTANT-SPEECH RECOGNITION IN DOMESTIC ENVIRONMENTS
Grezl, Frantisek	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Gupta, Vishwa	(pg. 681) T4.9: CRIM AND LIUM APPROACHES FOR MULTI-GENRE BROADCAST MEDIA TRANSCRIPTION

H

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Ha He Hi Ho Hs Hu Hw

Haeb-Umbach, Reinhold	(pg. 444) T2.7: BLSTM SUPPORTED GEV BEAMFORMER FRONT-END FOR THE 3RD CHIME CHALLENGE
Hagmüller, Martin	(pg. 452) T2.8: MULTI-CHANNEL SPEECH PROCESSING ARCHITECTURES FOR NOISE ROBUST SPEECH RECOGNITION: 3RD CHIME CHALLENGE RESULTS
Hain, Thomas	(pg. 130) M3.2: LATENT DIRICHLET ALLOCATION BASED ORGANISATION OF BROADCAST MEDIA ARCHIVES FOR DEEP NEURAL NETWORK ADAPTATION (pg. 624) T4.1: THE 2015 SHEFFIELD SYSTEM FOR TRANSCRIPTION OF MULTI-GENRE BROADCAST MEDIA (pg. 632) T4.2: THE 2015 SHEFFIELD SYSTEM FOR LONGITUDINAL DIARISATION OF BROADCAST MEDIA (pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Hakkani-Tur, Dilek	(pg. 361) R2.3: A UNIVERSAL MODEL FOR FLEXIBLE ITEM SELECTION IN CONVERSATIONAL DIALOGS (pg. 375) R2.5: DETECTING ACTIONABLE ITEMS IN MEETINGS BY CONVOLUTIONAL DEEP STRUCTURED SEMANTIC MODELS
Hakouz, Waed	(Demo) W1.4: LAHAJET: A GAME FOR CLASSIFYING DIALECTAL ARABIC SPEECH
Hamidi Ghalehjegh, Sina	(pg. 555) T3.1: DEEP BOTTLENECK FEATURES FOR I-VECTOR BASED TEXT-INDEPENDENT SPEAKER VERIFICATION
Han, Sangdo	(pg. 771) W2.3: OPEN-DOMAIN PERSONALIZED DIALOG SYSTEM USING USER-INTERESTED TOPICS IN SYSTEM RESPONSES
Hansen, John H. L.	(pg. 331) R1.10: AN I-VECTOR PLDA BASED GENDER IDENTIFICATION APPROACH FOR SEVERELY DISTORTED AND MULTILINGUAL DARPA RATS DATA
Harper, Mary	(pg. 547) T1.6: THE AUTOMATIC SPEECH RECOGITION IN REVERBERANT ENVIRONMENTS (ASPIRE) CHALLENGE
Hartmann, William	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Harwath, David	(pg. 237) M4.7: DEEP MULTIMODAL SEMANTIC EMBEDDINGS FOR SPEECH AND IMAGES
Hasan, Madina	(pg. 624) T4.1: THE 2015 SHEFFIELD SYSTEM FOR TRANSCRIPTION OF MULTI-GENRE BROADCAST MEDIA
He, Xiaodong	(pg. 375) R2.5: DETECTING ACTIONABLE ITEMS IN MEETINGS BY CONVOLUTIONAL DEEP STRUCTURED SEMANTIC MODELS
He, Yanzhang	(pg. 496) T2.14: COMBINING SPECTRAL FEATURE MAPPING AND MULTI-CHANNEL MODEL-BASED SOURCE SEPARATION FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION
Heck, Michael	(pg. 654) T4.5: THE NAIST ASR SYSTEM FOR THE 2015 MULTI-GENRE BROADCAST CHALLENGE: ON COMBINATION OF DEEP LEARNING SYSTEMS USING A RANK-SCORE FUNCTION
Hermansky, Hynek	(pg. 283) R1.3: UNCERTAINTY ESTIMATION OF DNN CLASSIFIERS (pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Hershey, John	(pg. 475) T2.11: THE MERL/SRI SYSTEM FOR THE 3RD CHIME CHALLENGE USING BEAMFORMING, ROBUST FEATURE EXTRACTION, AND ADVANCED SPEECH RECOGNITION
Heymann, Jahn	(pg. 444) T2.7: BLSTM SUPPORTED GEV BEAMFORMER FRONT-END FOR THE 3RD CHIME CHALLENGE
Higuchi, Takuya	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Himawan, Ivan	(pg. 289) R1.4: TOWARDS UTTERANCE-BASED NEURAL NETWORK ADAPTATION IN ACOUSTIC MODELING
Homma, Takeshi	(pg. 416) T2.3: UNIFIED ASR SYSTEM USING LGM-BASED SOURCE SEPARATION, NOISE-ROBUST FEATURE EXTRACTION, AND WORD HYPOTHESIS SELECTION
Hori, Takaaki	(pg. 475) T2.11: THE MERL/SRI SYSTEM FOR THE 3RD CHIME CHALLENGE USING BEAMFORMING, ROBUST FEATURE EXTRACTION, AND ADVANCED SPEECH RECOGNITION
Hsiao, Roger	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Hui, Like	(pg. 215) M4.4: HIGH-PERFORMANCE SWAHILI KEYWORD SEARCH WITH VERY LIMITED LANGUAGE PACK: THE THUEE SYSTEM FOR THE OPENKWS15 EVALUATION (pg. 230) M4.6: IMPROVED SYSTEM FUSION FOR KEYWORD SEARCH
Hwang, Mei-Yuh	(pg. 353) R2.2: SEMI-SUPERVISED SLOT TAGGING IN SPOKEN LANGUAGE UNDERSTANDING USING RECURRENT TRANSDUCTIVE SUPPORT VECTOR MACHINES

I

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Ik Il It Iv

Ikeshita, Rintaro	(pg. 416) T2.3: UNIFIED ASR SYSTEM USING LGM-BASED SOURCE SEPARATION, NOISE-ROBUST FEATURE EXTRACTION, AND WORD HYPOTHESIS SELECTION
Ilham, Faiz	(pg. 252) M4.9: INCREMENTAL SENTENCE COMPRESSION USING LSTM RECURRENT NETWORKS
Illina, Irina	(pg. 1) M1.1: DIFFERENT WORD REPRESENTATIONS AND THEIR COMBINATION FOR PROPER NAME RETRIEVAL FROM DIACHRONIC DOCUMENTS (pg. 482) T2.12: ROBUST ASR USING NEURAL NETWORK BASED SPEECH ENHANCEMENT AND FEATURE SIMULATION
Ito, Nobutaka	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Ivanov, Alexei V.	(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH (Demo) W1.7: A MODULAR OPEN-SOURCE STANDARD-COMPLIANT DIALOG SYSTEM FRAMEWORK WITH VIDEO SUPPORT (Demo) W1.9: FAST AND POWER EFFICIENT HARDWARE-ACCELERATED CLOUD-BASED ASR FOR REMOTE DIALOG APPLICATIONS

J

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Ja Je Ji Jo Ju

Jalalvand, Shahab	(pg. 409) T2.2: BOOSTED ACOUSTIC MODEL LEARNING AND HYPOTHESES RESCORING ON THE CHIME-3 TASK
Jett, Kevin	(pg. 192) M4.1: INCORPORATING USER FEEDBACK TO RE-RANK KEYWORD SEARCH RESULTS
Ji, Heng	(pg. 324) R1.9: NAME-AWARE LANGUAGE MODEL ADAPTATION AND SPARSE FEATURES FOR STATISTICAL MACHINE TRANSLATION
Jones, Douglas L.	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Jurcicek, Filip	(pg. 757) W2.1: INCREMENTAL LSTM-BASED DIALOG STATE TRACKER

