Using same-language machine translation to create alternative target sequences for text-to-speech synthesis

نویسندگان

  • Peter Cahill
  • Jinhua Du
  • Andy Way
  • Julie Carson-Berndsen
چکیده

Modern speech synthesis systems attempt to produce speech utterances from an open domain of words. In some situations, the synthesiser will not have the appropriate units to pronounce some words or phrases accurately but it still must attempt to pronounce them. This paper presents a hybrid machine translation and unit selection speech synthesis system. The machine translation system was trained with English as the source and target language. Rather than the synthesiser only saying the input text as would happen in conventional synthesis systems, the synthesiser may say an alternative utterance with the same meaning. This method allows the synthesiser to overcome the problem of insufficient units in runtime.

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تاریخ انتشار 2009