Gaussian Mixture Clustering and Language Adaptation for the Development of a New Language Speech Recognition System
| Autor: | Vassilios Digalakis, Vassilios Diakoloukas, Nikos Chatzichrisafis, Costas Harizakis |
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| Rok vydání: | 2007 |
| Předmět: |
Acoustics and Ultrasonics
business.industry Computer science Speech recognition Process (computing) Acoustic model Speech processing computer.software_genre Porting Constructed language symbols.namesake symbols Artificial intelligence Electrical and Electronic Engineering Adaptation (computer science) business Cluster analysis computer Gaussian process Natural language processing |
| Zdroj: | IEEE Transactions on Audio, Speech and Language Processing. 15:928-938 |
| ISSN: | 1558-7916 |
| DOI: | 10.1109/tasl.2006.885259 |
| Popis: | 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 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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