Noise and Channel Distortion Robust ASR System for DARPA SPINE2 Task

Konstantin MARKOV  Tomoko MATSUI  Rainer GRUHN  Jinsong ZHANG  Satoshi NAKAMURA  

IEICE TRANSACTIONS on Information and Systems   Vol.E86-D    No.3    pp.497-504
Publication Date: 2003/03/01
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Speech Information Processing)
Category: Robust Speech Recognition and Enhancement
noise robustness,  online adaptation,  hypothesis combination,  robust features,  

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This paper presents the ATR speech recognition system designed for the DARPA SPINE2 evaluation task. The system is capable of dealing with speech from highly variable, real-world noisy conditions and communication channels. A number of robust techniques are implemented, such as differential spectrum mel-scale cepstrum features, on-line MLLR adaptation, and word-level hypothesis combination, which led to a significant reduction in the word error rate.