K

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Ka Kh Ki Kn Ko

Kanda, Naoyuki	(pg. 15) M1.3: TRAINING DATA PSEUDO-SHUFFLING AND DIRECT DECODING FRAMEWORK FOR RECURRENT NEURAL NETWORK BASED ACOUSTIC MODELING
Kang, Jian	(pg. 215) M4.4: HIGH-PERFORMANCE SWAHILI KEYWORD SEARCH WITH VERY LIMITED LANGUAGE PACK: THE THUEE SYSTEM FOR THE OPENKWS15 EVALUATION (pg. 230) M4.6: IMPROVED SYSTEM FUSION FOR KEYWORD SEARCH
Karafiat, Martin	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Karanasou, Penny	(pg. 639) T4.3: CAMBRIDGE UNIVERSITY TRANSCRIPTION SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 647) T4.4: THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY ALIGNMENT SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 660) T4.6: SPEAKER DIARISATION AND LONGITUDINAL LINKING IN MULTI-GENRE BROADCAST DATA
Kawaguchi, Yohei	(pg. 416) T2.3: UNIFIED ASR SYSTEM USING LGM-BASED SOURCE SEPARATION, NOISE-ROBUST FEATURE EXTRACTION, AND WORD HYPOTHESIS SELECTION
Kawai, Hisashi	(pg. 15) M1.3: TRAINING DATA PSEUDO-SHUFFLING AND DIRECT DECODING FRAMEWORK FOR RECURRENT NEURAL NETWORK BASED ACOUSTIC MODELING
Khudanpur, Sanjeev	(pg. 539) T1.5: JHU ASPIRE SYSTEM : ROBUST LVCSR WITH TDNNS, IVECTOR ADAPTATION AND RNN-LMS
Kilgour, Jonathan	(pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Kimball, Owen	(pg. 192) M4.1: INCORPORATING USER FEEDBACK TO RE-RANK KEYWORD SEARCH RESULTS
Kingsbury, Brian	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Kinoshita, Keisuke	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Kirchhoff, Katrin	(pg. 581) T3.5: ACOUSTIC MODELING WITH NEURAL GRAPH EMBEDDINGS
Kislal, Ellen	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Kizuki, Hideaki	(pg. 784) W2.5: ADAPTIVE SELECTION FROM MULTIPLE RESPONSE CANDIDATES IN EXAMPLE-BASED DIALOGUE
Knill, Kate M.	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Ko, Tom	(pg. 539) T1.5: JHU ASPIRE SYSTEM : ROBUST LVCSR WITH TDNNS, IVECTOR ADAPTATION AND RNN-LMS
Kollmeier, Birger	(pg. 468) T2.10: A CHIME-3 CHALLENGE SYSTEM: LONG-TERM ACOUSTIC FEATURES FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION
Komatani, Kazunori	(pg. 52) M1.8: ACOUSTIC MODEL TRAINING BASED ON NODE-WISE WEIGHT BOUNDARY MODEL INCREASING SPEED OF DISCRETE NEURAL NETWORKS
Koo, Sangjun	(pg. 798) W2.7: IMPLEMENTATION OF GENERIC POSITIVE-NEGATIVE TRACKER IN EXTENSIBLE DIALOG SYSTEM
Korenevsky, Maxim	(pg. 401) T2.1: ADAPTIVE BEAMFORMING AND ADAPTIVE TRAINING OF DNN ACOUSTIC MODELS FOR ENHANCED MULTICHANNEL NOISY SPEECH RECOGNITION

L

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La Le Li Ll Lo Lu Lv

Lahiri, Abhik	(pg. 45) M1.7: DISCRIMINATIVE TRAINING OF CONTEXT-DEPENDENT LANGUAGE MODEL SCALING FACTORS AND INTERPOLATION WEIGHTS
Lamel, Lori	(pg. 153) M3.5: IMPROVING DATA SELECTION FOR LOW-RESOURCE STT AND KWS
Lanchantin, Pierre	(pg. 639) T4.3: CAMBRIDGE UNIVERSITY TRANSCRIPTION SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 647) T4.4: THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY ALIGNMENT SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 660) T4.6: SPEAKER DIARISATION AND LONGITUDINAL LINKING IN MULTI-GENRE BROADCAST DATA (pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Lange, Patrick	(Demo) W1.7: A MODULAR OPEN-SOURCE STANDARD-COMPLIANT DIALOG SYSTEM FRAMEWORK WITH VIDEO SUPPORT
Lange, Patrick L.	(Demo) W1.9: FAST AND POWER EFFICIENT HARDWARE-ACCELERATED CLOUD-BASED ASR FOR REMOTE DIALOG APPLICATIONS
Laurent, Antoine	(pg. 153) M3.5: IMPROVING DATA SELECTION FOR LOW-RESOURCE STT AND KWS
Le Roux, Jonathan	(pg. 475) T2.11: THE MERL/SRI SYSTEM FOR THE 3RD CHIME CHALLENGE USING BEAMFORMING, ROBUST FEATURE EXTRACTION, AND ADVANCED SPEECH RECOGNITION
Le, Viet Bac	(pg. 153) M3.5: IMPROVING DATA SELECTION FOR LOW-RESOURCE STT AND KWS
Lecouteux, Benjamin	(pg. 267) R1.1: SPOKEN LANGUAGE TRANSLATION GRAPHS RE-DECODING USING AUTOMATIC QUALITY ASSESSMENT
Lee, Chin-Hui	(pg. 430) T2.5: AN INFORMATION FUSION APPROACH TO RECOGNIZING MICROPHONE ARRAY SPEECH IN THE CHIME-3 CHALLENGE BASED ON A DEEP LEARNING FRAMEWORK
Lee, Gary Geunbae	(pg. 771) W2.3: OPEN-DOMAIN PERSONALIZED DIALOG SYSTEM USING USER-INTERESTED TOPICS IN SYSTEM RESPONSES (pg. 798) W2.7: IMPLEMENTATION OF GENERIC POSITIVE-NEGATIVE TRACKER IN EXTENSIBLE DIALOG SYSTEM
Lee, Hoshik	(pg. 65) M1.10: RNNDROP: A NOVEL DROPOUT FOR RNNS IN ASR
Lee, Hung-yi	(pg. 84) M1.13: PERSONALIZING UNIVERSAL RECURRENT NEURAL NETWORK LANGUAGE MODEL WITH USER CHARACTERISTIC FEATURES BY SOCIAL NETWORK CROWDSOURCING
Lee, Hung-Yi	(pg. 137) M3.3: TOWARDS STRUCTURED DEEP NEURAL NETWORK FOR AUTOMATIC SPEECH RECOGNITION
Lee, Hung-yi	(pg. 245) M4.8: AN ITERATIVE DEEP LEARNING FRAMEWORK FOR UNSUPERVISED DISCOVERY OF SPEECH FEATURES AND LINGUISTIC UNITS WITH APPLICATIONS ON SPOKEN TERM DETECTION
Lee, Kyusong	(pg. 771) W2.3: OPEN-DOMAIN PERSONALIZED DIALOG SYSTEM USING USER-INTERESTED TOPICS IN SYSTEM RESPONSES
Lee, Lin-Shan	(pg. 84) M1.13: PERSONALIZING UNIVERSAL RECURRENT NEURAL NETWORK LANGUAGE MODEL WITH USER CHARACTERISTIC FEATURES BY SOCIAL NETWORK CROWDSOURCING
Lee, Lin-shan	(pg. 137) M3.3: TOWARDS STRUCTURED DEEP NEURAL NETWORK FOR AUTOMATIC SPEECH RECOGNITION (pg. 245) M4.8: AN ITERATIVE DEEP LEARNING FRAMEWORK FOR UNSUPERVISED DISCOVERY OF SPEECH FEATURES AND LINGUISTIC UNITS WITH APPLICATIONS ON SPOKEN TERM DETECTION
Levit, Michael	(pg. 45) M1.7: DISCRIMINATIVE TRAINING OF CONTEXT-DEPENDENT LANGUAGE MODEL SCALING FACTORS AND INTERPOLATION WEIGHTS
Li, Haibo	(pg. 324) R1.9: NAME-AWARE LANGUAGE MODEL ADAPTATION AND SPARSE FEATURES FOR STATISTICAL MACHINE TRANSLATION
Li, Haizhou	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Li, Jinyu	(pg. 187) M3.10: LSTM TIME AND FREQUENCY RECURRENCE FOR AUTOMATIC SPEECH RECOGNITION
Li, Xin	(pg. 59) M1.9: TWO-STAGE ASGD FRAMEWORK FOR PARALLEL TRAINING OF DNN ACOUSTIC MODELS USING ETHERNET
Liao, Yi-Hsiu	(pg. 137) M3.3: TOWARDS STRUCTURED DEEP NEURAL NETWORK FOR AUTOMATIC SPEECH RECOGNITION
Linarès, Georges	(pg. 346) R2.1: TOPIC-SPACE BASED SETUP OF A NEURAL NETWORK FOR THEME IDENTIFICATION OF HIGHLY IMPERFECT TRANSCRIPTIONS
Liss, Julie	(pg. 569) T3.3: HILBERT SPECTRAL ANALYSIS OF VOWELS USING INTRINSIC MODE FUNCTIONS
Liu, Chia-Hsiang	(pg. 245) M4.8: AN ITERATIVE DEEP LEARNING FRAMEWORK FOR UNSUPERVISED DISCOVERY OF SPEECH FEATURES AND LINGUISTIC UNITS WITH APPLICATIONS ON SPOKEN TERM DETECTION
Liu, Gang	(pg. 331) R1.10: AN I-VECTOR PLDA BASED GENDER IDENTIFICATION APPROACH FOR SEVERELY DISTORTED AND MULTILINGUAL DARPA RATS DATA
Liu, Jia	(pg. 215) M4.4: HIGH-PERFORMANCE SWAHILI KEYWORD SEARCH WITH VERY LIMITED LANGUAGE PACK: THE THUEE SYSTEM FOR THE OPENKWS15 EVALUATION (pg. 230) M4.6: IMPROVED SYSTEM FUSION FOR KEYWORD SEARCH
Liu, Shih-Hung	(pg. 207) M4.3: INCORPORATING PARAGRAPH EMBEDDINGS AND DENSITY PEAKS CLUSTERING FOR SPOKEN DOCUMENT SUMMARIZATION
Liu, Xiaohu	(pg. 397) R2.8: NATURAL LANGUAGE UNDERSTANDING FOR PARTIAL QUERIES
Liu, Xunying	(pg. 181) M3.9: INVESTIGATION OF BACK-OFF BASED INTERPOLATION BETWEEN RECURRENT NEURAL NETWORK AND N-GRAM LANGUAGE MODELS (pg. 639) T4.3: CAMBRIDGE UNIVERSITY TRANSCRIPTION SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 647) T4.4: THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY ALIGNMENT SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 660) T4.6: SPEAKER DIARISATION AND LONGITUDINAL LINKING IN MULTI-GENRE BROADCAST DATA (pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Liu, Yang	(pg. 98) M2.1: AUTOMATIC PROSODY PREDICTION FOR CHINESE SPEECH SYNTHESIS USING BLSTM-RNN AND EMBEDDING FEATURES
Liu, Yulan	(pg. 624) T4.1: THE 2015 SHEFFIELD SYSTEM FOR TRANSCRIPTION OF MULTI-GENRE BROADCAST MEDIA
Liu, Yuzong	(pg. 581) T3.5: ACOUSTIC MODELING WITH NEURAL GRAPH EMBEDDINGS
Liutkus, Antoine	(pg. 482) T2.12: ROBUST ASR USING NEURAL NETWORK BASED SPEECH ENHANCEMENT AND FEATURE SIMULATION
Livescu, Karen	(pg. 561) T3.2: DISCRIMINATIVE SEGMENTAL CASCADES FOR FEATURE-RICH PHONE RECOGNITION
Lleida, Eduardo	(pg. 667) T4.7: VARIATIONAL BAYESIAN PLDA FOR SPEAKER DIARIZATION IN THE MGB CHALLENGE
Lopez-Otero, Paula	(pg. 223) M4.5: PHONETIC UNIT SELECTION FOR CROSS-LINGUAL QUERY-BY-EXAMPLE SPOKEN TERM DETECTION
Lu, Cheng	(pg. 215) M4.4: HIGH-PERFORMANCE SWAHILI KEYWORD SEARCH WITH VERY LIMITED LANGUAGE PACK: THE THUEE SYSTEM FOR THE OPENKWS15 EVALUATION (pg. 230) M4.6: IMPROVED SYSTEM FUSION FOR KEYWORD SEARCH
Lu, Hsiang-Hung	(pg. 245) M4.8: AN ITERATIVE DEEP LEARNING FRAMEWORK FOR UNSUPERVISED DISCOVERY OF SPEECH FEATURES AND LINGUISTIC UNITS WITH APPLICATIONS ON SPOKEN TERM DETECTION
Lu, Xugang	(pg. 15) M1.3: TRAINING DATA PSEUDO-SHUFFLING AND DIRECT DECODING FRAMEWORK FOR RECURRENT NEURAL NETWORK BASED ACOUSTIC MODELING
Lubis, Nurul	(pg. 777) W2.4: A STUDY OF SOCIAL-AFFECTIVE COMMUNICATION: AUTOMATIC PREDICTION OF EMOTION TRIGGERS AND RESPONSES IN TELEVISION TALK SHOWS
Lubold, Nichola	(pg. 103) M2.2: NATURALNESS AND RAPPORT IN A PITCH ADAPTIVE LEARNING COMPANION
Luong, Ngoc-Quang	(pg. 267) R1.1: SPOKEN LANGUAGE TRANSLATION GRAPHS RE-DECODING USING AUTOMATIC QUALITY ASSESSMENT
Lv, Zhiqiang	(pg. 215) M4.4: HIGH-PERFORMANCE SWAHILI KEYWORD SEARCH WITH VERY LIMITED LANGUAGE PACK: THE THUEE SYSTEM FOR THE OPENKWS15 EVALUATION (pg. 230) M4.6: IMPROVED SYSTEM FUSION FOR KEYWORD SEARCH

