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2008

Evaluation of several Maximum Likelihood Linear Regression Variants for Language Adaptation

12 years 3 months ago
Evaluation of several Maximum Likelihood Linear Regression Variants for Language Adaptation
Multilingual Automatic Speech Recognition (ASR) systems are of great interest in multilingual environments. We studied the case of the Comunitat Valenciana where the two official languages are Spanish and Valencian. These two languages share most of their phonemes, and their syntax and vocabulary are also quite similar since they have influenced each other for many years. We constructed a system, and trained its acoustic models with a small corpus of Spanish and Valencian, which has produced poor results due to the lack of data. Adaptation techniques can be used to adapt acoustic models that are trained with a large corpus of a language inr order to obtain acoustic models for a phonetically similar language. This process is known as language adaptation. The Maximum Likelihood Linear Regression (MLLR) technique has commonly been used in speaker adaptation; however we have used MLLR in language adaptation. We compared several MLLR variants (mean square, diagonal matrix and full matrix) ...
Míriam Luján-Mares, Carlos D. Mart&i
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where LREC
Authors Míriam Luján-Mares, Carlos D. Martínez-Hinarejos, Vicent Alabau Gonzalvo
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