Technical Program

SP-L8: Alternative ASR Methods

Session Type: Lecture
Time: Friday, March 30, 10:30 - 12:30
Location: Room B-1
Session Chairs: Dirk van Compernolle, K.U.Leuven – ESAT and Honza Cernocky, Brno University of Technology
 
SP-L8.1: INFERENCE ALGORITHMS FOR GENERATIVE SCORE-SPACES
         Anton Ragni; University of Cambridge
         Mark Gales; University of Cambridge
 
SP-L8.2: AUTO-ENCODER BOTTLENECK FEATURES USING DEEP BELIEF NETWORKS
         Tara Sainath; IBM T.J. Watson Research Center
         Brian Kingsbury; IBM T.J. Watson Research Center
         Bhuvana Ramabhadran; IBM T.J. Watson Research Center
 
SP-L8.3: ANALYZING THE MEMORY OF BLSTM NEURAL NETWORKS FOR ENHANCED EMOTION CLASSIFICATION IN DYADIC SPOKEN INTERACTIONS
         Martin Woellmer; Technische Universitaet Muenchen
         Angeliki Metallinou; University of Southern California
         Nassos Katsamanis; University of Southern California
         Björn Schuller; Technische Universität München
         Shrikanth Narayanan; University of Southern California
 
SP-L8.4: CLASSIFICATION AND RECOGNITION WITH DIRECT SEGMENT MODELS
         Geoffrey Zweig; Microsoft Research
 
SP-L8.5: IMPROVED PRE-TRAINING OF DEEP BELIEF NETWORKS USING SPARSE ENCODING SYMMETRIC MACHINES
         Christian Plahl; RWTH Aachen University
         Tara Sainath; International Business Machines Corporation
         Bhuvana Ramabhadran; International Business Machines Corporation
         David Nahamoo; International Business Machines Corporation
 
SP-L8.6: BOOSTING ATTRIBUTE AND PHONE ESTIMATION ACCURACIES WITH DEEP NEURAL NETWORKS FOR DETECTION-BASED SPEECH RECOGNITION
         Dong Yu; Microsoft Research
         Sabato Siniscalchi; Kore University of Enna
         Li Deng; Microsoft Research
         Chin-Hui Lee; Georgia Institute of Technology