M

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Ma Mc Me Mi Mo Mr Mu

Ma, Jeff	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Ma, Ning	(pg. 490) T2.13: EXPLOITING SYNCHRONY SPECTRA AND DEEP NEURAL NETWORKS FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION
Madikeri, Srikanth	(pg. 289) R1.4: TOWARDS UTTERANCE-BASED NEURAL NETWORK ADAPTATION IN ACOUSTIC MODELING
Magdy, Walid	(pg. 576) T3.4: MULTI-REFERENCE WER FOR EVALUATING ASR FOR LANGUAGES WITH NO ORTHOGRAPHIC RULES
Mallidi, Sri Harish	(pg. 283) R1.3: UNCERTAINTY ESTIMATION OF DNN CLASSIFIERS (pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Malyska, Nicolas	(pg. 512) T1.1: ANALYSIS OF FACTORS AFFECTING SYSTEM PERFORMANCE IN THE ASPIRE CHALLENGE
Mandel, Michael	(pg. 496) T2.14: COMBINING SPECTRAL FEATURE MAPPING AND MULTI-CHANNEL MODEL-BASED SOURCE SEPARATION FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION
Mangu, Lidia	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Manohar, Vimal	(pg. 539) T1.5: JHU ASPIRE SYSTEM : ROBUST LVCSR WITH TDNNS, IVECTOR ADAPTATION AND RNN-LMS
Marius, Tamas	(Demo) W1.1: NETPROF IOS PRONUNCIATION FEEDBACK DEMONSTRATION
Martin, Lara J.	(pg. 303) R1.6: UTTERANCE CLASSIFICATION IN SPEECH-TO-SPEECH TRANSLATION FOR ZERO-RESOURCE LANGUAGES IN THE HOSPITAL ADMINISTRATION DOMAIN
Marxer, Ricard	(pg. 490) T2.13: EXPLOITING SYNCHRONY SPECTRA AND DEEP NEURAL NETWORKS FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION (pg. 504) T2.15: THE THIRD `CHIME' SPEECH SEPARATION AND RECOGNITION CHALLENGE: DATASET, TASK AND BASELINES
Matassoni, Marco	(pg. 409) T2.2: BOOSTED ACOUSTIC MODEL LEARNING AND HYPOTHESES RESCORING ON THE CHIME-3 TASK
McLaren, Mitchell	(pg. 525) T1.3: IMPROVING ROBUSTNESS AGAINST REVERBERATION FOR AUTOMATIC SPEECH RECOGNITION
McParland, Andrew	(pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Meignier, Sylvain	(pg. 681) T4.9: CRIM AND LIUM APPROACHES FOR MULTI-GENRE BROADCAST MEDIA TRANSCRIPTION
Melot, Jennifer	(pg. 512) T1.1: ANALYSIS OF FACTORS AFFECTING SYSTEM PERFORMANCE IN THE ASPIRE CHALLENGE (Demo) W1.1: NETPROF IOS PRONUNCIATION FEEDBACK DEMONSTRATION
Messaoudi, Abdel	(pg. 153) M3.5: IMPROVING DATA SELECTION FOR LOW-RESOURCE STT AND KWS
Metze, Florian	(pg. 167) M3.7: EESEN: END-TO-END SPEECH RECOGNITION USING DEEP RNN MODELS AND WFST-BASED DECODING
Miao, Yajie	(pg. 167) M3.7: EESEN: END-TO-END SPEECH RECOGNITION USING DEEP RNN MODELS AND WFST-BASED DECODING
Miguel, Antonio	(pg. 667) T4.7: VARIATIONAL BAYESIAN PLDA FOR SPEAKER DIARIZATION IN THE MGB CHALLENGE
Milner, Rosanna	(pg. 624) T4.1: THE 2015 SHEFFIELD SYSTEM FOR TRANSCRIPTION OF MULTI-GENRE BROADCAST MEDIA (pg. 632) T4.2: THE 2015 SHEFFIELD SYSTEM FOR LONGITUDINAL DIARISATION OF BROADCAST MEDIA
Miryala, Sai Sumanth	(pg. 303) R1.6: UTTERANCE CLASSIFICATION IN SPEECH-TO-SPEECH TRANSLATION FOR ZERO-RESOURCE LANGUAGES IN THE HOSPITAL ADMINISTRATION DOMAIN
Mitra, Vikramjit	(pg. 317) R1.8: TIME-FREQUENCY CONVOLUTIONAL NETWORKS FOR ROBUST SPEECH RECOGNITION (pg. 475) T2.11: THE MERL/SRI SYSTEM FOR THE 3RD CHIME CHALLENGE USING BEAMFORMING, ROBUST FEATURE EXTRACTION, AND ADVANCED SPEECH RECOGNITION (pg. 525) T1.3: IMPROVING ROBUSTNESS AGAINST REVERBERATION FOR AUTOMATIC SPEECH RECOGNITION
Mizukami, Masahiro	(pg. 784) W2.5: ADAPTIVE SELECTION FROM MULTIPLE RESPONSE CANDIDATES IN EXAMPLE-BASED DIALOGUE
Mohamed, Abdel-Rahman	(pg. 78) M1.12: DEEP BI-DIRECTIONAL RECURRENT NETWORKS OVER SPECTRAL WINDOWS (pg. 187) M3.10: LSTM TIME AND FREQUENCY RECURRENCE FOR AUTOMATIC SPEECH RECOGNITION
Moon, Taesup	(pg. 65) M1.10: RNNDROP: A NOVEL DROPOUT FOR RNNS IN ASR
Morales-Cordovilla, Juan A.	(pg. 482) T2.12: ROBUST ASR USING NEURAL NETWORK BASED SPEECH ENHANCEMENT AND FEATURE SIMULATION
Morchid, Mohamed	(pg. 346) R2.1: TOPIC-SPACE BASED SETUP OF A NEURAL NETWORK FOR THEME IDENTIFICATION OF HIGHLY IMPERFECT TRANSCRIPTIONS
Moritz, Niko	(pg. 468) T2.10: A CHIME-3 CHALLENGE SYSTEM: LONG-TERM ACOUSTIC FEATURES FOR NOISE ROBUST AUTOMATIC SPEECH RECOGNITION
Moriya, Takafumi	(pg. 610) T3.9: AUTOMATION OF SYSTEM BUILDING FOR STATE-OF-THE-ART LARGE VOCABULARY SPEECH RECOGNITION USING EVOLUTION STRATEGY
Motlicek, Petr	(pg. 289) R1.4: TOWARDS UTTERANCE-BASED NEURAL NETWORK ADAPTATION IN ACOUSTIC MODELING
Mrksic, Nikola	(pg. 763) W2.2: MULTI-DOMAIN DIALOGUE SUCCESS CLASSIFIERS FOR POLICY TRAINING (pg. 806) W2.8: POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN DIALOGUE SYSTEMS
Mundkowsky, Robert	(Demo) W1.7: A MODULAR OPEN-SOURCE STANDARD-COMPLIANT DIALOG SYSTEM FRAMEWORK WITH VIDEO SUPPORT

