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2009
IEEE

A study on multilingual acoustic modeling for large vocabulary ASR

10 years 4 months ago
A study on multilingual acoustic modeling for large vocabulary ASR
We study key issues related to multilingual acoustic modeling for automatic speech recognition (ASR) through a series of large-scale ASR experiments. Our study explores shared structures embedded in a large collection of speech data spanning over a number of spoken languages in order to establish a common set of universal phone models that can be used for large vocabulary ASR of all the languages seen or unseen during training. Language-universal and language-adaptive models are compared with language-specific models, and the comparison results show that in many cases it is possible to build general-purpose language-universal and language-adaptive acoustic models that outperform language-specific ones if the set of shared units, the structure of shared states, and the shared acoustic-phonetic properties among different languages can be properly utilized. Specifically, our results demonstrate that when the context coverage is poor in language-specific training, we can use one tenth of ...
Hui Lin, Li Deng, Dong Yu, Yifan Gong, Alex Acero,
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Hui Lin, Li Deng, Dong Yu, Yifan Gong, Alex Acero, Chin-Hui Lee
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