Personalising speech-to-speech translation: Unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis
| Type of publication: | Journal paper |
| Citation: | Dines_CSL_2011 |
| Publication status: | Accepted |
| Journal: | Computer Speech and Language |
| Year: | 2011 |
| URL: | http://www.sciencedirect.com/s... |
| DOI: | doi:10.1016/j.csl.2011.08.003 |
| Abstract: | 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 user by way of speech recognition. In this work we present results of several different unsupervised and cross-lingual adaptation approaches as well as an end-to-end speaker adaptive speech-to-speech translation system. Our experiments show that we can successfully apply speaker adaptation in both unsupervised and cross-lingual scenarios and our proposed algorithms seem to generalise well for several language pairs. We also discuss important future directions including the need for better evaluation metrics. |
| Keywords: | cross-lingual speaker adaptation, Machine Translation, speech recognition, speech synthesis |
| Projects: |
Idiap EMIME |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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