N

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Na Ne Ng No Nu

Na, Xingyu	(pg. 59) M1.9: TWO-STAGE ASGD FRAMEWORK FOR PARALLEL TRAINING OF DNN ACOUSTIC MODELS USING ETHERNET
Nakadai, Kazuhiro	(pg. 52) M1.8: ACOUSTIC MODEL TRAINING BASED ON NODE-WISE WEIGHT BOUNDARY MODEL INCREASING SPEED OF DISCRETE NEURAL NETWORKS
Nakagawa, Seiichi	(pg. 200) M4.2: COMBINATION OF SYLLABLE BASED N-GRAM SEARCH AND WORD SEARCH FOR SPOKEN TERM DETECTION THROUGH SPOKEN QUERIES AND IV/OOV CLASSIFICATION
Nakamura, Satoshi	(pg. 175) M3.8: STOCHASTIC GRADIENT VARIATIONAL BAYES FOR DEEP LEARNING-BASED ASR (pg. 252) M4.9: INCREMENTAL SENTENCE COMPRESSION USING LSTM RECURRENT NETWORKS (pg. 654) T4.5: THE NAIST ASR SYSTEM FOR THE 2015 MULTI-GENRE BROADCAST CHALLENGE: ON COMBINATION OF DEEP LEARNING SYSTEMS USING A RANK-SCORE FUNCTION (pg. 777) W2.4: A STUDY OF SOCIAL-AFFECTIVE COMMUNICATION: AUTOMATIC PREDICTION OF EMOTION TRIGGERS AND RESPONSES IN TELEVISION TALK SHOWS (pg. 784) W2.5: ADAPTIVE SELECTION FROM MULTIPLE RESPONSE CANDIDATES IN EXAMPLE-BASED DIALOGUE
Nakatani, Tomohiro	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Narayanan, Arun	(pg. 30) M1.5: SPEAKER LOCATION AND MICROPHONE SPACING INVARIANT ACOUSTIC MODELING FROM RAW MULTICHANNEL WAVEFORMS
Neubig, Graham	(pg. 252) M4.9: INCREMENTAL SENTENCE COMPRESSION USING LSTM RECURRENT NETWORKS (pg. 654) T4.5: THE NAIST ASR SYSTEM FOR THE 2015 MULTI-GENRE BROADCAST CHALLENGE: ON COMBINATION OF DEEP LEARNING SYSTEMS USING A RANK-SCORE FUNCTION (pg. 777) W2.4: A STUDY OF SOCIAL-AFFECTIVE COMMUNICATION: AUTOMATIC PREDICTION OF EMOTION TRIGGERS AND RESPONSES IN TELEVISION TALK SHOWS (pg. 784) W2.5: ADAPTIVE SELECTION FROM MULTIPLE RESPONSE CANDIDATES IN EXAMPLE-BASED DIALOGUE
Ney, Hermann	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH (pg. 596) T3.7: SPEAKER ADAPTIVE JOINT TRAINING OF GAUSSIAN MIXTURE MODELS AND BOTTLENECK FEATURES
Ng, Raymond W. M.	(pg. 130) M3.2: LATENT DIRICHLET ALLOCATION BASED ORGANISATION OF BROADCAST MEDIA ARCHIVES FOR DEEP NEURAL NETWORK ADAPTATION (pg. 624) T4.1: THE 2015 SHEFFIELD SYSTEM FOR TRANSCRIPTION OF MULTI-GENRE BROADCAST MEDIA (pg. 632) T4.2: THE 2015 SHEFFIELD SYSTEM FOR LONGITUDINAL DIARISATION OF BROADCAST MEDIA
Ngoc-Tien, Le	(pg. 267) R1.1: SPOKEN LANGUAGE TRANSLATION GRAPHS RE-DECODING USING AUTOMATIC QUALITY ASSESSMENT
Nguyen, Thi Ngoc Tho	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Nomura, Toshio	(pg. 784) W2.5: ADAPTIVE SELECTION FROM MULTIPLE RESPONSE CANDIDATES IN EXAMPLE-BASED DIALOGUE
Novotney, Scott	(pg. 192) M4.1: INCORPORATING USER FEEDBACK TO RE-RANK KEYWORD SEARCH RESULTS
Nugraha, Aditya Arie	(pg. 482) T2.12: ROBUST ASR USING NEURAL NETWORK BASED SPEECH ENHANCEMENT AND FEATURE SIMULATION
Nussbaum-Thom, Markus	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH

O

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Og Om Or

Ogawa, Atsunori	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Ogawa, Tetsuji	(pg. 283) R1.3: UNCERTAINTY ESTIMATION OF DNN CLASSIFIERS
Oguz, Barlas	(pg. 45) M1.7: DISCRIMINATIVE TRAINING OF CONTEXT-DEPENDENT LANGUAGE MODEL SCALING FACTORS AND INTERPOLATION WEIGHTS
Omologo, Maurizio	(pg. 275) R1.2: THE DIRHA-ENGLISH CORPUS AND RELATED TASKS FOR DISTANT-SPEECH RECOGNITION IN DOMESTIC ENVIRONMENTS (pg. 409) T2.2: BOOSTED ACOUSTIC MODEL LEARNING AND HYPOTHESES RESCORING ON THE CHIME-3 TASK (Demo) W1.6: THE DIRHA-ENGLISH CORPUS: AN OVERVIEW ON THE DATASET WITH THE RELATED TOOLS AND RECIPES
Ortega, Alfonso	(pg. 667) T4.7: VARIATIONAL BAYESIAN PLDA FOR SPEAKER DIARIZATION IN THE MGB CHALLENGE

