Using the Multi-Stream Approach for Continuous Audio-Visual Speech Recognition: Experiments on the M2VTS Database

The Multi-Stream automatic speech recognition approach was investigated in this work as a framework for Audio-Visual data fusion and speech recognition. This method presents many potential advantages for such a task. It particularly allows for synchronous decoding of continuous speech while still allowing for some asynchrony of the visual and acoustic information streams. First, the Multi-Stream formalism is briefly recalled. Then, on top of the Multi-Stream motivations, experiments on the M2VTS multimodal database are presented and discussed. To our knowledge, these are the first experiments about multi-speaker continuous Audio-Visual Speech Recognition (AVSR). It is shown that the Multi-Stream approach can yield improved Audio-Visual speech recognition performance when the acoustic signal is corrupted by noise as well as for clean speech.

Published in:
Proc. 5th Int. Conf. on Spoken Language Processing, 4, 1283-1286
Presented at:
Proc. 5th Int. Conf. on Spoken Language Processing

 Record created 2006-03-10, last modified 2018-03-17

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