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• W11074920 abstract "Grapheme-to-phoneme conversion is an important step in speech segmentation and synthesis. Many approaches are proposed in the literature to perform appropriate transcriptions: CART, FST, HMM, etc. In this paper we propose the use of an automatic algorithm that uses the transformation-based errordriven learning to match the phonetic transcription with the speaker’s dialect and style. Different transcriptions based on word, part-of-speech tags, weak forms and phonotactic rules are validated. The experimental results show an improvement in the transcription using an objective measure. The articulation MOS score is also improved, as most of the changes in phonetic transcription affect coarticulation effects. Index Terms: speech synthesis, speech intelligibility, speech recognition, Hidden Markov models" @default.
• W11074920 created "2016-06-24" @default.
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• W11074920 date "2009-09-06" @default.
• W11074920 modified "2023-09-26" @default.
• W11074920 title "Improving consistence of phonetic transcription for text-to-speech" @default.
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• W11074920 doi "https://doi.org/10.21437/interspeech.2009-194" @default.
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