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N-gram Adaptation with Dynamic Interpolation Coefficient Using Information Retrieval Technique
Joon-Ki CHOI Yung-Hwan OH
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2006/09/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
language model adaptation, adaptation corpus, dynamic interpolation coefficient, speech recognition,
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This study presents an N-gram adaptation technique when additional text data for the adaptation do not exist. We use a language modeling approach to the information retrieval (IR) technique to collect the appropriate adaptation corpus from baseline text data. We propose to use a dynamic interpolation coefficient to merge the N-gram, where the interpolation coefficient is estimated from the word hypotheses obtained by segmenting the input speech. Experimental results show that the proposed adapted N-gram always has better performance than the background N-gram.