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The IBM 2015 English Conversational Telephone Speech Recognition System (1505.05899v1)
Published 21 May 2015 in cs.CL
Abstract: We describe the latest improvements to the IBM English conversational telephone speech recognition system. Some of the techniques that were found beneficial are: maxout networks with annealed dropout rates; networks with a very large number of outputs trained on 2000 hours of data; joint modeling of partially unfolded recurrent neural networks and convolutional nets by combining the bottleneck and output layers and retraining the resulting model; and lastly, sophisticated LLM rescoring with exponential and neural network LMs. These techniques result in an 8.0% word error rate on the Switchboard part of the Hub5-2000 evaluation test set which is 23% relative better than our previous best published result.
- George Saon (39 papers)
- Hong-Kwang J. Kuo (11 papers)
- Steven Rennie (6 papers)
- Michael Picheny (32 papers)