A nonlinear unit selection strategy for concatenative speech synthesis based on syllable level features
نویسندگان
چکیده
This paper describes an improved algorithm, motivated by fuzzy logic theory, for the selection of speech segments for concatenative synthesis from a huge database. Triphone HMM clustering is employed as an adaptive measure for articulatory similarity within a given database. Stress level contours are evaluated in the context of their surrounding vocalic peaks. The algorithm uses a beam search technique to optimise the suitability of each candidate unit to realise the desired target as well as continuity in concatenation.
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