Gaussian Mixture Clustering and Language Adaptation for the Development of a New Language Speech Recognition System.
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| Title: | Gaussian Mixture Clustering and Language Adaptation for the Development of a New Language Speech Recognition System. |
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| Authors: | Chatzichrisafis, Nikos1 Nikos.Chatzichrisafis@vozZup.com, Diakoloukas, Vassilios2 vas@ltelecom.tuc.gr, Digalakis, Vassilios2 vdiak@telecom.tuc.gr, Harizakis, Costas2 harizak@speech.gr |
| Source: | IEEE Transactions on Audio, Speech & Language Processing. Mar2007, Vol. 15 Issue 3, p928-938. 11p. 4 Diagrams, 7 Charts, 7 Graphs. |
| Subjects: | Speech processing systems, Application software porting, Speech perception, Language & languages, Acoustic models |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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