10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Performance Comparisons of the Integrated Parallel Model Combination Approaches with Front-End Noise Reduction

Guanghu Shen (1), Soo-Young Suk (2), Hyun-Yeol Chung (1)

(1) Yeungnam University, Korea
(2) AIST, Japan

In this paper, to find the best noise robustness approach, we study on approaches implemented at both-end (i.e. front-end and back-end) of speech recognition system. To reduce the noise with lower speech distortion at front-end, we investigate the Two-stage Mel-warped Wiener Filtering (TMWF) in the integrated Parallel Model Combination (PMC) approach. Furthermore, the first-stage of TMWF (i.e. One-stage Mel-warped Wiener Filtering (OMWF)), as well as the well-known Wiener Filtering (WF), is effective to reduce the noise, so we integrate PMC with those front-end noise reduction approaches. From the recognition performance, TMWF-PMC shows improved performance comparing with the well-known WF-PMC, and OMWF-PMC also shows a comparable performance in all noises.

Full Paper

Bibliographic reference.  Shen, Guanghu / Suk, Soo-Young / Chung, Hyun-Yeol (2009): "Performance comparisons of the integrated parallel model combination approaches with front-end noise reduction", In INTERSPEECH-2009, 2387-2390.