Open AccessModel Adaptation Using Discriminative Noise Adaptive Training Approach for New Environments
Author(s) -
Jung HoYoung,
Kang ByungOk,
Lee Yunkeun
Publication year - 2008
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.08.0208.0256
Subject(s) - discriminative model , adaptation (eye) , computer science , noise (video) , speech recognition , artificial intelligence , training (meteorology) , machine learning , pattern recognition (psychology) , psychology , image (mathematics) , neuroscience , meteorology , physics
A conventional environment adaptation for robust speech recognition is usually conducted using transform‐based techniques. Here, we present a discriminative adaptation strategy based on a multi‐condition‐trained model, and propose a new method to provide universal application to a new environment using the environment's specific conditions. Experimental results show that a speech recognition system adapted using the proposed method works successfully for other conditions as well as for those of the new environment.