Technical Program

ASR-2: Speech Recognition 2

Session Type: Poster
Poster Time: Thursday, December 15, 15:30 - 17:30
Location: Lahaina Bay Room
Session Chair: Michiel Bacchiani, Google Inc.
 
ASR-2.1: AN UNSUPERVISED VOCABULARY SELECTION TECHNIQUE FOR CHINESE AUTOMATIC SPEECH RECOGNITION
         Yike Zhang; Institue of Acoustics, Chinese Academy of Sciences, China
         Pengyuan Zhang; Institue of Acoustics, Chinese Academy of Sciences, China
         Ta Li; Institue of Acoustics, Chinese Academy of Sciences, China
         Yonghong Yan; Institue of Acoustics, Chinese Academy of Sciences, China
 
ASR-2.2: DYNAMIC ADJUSTMENT OF LANGUAGE MODELS FOR AUTOMATIC SPEECH RECOGNITION USING WORD SIMILARITY
         Anna Currey; LORIA-INRIA, France
         Irina Illina; LORIA-INRIA, France
         Dominique Fohr; LORIA-INRIA, France
 
ASR-2.3: PUNCTUATED TRANSCRIPTION OF MULTI-GENRE BROADCASTS USING ACOUSTIC AND LEXICAL APPROACHES
         Ondřej Klejch; University of Edinburgh, United Kingdom
         Peter Bell; University of Edinburgh, United Kingdom
         Steve Renals; University of Edinburgh, United Kingdom
 
ASR-2.4: CONTEXTUAL LANGUAGE MODEL ADAPTATION USING DYNAMIC CLASSES
         Lucy Vasserman; Google Inc., United States
         Ben Haynor; Google Inc., United States
         Petar Aleksic; Google Inc., United States
 
ASR-2.5: UNSUPERVISED CONTEXT LEARNING FOR SPEECH RECOGNITION
         Assaf Hurwitz Michaely; Google Inc., United States
         Mohammadreza Ghodsi; Google Inc., United States
         Zelin Wu; Google Inc., United States
         Justin Scheiner; Google Inc., United States
         Petar Aleksic; Google Inc., United States
 
ASR-2.6: AUTOMATED OPTIMIZATION OF DECODER HYPER-PARAMETERS FOR ONLINE LVCSR
         Akshay Chandrashekaran; Carnegie Mellon University, United States
         Ian Lane; Carnegie Mellon University, United States
 
ASR-2.7: SEQUENCE TRAINING AND ADAPTATION OF HIGHWAY DEEP NEURAL NETWORKS
         Liang Lu; Toyota Technological Institute at Chicago, United States
 
ASR-2.8: A PRIORITIZED GRID LONG SHORT-TERM MEMORY RNN FOR SPEECH RECOGNITION
         Wei-Ning Hsu; Massachusetts Institute of Technology, United States
         Yu Zhang; Massachusetts Institute of Technology, United States
         James Glass; Massachusetts Institute of Technology, United States
 
ASR-2.9: MAX-POOLING LOSS TRAINING OF LONG SHORT-TERM MEMORY NETWORKS FOR SMALL-FOOTPRINT KEYWORD SPOTTING
         Ming Sun; Amazon.com, United States
         Anirudh Raju; Amazon.com, United States
         George Tucker; Google Inc., United States
         Sankaran Panchapagesan; Amazon.com, United States
         Gengshen Fu; Amazon.com, United States
         Arindam Mandal; Amazon.com, United States
         Spyros Matsoukas; Amazon.com, United States
         Nikko Strom; Amazon.com, United States
         Shiv Vitaladevuni; Amazon.com, United States
 
ASR-2.10: VERY DEEP CONVOLUTIONAL NEURAL NETWORKS FOR ROBUST SPEECH RECOGNITION
         Yanmin Qian; Shanghai Jiao Tong University, China
         Philip C Woodland; Cambridge University, United Kingdom
 
ASR-2.11: DEEP LEARNING WITH MAXIMAL FIGURE-OF-MERIT COST TO ADVANCE MULTI-LABEL SPEECH ATTRIBUTE DETECTION
         Ivan Kukanov; University of Eastern Finland, Finland
         Ville Hautamäki; University of Eastern Finland, Finland
         Marco Siniscalchi; The Kore University of Enna, Italy
         Kehuang Li; Georgia Institute of Technology, United States
 
ASR-2.12: END-TO-END TRAINING APPROACHES FOR DISCRIMINATIVE SEGMENTAL MODELS
         Hao Tang; Toyota Technological Institute at Chicago, United States
         Weiran Wang; Toyota Technological Institute at Chicago, United States
         Kevin Gimpel; Toyota Technological Institute at Chicago, United States
         Karen Livescu; Toyota Technological Institute at Chicago, United States
 
ASR-2.13: DISCRIMINATIVE ACOUSTIC WORD EMBEDDINGS: RECURRENT NEURAL NETWORK-BASED APPROACHES
         Shane Settle; Toyota Technological Institute at Chicago, United States
         Karen Livescu; Toyota Technological Institute at Chicago, United States