Revisiting recurrent neural networks for robust ASR

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2012, Pages 4085-4088

  Vinyals, Oriol ^a,b   Ravuri, Suman V ^a,b   Povey, Daniel ^c  

^a INTERNATIONAL COMPUTER SCIENCE INSTITUTE   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c MICROSOFT RESEARCH   (United States)

Author keywords

Automatic Speech Recognition; Deep Learning; Recurrent Neural Networks

Indexed keywords

AUTOMATIC SPEECH RECOGNITION; CLEAN SPEECH; DEEP LEARNING; HIDDEN STATE; HIGH NOISE; MARKOVIAN DYNAMICS; MULTI-LAYER PERCEPTRONS; NETWORK STRUCTURES; NOISE CONDITIONS; NONLINEAR FUNCTIONS; OPTIMIZATION TECHNIQUES; PRE-TRAINING; ROBUST ASR; SECOND ORDERS;

ACOUSTIC NOISE; FUNCTIONS; OPTIMIZATION; PATTERN RECOGNITION SYSTEMS; SIGNAL PROCESSING; SPEECH RECOGNITION;

RECURRENT NEURAL NETWORKS;

EID: 84867626068     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2012.6288816     Document Type: Conference Paper

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