@inproceedings{361d68b25c4b4ad2981b0a88d32bb4dd,
title = "Acoustic feature compensation based on decomposition of speech and noise for ASR in noisy environments",
abstract = "This paper presents a set of acoustic feature pre-processing techniques that are applied to improving automatic speech recognition (ASR) performance on the Aurora 2 noisy speech recognition task. The principal contribution of this paper is an approach for cepstrum domain feature compensation in ASR which is motivated by techniques for decomposing speech and noise that were originally developed for noisy speech enhancement. This approach is applied in combination with other feature compensation algorithms to compensating ASR features obtained from a mel-filterbank cepstrum coefficient (MFCC) front-end. Performance comparisons are made with respect to the application of the minimum mean squared error log spectral amplitude estimator (MMSE-LSA) based speech enhancement algorithm prior to feature analysis. An experimental study is presented where the feature compensation approaches described in the paper are found to reduce ASR word error rate by as much as 31% relative to uncompensated features under simulated environmental and channel mismatched conditions.",
author = "Kim, {Hong Kook} and Rose, {Richard C.} and Kang, {Hong Goo}",
year = "2001",
language = "English",
series = "EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology",
publisher = "International Speech Communication Association",
pages = "421--424",
editor = "Borge Lindberg and Henrik Benner and Paul Dalsgaard and Zheng-Hua Tan",
booktitle = "EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology",
note = "7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001 ; Conference date: 03-09-2001 Through 07-09-2001",
}