Multichannel Speech Recognition Using Distributed Microphone Signal Fusion Strategies

Marek B. Trawicki, Marquette University
Michael T. Johnson, Marquette University
An Ji, Marquette University
Tomasz S. Osiejuk, Adam Mickiewicz University

Published as part of the proceedings of the conference, Multichannel Speech Recognition using Distributed Microphone Signal Fusion Strategies, 2012: 1146-1150. DOI: 10.1109/ICALIP.2012.6376789.

Abstract

Multichannel fusion strategies are presented for the distributed microphone recognition environment, for the task of song-type recognition in a multichannel songbird dataset. The signals are first fused together based on various heuristics, including their amplitudes, variances, physical distance, or squared distance, before passing the enhanced single-channel signal into the speech recognition system. The intensity-weighted fusion strategy achieved the highest overall recognition accuracy of 94.4%. By combining the noisy distributed microphone signals in an intelligent way that is proportional to the information contained in the signals, speech recognition systems can achieve higher recognition accuracies.