Technical Program

SP-L8: Acoustic Modeling and Adaptation

Session Type: Lecture
Time: Wednesday, March 8, 16:00 - 18:00
Location: Grand Salon 16
Session Chairs: Michiel Bacchiani, Google and Koichi Shinoda, Tokyo Institute of Technology
 
SP-L8.1: JOINT OPTIMISATION OF TANDEM SYSTEMS USING GAUSSIAN MIXTURE DENSITY NEURAL NETWORK DISCRIMINATIVE SEQUENCE TRAINING
         Chao Zhang; Cambridge University
         Phil Woodland; Cambridge University
 
SP-L8.2: VISUAL FEATURES FOR CONTEXT-AWARE SPEECH RECOGNITION
         Abhinav Gupta; Carnegie Mellon University
         Yajie Miao; Carnegie Mellon University
         Leonardo Neves; Carnegie Mellon University
         Florian Metze; Carnegie Mellon University
 
SP-L8.3: EXPLOITING SEQUENTIAL LOW-RANK FACTORIZATION FOR MULTILINGUAL DNNS
         Reza Sahraeian; KU Leuven
         Dirk Van Compernolle; KU Leuven
 
SP-L8.4: LOW-RESOURCE GRAPHEME-TO-PHONEME CONVERSION USING RECURRENT NEURAL NETWORKS
         Preethi Jyothi; Indian Institute of Technology Bombay
         Mark Hasegawa-Johnson; University of Illinois at Urbana-Champaign
 
SP-L8.5: AN INVESTIGATION INTO LEARNING EFFECTIVE SPEAKER SUBSPACES FOR ROBUST UNSUPERVISED DNN ADAPTATION
         Lahiru Samarakoon; National University of Singapore
         Khe Chai Sim; Google Inc.
         Brian Mak; Hong Kong University of Science and Technology
 
SP-L8.6: EXTENDED LOW-RANK PLUS DIAGONAL ADAPTATION FOR DEEP AND RECURRENT NEURAL NETWORKS
         Yong Zhao; Microsoft
         Jinyu Li; Microsoft
         Kshitiz Kumar; Microsoft
         Yifan Gong; Microsoft