Article details

Research area
Natural language & AI

Location
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on

Date
2005

Author(s)

Increased robustness against bit errors for distributed speech recognition in wireless environments

Synopsis:

In distributed speech recognition, the speech features are com­puted on a mobile device, compressed, and sent over a network to a speech recognition server, where the Viterbi search and hid­den Markov modeling takes place. In this work, we examine some error concealment methods for distributed speech recognition over burst error channels. We consider interpolation and interleaving, and we present a novel use of the stochastic weighted Viterbi recog­nition algorithm to increase robustness against interpolated fea­tures. We examine interleaving at both the frame level and code-book index level. Channel errors are simulated using a Gilbert model, and the performance of our algorithm is compared with other techniques, including the ETSI DSR standard, on a digits task and a large vocabulary task. Coupled with interleaving and in­terpolation, our algorithm can provide accuracy as high as 96.7% on a digit recognition task during an average bit error probabil­ity of 20 1.On the more difficult WSJ task, the accuracy without bit errors is 85.7%. Using our algorithm, we can achieve 82.9% accuracy with an average bit error probability of130.

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