P

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Pa Pe Pf Pi Pl Po Pr Pu

Pan, Jielin	(pg. 59) M1.9: TWO-STAGE ASGD FRAMEWORK FOR PARALLEL TRAINING OF DNN ACOUSTIC MODELS USING ETHERNET
Pan, Yi-Cheng	(pg. 353) R2.2: SEMI-SUPERVISED SLOT TAGGING IN SPOKEN LANGUAGE UNDERSTANDING USING RECURRENT TRANSDUCTIVE SUPPORT VECTOR MACHINES
Peddinti, Vijayaditya	(pg. 539) T1.5: JHU ASPIRE SYSTEM : ROBUST LVCSR WITH TDNNS, IVECTOR ADAPTATION AND RNN-LMS
Pellin, Marco	(pg. 275) R1.2: THE DIRHA-ENGLISH CORPUS AND RELATED TASKS FOR DISTANT-SPEECH RECOGNITION IN DOMESTIC ENVIRONMENTS
Penn, Gerald	(pg. 78) M1.12: DEEP BI-DIRECTIONAL RECURRENT NETWORKS OVER SPECTRAL WINDOWS
Pernkopf, Franz	(pg. 452) T2.8: MULTI-CHANNEL SPEECH PROCESSING ARCHITECTURES FOR NOISE ROBUST SPEECH RECOGNITION: 3RD CHIME CHALLENGE RESULTS
Pfeifenberger, Lukas	(pg. 452) T2.8: MULTI-CHANNEL SPEECH PROCESSING ARCHITECTURES FOR NOISE ROBUST SPEECH RECOGNITION: 3RD CHIME CHALLENGE RESULTS
Picheny, Michael	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Pietquin, Olivier	(pg. 71) M1.11: SPECTRAL LEARNING WITH NON NEGATIVE PROBABILITIES FOR FINITE STATE AUTOMATON
Pironkov, Gueorgui	(pg. 124) M3.1: INVESTIGATING SPARSE DEEP NEURAL NETWORKS FOR SPEECH RECOGNITION
Plummer, Andrew	(pg. 496) T2.14: COMBINING SPECTRAL FEATURE MAPPING AND MULTI-CHANNEL MODEL-BASED SOURCE SEPARATION FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION
Pon-Barry, Heather	(pg. 103) M2.2: NATURALNESS AND RAPPORT IN A PITCH ADAPTIVE LEARNING COMPANION
Povey, Daniel	(pg. 92) M1.14: TIME DELAY DEEP NEURAL NETWORK-BASED UNIVERSAL BACKGROUND MODELS FOR SPEAKER RECOGNITION (pg. 539) T1.5: JHU ASPIRE SYSTEM : ROBUST LVCSR WITH TDNNS, IVECTOR ADAPTATION AND RNN-LMS
Prudnikov, Alexey	(pg. 401) T2.1: ADAPTIVE BEAMFORMING AND ADAPTIVE TRAINING OF DNN ACOUSTIC MODELS FOR ENHANCED MULTICHANNEL NOISY SPEECH RECOGNITION
Purwarianti, Ayu	(pg. 252) M4.9: INCREMENTAL SENTENCE COMPRESSION USING LSTM RECURRENT NETWORKS

Q

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Qian, Yanmin

Qian, Yao

(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH

R

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Ra Re Ri Ro Ru Ry

Ragni, Anton	(pg. 160) M3.6: STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES (pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Rallabandi, Sai Krishna	(pg. 111) M2.3: LEARNING CONTINUOUS REPRESENTATION OF TEXT FOR PHONE DURATION MODELING IN STATISTICAL PARAMETRIC SPEECH SYNTHESIS
Rallabandi, Sai Sirisha	(pg. 111) M2.3: LEARNING CONTINUOUS REPRESENTATION OF TEXT FOR PHONE DURATION MODELING IN STATISTICAL PARAMETRIC SPEECH SYNTHESIS
Ramabhadran, Bhuvana	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Ramanarayanan, Vikram	(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH (Demo) W1.7: A MODULAR OPEN-SOURCE STANDARD-COMPLIANT DIALOG SYSTEM FRAMEWORK WITH VIDEO SUPPORT
Ranjan, Shivesh	(pg. 331) R1.10: AN I-VECTOR PLDA BASED GENDER IDENTIFICATION APPROACH FOR SEVERELY DISTORTED AND MULTILINGUAL DARPA RATS DATA
Rao, Kanishka	(pg. 604) T3.8: ACOUSTIC MODELLING WITH CD-CTC-SMBR LSTM RNNS
Ravanelli, Mirco	(pg. 275) R1.2: THE DIRHA-ENGLISH CORPUS AND RELATED TASKS FOR DISTANT-SPEECH RECOGNITION IN DOMESTIC ENVIRONMENTS (Demo) W1.6: THE DIRHA-ENGLISH CORPUS: AN OVERVIEW ON THE DATASET WITH THE RELATED TOOLS AND RECIPES
Ravuri, Suman	(pg. 37) M1.6: HYBRID DNN-LATENT STRUCTURED SVM ACOUSTIC MODELS FOR CONTINUOUS SPEECH RECOGNITION (pg. 368) R2.4: A COMPARATIVE STUDY OF NEURAL NETWORK MODELS FOR LEXICAL INTENT CLASSIFICATION
Ray, Jessica	(pg. 512) T1.1: ANALYSIS OF FACTORS AFFECTING SYSTEM PERFORMANCE IN THE ASPIRE CHALLENGE
Ren, Bo	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Ren, Hang	(pg. 791) W2.6: OPTIMIZING HUMAN-INTERPRETABLE DIALOG MANAGEMENT POLICY USING GENETIC ALGORITHM
Renals, Steve	(pg. 576) T3.4: MULTI-REFERENCE WER FOR EVALUATING ASR FOR LANGUAGES WITH NO ORTHOGRAPHIC RULES (pg. 675) T4.8: A SYSTEM FOR AUTOMATIC ALIGNMENT OF BROADCAST MEDIA CAPTIONS USING WEIGHTED FINITE-STATE TRANSDUCERS (pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Riccardi, Giuseppe	(Demo) W1.3: AUTOMATIC SUMMARIZATION OF CALL-CENTER CONVERSATIONS
Robison, Vivian	(pg. 303) R1.6: UTTERANCE CLASSIFICATION IN SPEECH-TO-SPEECH TRANSLATION FOR ZERO-RESOURCE LANGUAGES IN THE HOSPITAL ADMINISTRATION DOMAIN
Rondeau, Marc-Antoine	(pg. 390) R2.7: RECENT IMPROVEMENTS TO NEUROCRFS FOR NAMED ENTITY RECOGNITION
Rose, Richard C.	(pg. 555) T3.1: DEEP BOTTLENECK FEATURES FOR I-VECTOR BASED TEXT-INDEPENDENT SPEAKER VERIFICATION
Rousseau, Anthony	(pg. 681) T4.9: CRIM AND LIUM APPROACHES FOR MULTI-GENRE BROADCAST MEDIA TRANSCRIPTION
Rouvier, Mickael	(pg. 383) R2.6: MULTIMODAL EMBEDDING FUSION FOR ROBUST SPEAKER ROLE RECOGNITION IN VIDEO BROADCAST
Ruiz, Nicholas	(pg. 296) R1.5: PHONETICALLY-ORIENTED WORD ERROR ALIGNMENT FOR SPEECH RECOGNITION ERROR ANALYSIS IN SPEECH TRANSLATION
Rybach, David	(pg. 589) T3.6: MULTITASK LEARNING AND SYSTEM COMBINATION FOR AUTOMATIC SPEECH RECOGNITION
Ryu, Seonghan	(pg. 798) W2.7: IMPLEMENTATION OF GENERIC POSITIVE-NEGATIVE TRACKER IN EXTENSIBLE DIALOG SYSTEM

S

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Sa Sc Se Sh SI Sn So St Su Sv Sz

