Explorer Unsupervised cross - lingual speaker adaptation for HMM - based speech synthesis
نویسندگان
چکیده
In the EMIME project, we are developing a mobile device that performs personalized speech-to-speech translation such that a user’s spoken input in one language is used to produce spoken output in another language, while continuing to sound like the user’s voice. We integrate two techniques, unsupervised adaptation for HMM-based TTS using a wordbased large-vocabulary continuous speech recognizer and cross-lingual speaker adaptation for HMM-based TTS, into a single architecture. Thus, an unsupervised cross-lingual speaker adaptation system can be developed. Listening tests show very promising results, demonstrating that adapted voices sound similar to the target speaker and that differences between supervised and unsupervised cross-lingual speaker adaptation are small.
منابع مشابه
Personalising speech-to-speech translation: Unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis
In this paper we present results of unsupervised cross-lingual speaker adaptation applied to text-to-speech synthesis. The application of our research is the personalisation of speech-to-speech translation in which we employ a HMM statistical framework for both speech recognition and synthesis. This framework provides a logical mechanism to adapt synthesised speech output to the voice of the us...
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In the EMIME project, we developed a mobile device that performs personalized speech-to-speech translation such that a user’s spoken input in one language is used to produce spoken output in another language, while continuing to sound like the user’s voice. We integrated two techniques into a single architecture: unsupervised adaptation for HMM-based TTS using word-based large-vocabulary contin...
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