Title
Bayesian And Gaussian Process Neural Networks For Large Vocabulary Continuous Speech Recognition
Abstract
The hidden activation functions inside deep neural networks ( DNNs) play a vital role in learning high level discriminative features and controlling the information flows to track longer history. However, the fixed model parameters used in standard DNNs can lead to over-fitting and poor generalization when given limited training data. Furthermore, the precise forms of activations used in DNNs are often manually set at a global level for all hidden nodes, thus lacking an automatic selection method. In order to address these issues, Bayesian neural networks ( BNNs) acoustic models are proposed in this paper to explicitly model the uncertainty associated with DNN parameters. Gaussian Process ( GP) activations based DNN and LSTM acoustic models are also used in this paper to allow the optimal forms of hidden activations to be stochastically learned for individual hidden nodes. An efficient variational inference based training algorithm is derived for BNN, GPNN and GPLSTM systems. Experiments were conducted on a LVCSR system trained on a 75 hour subset of Switchboard I data. The best BNN and GPNN systems outperformed both the baseline DNN systems constructed using fixed form activations and their combination via frame level joint decoding by 1% absolute in word error rate.
Year
DOI
Venue
2019
10.1109/icassp.2019.8682487
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
Bayesian Neural Network, Gaussian Process Neural Network, activation function selection, speech recognition
Pattern recognition,Computer science,Inference,Word error rate,Speech recognition,Artificial intelligence,Gaussian process,Decoding methods,Artificial neural network,Discriminative model,Vocabulary,Bayesian probability
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Shoukang Hu1610.90
Max W. Y. Lam216.43
Xurong Xie368.57
Shansong Liu425.77
Jianwei Yu5810.92
Wu Xixin62314.32
Xunying Liu733052.46
Helen M. Meng81078172.82