Robust speech recognition using noise-cluster HMM interpolation

Thatphithakkul, Nattanun; Kruatrachue, Boontee; Wutiwiwatchai, Chai; Marukatat, Sanparith; Boonpiam, Vataya

doi:10.1109/ICOSP.2008.4697203

Robust speech recognition using noise-cluster HMM interpolation

Author(s)

Thatphithakkul, Nattanun

Kruatrachue, Boontee

Wutiwiwatchai, Chai

Marukatat, Sanparith

Boonpiam, Vataya

Date Issued

December 1, 2008

Type

Conference Paper

DOI

10.1109/ICOSP.2008.4697203

Abstract

This paper proposes a novel approach called noisecluster HMM interpolation for robust speech recognition. The approach helps alleviating the problem of speech recognition under noisy environments not trained in the system. In this method, a new HMM is interpolated from existing noisy-speech HMMs that are best matched to the input speech. This process is performed on-the-fly with an acceptable delay time and, hence, no need to prepare and store the final model in advance. Interpolation weights among HMMs can be determined by either a direct or a tree-structured search. Evaluated focusing on speech in unseen noisy-environments, the proposed method obviously outperforms a baseline system whose acoustic model for such unseen environment is selected from a tree structure. © 2008 IEEE.

Citation

International Conference on Signal Processing Proceedings ICSP, 596-600, 2008