Sainath, Tara	(pg. 30) M1.5: SPEAKER LOCATION AND MICROPHONE SPACING INVARIANT ACOUSTIC MODELING FROM RAW MULTICHANNEL WAVEFORMS (pg. 604) T3.8: ACOUSTIC MODELLING WITH CD-CTC-SMBR LSTM RNNS
Sak, Hasim	(pg. 604) T3.8: ACOUSTIC MODELLING WITH CD-CTC-SMBR LSTM RNNS
Sakamoto, Nagisa	(pg. 200) M4.2: COMBINATION OF SYLLABLE BASED N-GRAM SEARCH AND WORD SEARCH FOR SPOKEN TERM DETECTION THROUGH SPOKEN QUERIES AND IV/OOV CLASSIFICATION
Sakti, Sakriani	(pg. 175) M3.8: STOCHASTIC GRADIENT VARIATIONAL BAYES FOR DEEP LEARNING-BASED ASR (pg. 252) M4.9: INCREMENTAL SENTENCE COMPRESSION USING LSTM RECURRENT NETWORKS (pg. 654) T4.5: THE NAIST ASR SYSTEM FOR THE 2015 MULTI-GENRE BROADCAST CHALLENGE: ON COMBINATION OF DEEP LEARNING SYSTEMS USING A RANK-SCORE FUNCTION (pg. 777) W2.4: A STUDY OF SOCIAL-AFFECTIVE COMMUNICATION: AUTOMATIC PREDICTION OF EMOTION TRIGGERS AND RESPONSES IN TELEVISION TALK SHOWS (pg. 784) W2.5: ADAPTIVE SELECTION FROM MULTIPLE RESPONSE CANDIDATES IN EXAMPLE-BASED DIALOGUE
Samarakoon, Lahiru	(pg. 145) M3.4: LEARNING FACTORIZED FEATURE TRANSFORMS FOR SPEAKER NORMALIZATION
Sandoval, Steven	(pg. 569) T3.3: HILBERT SPECTRAL ANALYSIS OF VOWELS USING INTRINSIC MODE FUNCTIONS (Demo) W1.5: VISUALIZATION OF THE HILBERT SPECTRUM
Sarikaya, Ruhi	(pg. 361) R2.3: A UNIVERSAL MODEL FOR FLEXIBLE ITEM SELECTION IN CONVERSATIONAL DIALOGS (pg. 397) R2.8: NATURAL LANGUAGE UNDERSTANDING FOR PARTIAL QUERIES
Saz, Oscar	(pg. 130) M3.2: LATENT DIRICHLET ALLOCATION BASED ORGANISATION OF BROADCAST MEDIA ARCHIVES FOR DEEP NEURAL NETWORK ADAPTATION (pg. 624) T4.1: THE 2015 SHEFFIELD SYSTEM FOR TRANSCRIPTION OF MULTI-GENRE BROADCAST MEDIA (pg. 632) T4.2: THE 2015 SHEFFIELD SYSTEM FOR LONGITUDINAL DIARISATION OF BROADCAST MEDIA (pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Schlüter, Ralf	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH (pg. 596) T3.7: SPEAKER ADAPTIVE JOINT TRAINING OF GAUSSIAN MIXTURE MODELS AND BOTTLENECK FEATURES
Schrank, Tobias	(pg. 452) T2.8: MULTI-CHANNEL SPEECH PROCESSING ARCHITECTURES FOR NOISE ROBUST SPEECH RECOGNITION: 3RD CHIME CHALLENGE RESULTS
Schwartz, Richard	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Seide, Frank	(pg. 78) M1.12: DEEP BI-DIRECTIONAL RECURRENT NETWORKS OVER SPECTRAL WINDOWS
Senior, Andrew	(pg. 30) M1.5: SPEAKER LOCATION AND MICROPHONE SPACING INVARIANT ACOUSTIC MODELING FROM RAW MULTICHANNEL WAVEFORMS (pg. 604) T3.8: ACOUSTIC MODELLING WITH CD-CTC-SMBR LSTM RNNS
Sethy, Abhinav	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Shazeer, Noam	(pg. 8) M1.2: SPARSE NON-NEGATIVE MATRIX LANGUAGE MODELING FOR GEO-ANNOTATED QUERY SESSION DATA
Shen, Wade	(pg. 512) T1.1: ANALYSIS OF FACTORS AFFECTING SYSTEM PERFORMANCE IN THE ASPIRE CHALLENGE
Shi, Yangyang	(pg. 353) R2.2: SEMI-SUPERVISED SLOT TAGGING IN SPOKEN LANGUAGE UNDERSTANDING USING RECURRENT TRANSDUCTIVE SUPPORT VECTOR MACHINES
Shih, Kai-Wun	(pg. 207) M4.3: INCORPORATING PARAGRAPH EMBEDDINGS AND DENSITY PEAKS CLUSTERING FOR SPOKEN DOCUMENT SUMMARIZATION
Shinozaki, Takahiro	(pg. 610) T3.9: AUTOMATION OF SYSTEM BUILDING FOR STATE-OF-THE-ART LARGE VOCABULARY SPEECH RECOGNITION USING EVOLUTION STRATEGY
Sim, Khe Chai	(pg. 22) M1.4: ON CONSTRUCTING AND ANALYSING AN INTERPRETABLE BRAIN MODEL FOR THE DNN BASED ON HIDDEN ACTIVITY PATTERNS
SIM, Khe Chai	(pg. 145) M3.4: LEARNING FACTORIZED FEATURE TRANSFORMS FOR SPEAKER NORMALIZATION
Sim, Khe Chai	(pg. 617) T3.10: IMPROVING THE INTERPRETABILITY OF DEEP NEURAL NETWORKS WITH STIMULATED LEARNING (Demo) W1.2: WHAT THE DNN HEARD? DISSECTING THE DNN FOR A BETTER INSIGHT
Singla, Karan	(Demo) W1.3: AUTOMATIC SUMMARIZATION OF CALL-CENTER CONVERSATIONS
Siohan, Olivier	(pg. 589) T3.6: MULTITASK LEARNING AND SYSTEM COMBINATION FOR AUTOMATIC SPEECH RECOGNITION
Sivasankaran, Sunit	(pg. 482) T2.12: ROBUST ASR USING NEURAL NETWORK BASED SPEECH ENHANCEMENT AND FEATURE SIMULATION
Snyder, David	(pg. 92) M1.14: TIME DELAY DEEP NEURAL NETWORK-BASED UNIVERSAL BACKGROUND MODELS FOR SPEAKER RECOGNITION
Song, Inchul	(pg. 65) M1.10: RNNDROP: A NOVEL DROPOUT FOR RNNS IN ASR
Sosi, Alessandro	(pg. 275) R1.2: THE DIRHA-ENGLISH CORPUS AND RELATED TASKS FOR DISTANT-SPEECH RECOGNITION IN DOMESTIC ENVIRONMENTS
Stepanov, Evgeny	(Demo) W1.3: AUTOMATIC SUMMARIZATION OF CALL-CENTER CONVERSATIONS
Stolcke, Andreas	(pg. 78) M1.12: DEEP BI-DIRECTIONAL RECURRENT NETWORKS OVER SPECTRAL WINDOWS (pg. 368) R2.4: A COMPARATIVE STUDY OF NEURAL NETWORK MODELS FOR LEXICAL INTENT CLASSIFICATION
Story, Brad H.	(Demo) W1.8: MULTI-TIME RESOLUTION ANALYSIS OF INTEGRATED ACOUSTIC INFORMATION IN REDUCED SPEECH
Su, Pei-Hao	(pg. 763) W2.2: MULTI-DOMAIN DIALOGUE SUCCESS CLASSIFIERS FOR POLICY TRAINING (pg. 806) W2.8: POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN DIALOGUE SYSTEMS
Su, Yi	(pg. 390) R2.7: RECENT IMPROVEMENTS TO NEUROCRFS FOR NAMED ENTITY RECOGNITION
Suendermann-Oeft, David	(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH (Demo) W1.7: A MODULAR OPEN-SOURCE STANDARD-COMPLIANT DIALOG SYSTEM FRAMEWORK WITH VIDEO SUPPORT (Demo) W1.9: FAST AND POWER EFFICIENT HARDWARE-ACCELERATED CLOUD-BASED ASR FOR REMOTE DIALOG APPLICATIONS
Sumiyoshi, Takashi	(pg. 416) T2.3: UNIFIED ASR SYSTEM USING LGM-BASED SOURCE SEPARATION, NOISE-ROBUST FEATURE EXTRACTION, AND WORD HYPOTHESIS SELECTION
Svaizer, Piergiorgio	(pg. 409) T2.2: BOOSTED ACOUSTIC MODEL LEARNING AND HYPOTHESES RESCORING ON THE CHIME-3 TASK
Szoke, Igor	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS

