Speaker Adaptation in Sparse Subspace of Acoustic Models

Yongwon JEONG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E96-D   No.6   pp.1402-1405
Publication Date: 2013/06/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E96.D.1402
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
Keyword: 
eigenvoice speaker adaptation,  robust speech recognition,  sparse principal component analysis,  speaker adaptation,  speech recognition,  

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Summary: 
I propose an acoustic model adaptation method using bases constructed through the sparse principal component analysis (SPCA) of acoustic models trained in a clean environment. I perform experiments on adaptation to a new speaker and noise. The SPCA-based method outperforms the PCA-based method in the presence of babble noise.