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Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/9E571AA5-BAA3-4B28-BEBF-B7187B634C0C | ||
| Year | 2007 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
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| Bibliographic Citation | N. Chatzichrisafis, V. Diakoloukas, V. Digalakis and C. Harizakis, "Gaussian mixture clustering and language adaptation for the development of a new language speech recognition system," IEEE Trans. Audio, Speech, Language Process., vol. 15, no. 3, pp. 928-938, Mar. 2007. doi:10.1109/TASL.2006.885259 https://doi.org/10.1109/TASL.2006.885259 | ||
| Appears in Collections |
The porting of a speech recognition system to a new language is usually a time-consuming and expensive process since it requires collecting, transcribing, and processing a large amount of language-specific training sentences. This work presents techniques for improved cross-language transfer of speech recognition systems to new target languages. Such techniques are particularly useful for target languages where minimal amounts of training data are available. We describe a novel method to produce a language-independent system by combining acoustic models from a number of source languages. This intermediate language-independent acoustic model is used to bootstrap a target-language system by applying language adaptation. For our experiments, we use acoustic models of seven source languages to develop a target Greek acoustic model. We show that our technique significantly outperforms a system trained from scratch when less than 8 h of read speech is available
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