T

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Ta Tj To Tr Ts Tu

Tachimori, Mitsuyoshi	(pg. 15) M1.3: TRAINING DATA PSEUDO-SHUFFLING AND DIRECT DECODING FRAMEWORK FOR RECURRENT NEURAL NETWORK BASED ACOUSTIC MODELING
Takashima, Ryoichi	(pg. 416) T2.3: UNIFIED ASR SYSTEM USING LGM-BASED SOURCE SEPARATION, NOISE-ROBUST FEATURE EXTRACTION, AND WORD HYPOTHESIS SELECTION
Takeda, Ryu	(pg. 52) M1.8: ACOUSTIC MODEL TRAINING BASED ON NODE-WISE WEIGHT BOUNDARY MODEL INCREASING SPEED OF DISCRETE NEURAL NETWORKS
Tan, Shawn	(pg. 617) T3.10: IMPROVING THE INTERPRETABILITY OF DEEP NEURAL NETWORKS WITH STIMULATED LEARNING
Tanaka, Tomohiro	(pg. 610) T3.9: AUTOMATION OF SYSTEM BUILDING FOR STATE-OF-THE-ART LARGE VOCABULARY SPEECH RECOGNITION USING EVOLUTION STRATEGY
Tang, Hao	(pg. 561) T3.2: DISCRIMINATIVE SEGMENTAL CASCADES FOR FEATURE-RICH PHONE RECOGNITION
Tao, Jidong	(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH
Tjandra, Andros	(pg. 175) M3.8: STOCHASTIC GRADIENT VARIATIONAL BAYES FOR DEEP LEARNING-BASED ASR
Toda, Tomoki	(pg. 252) M4.9: INCREMENTAL SENTENCE COMPRESSION USING LSTM RECURRENT NETWORKS (pg. 654) T4.5: THE NAIST ASR SYSTEM FOR THE 2015 MULTI-GENRE BROADCAST CHALLENGE: ON COMBINATION OF DEEP LEARNING SYSTEMS USING A RANK-SCORE FUNCTION (pg. 777) W2.4: A STUDY OF SOCIAL-AFFECTIVE COMMUNICATION: AUTOMATIC PREDICTION OF EMOTION TRIGGERS AND RESPONSES IN TELEVISION TALK SHOWS (pg. 784) W2.5: ADAPTIVE SELECTION FROM MULTIPLE RESPONSE CANDIDATES IN EXAMPLE-BASED DIALOGUE
Togami, Masahito	(pg. 416) T2.3: UNIFIED ASR SYSTEM USING LGM-BASED SOURCE SEPARATION, NOISE-ROBUST FEATURE EXTRACTION, AND WORD HYPOTHESIS SELECTION
Tran, Huy Dat	(pg. 518) T1.2: SINGLE AND MULTI-CHANNEL APPROACHES FOR DISTANT SPEECH RECOGNITION UNDER NOISY REVERBERANT CONDITIONS: I2R'S SYSTEM DESCRIPTION FOR THE ASPIRE CHALLENGE
Trione, Jeremy	(Demo) W1.3: AUTOMATIC SUMMARIZATION OF CALL-CENTER CONVERSATIONS
Tsai, Cheng-Yu	(pg. 245) M4.8: AN ITERATIVE DEEP LEARNING FRAMEWORK FOR UNSUPERVISED DISCOVERY OF SPEECH FEATURES AND LINGUISTIC UNITS WITH APPLICATIONS ON SPOKEN TERM DETECTION
Tsakalidis, Stavros	(pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS
Tseng, Bo-Hsiang	(pg. 84) M1.13: PERSONALIZING UNIVERSAL RECURRENT NEURAL NETWORK LANGUAGE MODEL WITH USER CHARACTERISTIC FEATURES BY SOCIAL NETWORK CROWDSOURCING
Tu, Yan-Hui	(pg. 430) T2.5: AN INFORMATION FUSION APPROACH TO RECOGNIZING MICROPHONE ARRAY SPEECH IN THE CHIME-3 CHALLENGE BASED ON A DEEP LEARNING FRAMEWORK
Tüske, Zoltán	(pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH (pg. 596) T3.7: SPEAKER ADAPTIVE JOINT TRAINING OF GAUSSIAN MIXTURE MODELS AND BOTTLENECK FEATURES

V

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va Ve Vi Vu

van Dalen, Rogier	(pg. 160) M3.6: STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES
Van Hout, Julien	(pg. 525) T1.3: IMPROVING ROBUSTNESS AGAINST REVERBERATION FOR AUTOMATIC SPEECH RECOGNITION
van Santen, Jan	(pg. 116) M2.4: SPEAKER INTONATION ADAPTATION FOR TRANSFORMING TEXT-TO-SPEECH SYNTHESIS SPEAKER IDENTITY
Vandyke, David	(pg. 763) W2.2: MULTI-DOMAIN DIALOGUE SUCCESS CLASSIFIERS FOR POLICY TRAINING (pg. 806) W2.8: POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN DIALOGUE SYSTEMS
Vergyri, Dimitra	(pg. 525) T1.3: IMPROVING ROBUSTNESS AGAINST REVERBERATION FOR AUTOMATIC SPEECH RECOGNITION
Vidaver, Gordon	(Demo) W1.1: NETPROF IOS PRONUNCIATION FEEDBACK DEMONSTRATION
Villalba, Jesus	(pg. 667) T4.7: VARIATIONAL BAYESIAN PLDA FOR SPEAKER DIARIZATION IN THE MGB CHALLENGE
Vincent, Emmanuel	(pg. 482) T2.12: ROBUST ASR USING NEURAL NETWORK BASED SPEECH ENHANCEMENT AND FEATURE SIMULATION (pg. 504) T2.15: THE THIRD `CHIME' SPEECH SEPARATION AND RECOGNITION CHALLENGE: DATASET, TASK AND BASELINES
Vu, Thanh T.	(pg. 423) T2.4: SPEECH ENHANCEMENT USING BEAMFORMING AND NON NEGATIVE MATRIX FACTORIZATION FOR ROBUST SPEECH RECOGNITION IN THE CHIME-3 CHALLENGE

W

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Wa We Wi Wo Wr

Walker, Erin	(pg. 103) M2.2: NATURALNESS AND RAPPORT IN A PITCH ADAPTIVE LEARNING COMPANION
Wang, Haipeng	(pg. 160) M3.6: STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES (pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH
Wang, Hsin-Min	(pg. 207) M4.3: INCORPORATING PARAGRAPH EMBEDDINGS AND DENSITY PEAKS CLUSTERING FOR SPOKEN DOCUMENT SUMMARIZATION
Wang, Lidan	(pg. 813) W2.9: APPLYING DEEP LEARNING TO ANSWER SELECTION: A STUDY AND AN OPEN TASK
Wang, Linlin	(pg. 639) T4.3: CAMBRIDGE UNIVERSITY TRANSCRIPTION SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 647) T4.4: THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY ALIGNMENT SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 660) T4.6: SPEAKER DIARISATION AND LONGITUDINAL LINKING IN MULTI-GENRE BROADCAST DATA
Wang, Longbiao	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Wang, Qing	(pg. 430) T2.5: AN INFORMATION FUSION APPROACH TO RECOGNIZING MICROPHONE ARRAY SPEECH IN THE CHIME-3 CHALLENGE BASED ON A DEEP LEARNING FRAMEWORK
Wang, Weiran	(pg. 561) T3.2: DISCRIMINATIVE SEGMENTAL CASCADES FOR FEATURE-RICH PHONE RECOGNITION
Wang, Wen	(pg. 324) R1.9: NAME-AWARE LANGUAGE MODEL ADAPTATION AND SPARSE FEATURES FOR STATISTICAL MACHINE TRANSLATION (pg. 525) T1.3: IMPROVING ROBUSTNESS AGAINST REVERBERATION FOR AUTOMATIC SPEECH RECOGNITION
Wang, Xinhao	(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH
Wang, Zhichao	(pg. 59) M1.9: TWO-STAGE ASGD FRAMEWORK FOR PARALLEL TRAINING OF DNN ACOUSTIC MODELS USING ETHERNET
Wang, Zhongqiu	(pg. 496) T2.14: COMBINING SPECTRAL FEATURE MAPPING AND MULTI-CHANNEL MODEL-BASED SOURCE SEPARATION FOR NOISE-ROBUST AUTOMATIC SPEECH RECOGNITION
Watanabe, Shinji	(pg. 475) T2.11: THE MERL/SRI SYSTEM FOR THE 3RD CHIME CHALLENGE USING BEAMFORMING, ROBUST FEATURE EXTRACTION, AND ADVANCED SPEECH RECOGNITION (pg. 504) T2.15: THE THIRD `CHIME' SPEECH SEPARATION AND RECOGNITION CHALLENGE: DATASET, TASK AND BASELINES (pg. 533) T1.4: ROBUST SPEECH RECOGNITION IN UNKNOWN REVERBERANT AND NOISY CONDITIONS (pg. 610) T3.9: AUTOMATION OF SYSTEM BUILDING FOR STATE-OF-THE-ART LARGE VOCABULARY SPEECH RECOGNITION USING EVOLUTION STRATEGY
Weiss, Ron	(pg. 30) M1.5: SPEAKER LOCATION AND MICROPHONE SPACING INVARIANT ACOUSTIC MODELING FROM RAW MULTICHANNEL WAVEFORMS
Wen, Tsung-Hsien	(pg. 763) W2.2: MULTI-DOMAIN DIALOGUE SUCCESS CLASSIFIERS FOR POLICY TRAINING (pg. 806) W2.8: POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN DIALOGUE SYSTEMS
Wester, Mirjam	(pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Wilkinson, Andrew	(pg. 303) R1.6: UTTERANCE CLASSIFICATION IN SPEECH-TO-SPEECH TRANSLATION FOR ZERO-RESOURCE LANGUAGES IN THE HOSPITAL ADMINISTRATION DOMAIN
Willi, Megan M.	(Demo) W1.8: MULTI-TIME RESOLUTION ANALYSIS OF INTEGRATED ACOUSTIC INFORMATION IN REDUCED SPEECH
Wilson, Kevin	(pg. 30) M1.5: SPEAKER LOCATION AND MICROPHONE SPACING INVARIANT ACOUSTIC MODELING FROM RAW MULTICHANNEL WAVEFORMS
Woodland, Philip C.	(pg. 181) M3.9: INVESTIGATION OF BACK-OFF BASED INTERPOLATION BETWEEN RECURRENT NEURAL NETWORK AND N-GRAM LANGUAGE MODELS (pg. 259) M4.10: MULTILINGUAL REPRESENTATIONS FOR LOW RESOURCE SPEECH RECOGNITION AND KEYWORD SEARCH (pg. 639) T4.3: CAMBRIDGE UNIVERSITY TRANSCRIPTION SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 647) T4.4: THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY ALIGNMENT SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 660) T4.6: SPEAKER DIARISATION AND LONGITUDINAL LINKING IN MULTI-GENRE BROADCAST DATA (pg. 687) T4.10: THE MGB CHALLENGE: EVALUATING MULTI-GENRE BROADCAST MEDIA RECOGNITION
Wray, Samantha	(Demo) W1.4: LAHAJET: A GAME FOR CLASSIFYING DIALECTAL ARABIC SPEECH

