DocumentCode :
2452343
Title :
Multichannel speech recognition using distributed microphone signal fusion strategies
Author :
Trawicki, Marek B. ; Johnson, Michael T. ; Ji, An ; Osiejuk, Tomasz S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
fYear :
2012
fDate :
16-18 July 2012
Firstpage :
1146
Lastpage :
1150
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.
Keywords :
microphones; speech recognition; distributed microphone signal fusion strategies; multichannel songbird dataset; multichannel speech recognition; noisy distributed microphone signals; song type recognition; Accuracy; Array signal processing; Microphone arrays; Noise measurement; Speech; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2012 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-0173-2
Type :
conf
DOI :
10.1109/ICALIP.2012.6376789
Filename :
6376789
Link To Document :
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