On the integration of time-frequency masking speech separation and recognition in underdetermined environments

Abstract

The successful application of automatic speech recognition systems in the real world is conditional on its ability to handle realistic environments with unfavorable conditions such as reverberation and multiple sources of inteference. Previous research has identified time-frequency masking based approaches to blind source separation as a viable approach for multisource reverberant source separation. It is proposed the use of such separation techniques as a front-end to speech recognition will encourage greater recognition accuracy. Experimental evaluations confirmed the hypothesis with an improvement in recognition accuracy of over 20% at a reverberation time of RT <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sub> = 300ms; this is indicative of the potential for future research in this field.