X

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Xi Xu

Xiang, Bing	(pg. 813) W2.9: APPLYING DEEP LEARNING TO ANSWER SELECTION: A STUDY AND AN OPEN TASK
Xiao, Xiong	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Xie, Lei	(pg. 98) M2.1: AUTOMATIC PROSODY PREDICTION FOR CHINESE SPEECH SYNTHESIS USING BLSTM-RNN AND EMBEDDING FEATURES
Xu, Weiqun	(pg. 791) W2.6: OPTIMIZING HUMAN-INTERPRETABLE DIALOG MANAGEMENT POLICY USING GENETIC ALGORITHM

Y

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Ya Yi Yo Yu

Yamamoto, Kazumasa	(pg. 200) M4.2: COMBINATION OF SYLLABLE BASED N-GRAM SEARCH AND WORD SEARCH FOR SPOKEN TERM DETECTION THROUGH SPOKEN QUERIES AND IV/OOV CLASSIFICATION
Yan, Jie	(pg. 98) M2.1: AUTOMATIC PROSODY PREDICTION FOR CHINESE SPEECH SYNTHESIS USING BLSTM-RNN AND EMBEDDING FEATURES
Yan, Yonghong	(pg. 59) M1.9: TWO-STAGE ASGD FRAMEWORK FOR PARALLEL TRAINING OF DNN ACOUSTIC MODELS USING ETHERNET (pg. 791) W2.6: OPTIMIZING HUMAN-INTERPRETABLE DIALOG MANAGEMENT POLICY USING GENETIC ALGORITHM
Yang, Jingzhou	(pg. 160) M3.6: STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES
Yao, Kaisheng	(pg. 353) R2.2: SEMI-SUPERVISED SLOT TAGGING IN SPOKEN LANGUAGE UNDERSTANDING USING RECURRENT TRANSDUCTIVE SUPPORT VECTOR MACHINES
Yin, Maofan	(pg. 310) R1.7: MULTI-TASK JOINT-LEARNING OF DEEP NEURAL NETWORKS FOR ROBUST SPEECH RECOGNITION
Yoshino, Koichiro	(pg. 777) W2.4: A STUDY OF SOCIAL-AFFECTIVE COMMUNICATION: AUTOMATIC PREDICTION OF EMOTION TRIGGERS AND RESPONSES IN TELEVISION TALK SHOWS (pg. 784) W2.5: ADAPTIVE SELECTION FROM MULTIPLE RESPONSE CANDIDATES IN EXAMPLE-BASED DIALOGUE
Yoshioka, Takuya	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
You, Yongbin	(pg. 310) R1.7: MULTI-TASK JOINT-LEARNING OF DEEP NEURAL NETWORKS FOR ROBUST SPEECH RECOGNITION
Young, Steve	(pg. 763) W2.2: MULTI-DOMAIN DIALOGUE SUCCESS CLASSIFIERS FOR POLICY TRAINING (pg. 806) W2.8: POLICY COMMITTEE FOR ADAPTATION IN MULTI-DOMAIN SPOKEN DIALOGUE SYSTEMS
Yu, Chengzhu	(pg. 436) T2.6: THE NTT CHIME-3 SYSTEM: ADVANCES IN SPEECH ENHANCEMENT AND RECOGNITION FOR MOBILE MULTI-MICROPHONE DEVICES
Yu, Dong	(pg. 78) M1.12: DEEP BI-DIRECTIONAL RECURRENT NETWORKS OVER SPECTRAL WINDOWS
Yu, Kai	(pg. 310) R1.7: MULTI-TASK JOINT-LEARNING OF DEEP NEURAL NETWORKS FOR ROBUST SPEECH RECOGNITION
Yu, Zhou	(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH (Demo) W1.7: A MODULAR OPEN-SOURCE STANDARD-COMPLIANT DIALOG SYSTEM FRAMEWORK WITH VIDEO SUPPORT

Z

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Ze Zh Zi Zw

Zechner, Klaus	(pg. 338) R1.11: USING BIDIRECTIONAL LSTM RECURRENT NEURAL NETWORKS TO LEARN HIGH-LEVEL ABSTRACTIONS OF SEQUENTIAL FEATURES FOR AUTOMATED SCORING OF NON-NATIVE SPONTANEOUS SPEECH
Zhang, Chao	(pg. 160) M3.6: STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES (pg. 639) T4.3: CAMBRIDGE UNIVERSITY TRANSCRIPTION SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 647) T4.4: THE DEVELOPMENT OF THE CAMBRIDGE UNIVERSITY ALIGNMENT SYSTEMS FOR THE MULTI-GENRE BROADCAST CHALLENGE (pg. 660) T4.6: SPEAKER DIARISATION AND LONGITUDINAL LINKING IN MULTI-GENRE BROADCAST DATA
Zhang, Weini	(pg. 98) M2.1: AUTOMATIC PROSODY PREDICTION FOR CHINESE SPEECH SYNTHESIS USING BLSTM-RNN AND EMBEDDING FEATURES
Zhang, Wei-Qiang	(pg. 230) M4.6: IMPROVED SYSTEM FUSION FOR KEYWORD SEARCH
Zhang, Zhaofeng	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Zhang, Zhuo	(pg. 215) M4.4: HIGH-PERFORMANCE SWAHILI KEYWORD SEARCH WITH VERY LIMITED LANGUAGE PACK: THE THUEE SYSTEM FOR THE OPENKWS15 EVALUATION
Zhao, Shengkui	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Zhong, Xionghu	(pg. 460) T2.9: ROBUST SPEECH RECOGNITION USING BEAMFORMING WITH ADAPTIVE MICROPHONE GAINS AND MULTICHANNEL NOISE REDUCTION
Zhou, Bowen	(pg. 813) W2.9: APPLYING DEEP LEARNING TO ANSWER SELECTION: A STUDY AND AN OPEN TASK
Zilka, Lukas	(pg. 757) W2.1: INCREMENTAL LSTM-BASED DIALOG STATE TRACKER
Zöhrer, Matthias	(pg. 452) T2.8: MULTI-CHANNEL SPEECH PROCESSING ARCHITECTURES FOR NOISE ROBUST SPEECH RECOGNITION: 3RD CHIME CHALLENGE RESULTS
Zweig, Geoffrey	(pg. 78) M1.12: DEEP BI-DIRECTIONAL RECURRENT NETWORKS OVER SPECTRAL WINDOWS (pg. 187) M3.10: LSTM TIME AND FREQUENCY RECURRENCE FOR AUTOMATIC SPEECH RECOGNITION