Integration of rule-based formant synthesis and waveform concatenation: a hybrid approach to text-to-speech synthesis
Sue Hertz
Abstract
Sue Hertz
Abstract
This paper describes an approach to speech synthesis in which waveform fragments dynamically produced with a set of formant-based synthesis rules are concatenated with pre-stored natural speech waveform fragments to produce a synthetic utterance. While this hybrid approach was originally implemented as a tool for research into improved voice quality in formant-based synthesis, it has produced such good results that we now view it as a potentially viable and advantageous approach for a text-to-speech product. Possible advantages of the approach include smaller speech databases for waveform concatenation, enhancement of certain speech cues for sub-optimal listening environments, and improved and more efficient unit selection/production. In addition, the approach has already proven its utility as a tool for research and development in both concatenative and formant-based synthesis.
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This paper describes an approach to speech synthesis in which waveform fragments dynamically produced with a set of formant-based synthesis rules are concatenated with pre-stored natural speech waveform fragments to produce a synthetic utterance. While this hybrid approach was originally implemented as a tool for research into improved voice quality in formant-based synthesis, it has produced such good results that we now view it as a potentially viable and advantageous approach for a text-to-speech product. Possible advantages of the approach include smaller speech databases for waveform concatenation, enhancement of certain speech cues for sub-optimal listening environments, and improved and more efficient unit selection/production. In addition, the approach has already proven its utility as a tool for research and development in both concatenative and formant-based synthesis.
Key concepts: Concatenation (mathematics), Speech synthesis, Formant, Computer science, Waveform, Speech recognition, Utterance, Set (abstract data type)