REPORT misra-rr-02-31/IDIAP Entropy-based Multi-stream Combination Misra, Hemant Bourlard, Hervé Tyagi, Vivek EXTERNAL http://publications.idiap.ch/attachments/reports/2002/rr02-31.pdf PUBLIC Idiap-RR-31-2002 2002 IDIAP Martigny, Switzerland {in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing {(ICASSP)}, 2003} Full-combination multi-band approach has been proposed in the literature and performs well for band-limited noise. But the approach fails to deliver in case of wide-band noise. To overcome this, multi-stream approaches are proposed in literature with varying degree of success. Based on our observation that for a classifier trained on clean speech, the entropy at the output of the classifier increases in presence of noise at its input, we used entropy as a measure of confidence to give weightage to a classifier output. In this paper, we propose a new entropy based combination strategy for full-combination multi-stream approach. In this entropy based approach, a particular stream is weighted inversely proportional to the output entropy of its specific classifier. A few variations of this basic approach are also suggested. It is observed that the word-error-rate (WER) achieved by the proposed combination methods is better for different types of noises and for their different signal-to-noise-ratios (SNRs). Some interesting relationship is observed between the WER performances of different combination methods and their respective entropies.