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A segment-based approach to voice conversion
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CHI '06 Extended Abstracts on Human Factors in Computing Systems
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Voice conversion techniques attempt to modify speech signal so that it is perceived as if spoken by another speaker, different from the original speaker. In this paper, we present a novel approach to perform voice conversion. Our approach uses acoustic models based on units of speech, like phones and diphones, for voice conversion. These models can be computed and used independently for a given speaker without being concerned about the source or target speaker. It avoids the use of a parallel speech corpus in the voices of source and target speakers. It is shown that by using the proposed approach, voice fonts can be created and stored which will represent individual characteristics of a particular speaker, to be used for customization of synthetic speech. We also show through objective and subjective tests, that voice conversion quality is comparable to other approaches that require a parallel speech corpus.