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KMID : 1022420180100010049
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Phonetics and Speech Sciences
2018 Volume.10 No. 1 p.49 ~ p.55
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A knowledge-based pronunciation generation system for French
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Kim Sun-Hee
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Abstract
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This paper aims to describe a knowledge-based pronunciation generation system for French. It has been reported that a rule-based pronunciation generation system outperforms most of the data-driven ones for French; however, only a few related studies are available due to existing language barriers. We provide basic information about the French language from the point of view of the relationship between orthography and pronunciation, and then describe our knowledge-based pronunciation generation system, which consists of morphological analysis, Part-of-Speech (POS) tagging, grapheme-to-phoneme generation, and phone-to-phone generation. The evaluation results show that the word error rate of POS tagging, based on a sample of 1,000 sentences, is 10.70% and that of phoneme generation, using 130,883 entries, is 2.70%. This study is expected to contribute to the development and evaluation of speech synthesis or speech recognition systems for French.
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KEYWORD
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pronunciation generation, French, speech synthesis, speech recognition, knowledge-based
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FullTexts / Linksout information
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