Abstract
This paper describes a tree-based model of prosodic phrasing for Chinese text-to-speech (TTS) systems. The model uses classification and regression trees (CART) techniques to generate the decision tree automatically. We collected 559 sentences from CCTV news program and built a corresponding speech corpus uttered by a professional male announcer. The prosodic boundaries were manually marked on the recorded speech, and word identification, part-of-speech tagging and syntactic analysis were also done on the text. A decision tree was then trained on 371 sentences (of approximately 50 min length), and tested on 188 sentences (of approximately 28 min length). Features for modeling prosody are proposed, and their effectiveness is measured by interpreting the resulting tree. We achieved a success rate of about 93%.
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© 2001 Springer-Verlag Berlin Heidelberg
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Chen, W., Linn, F., Li, J., Zhangh, B. (2001). A Tree-Based Model of Prosodic Phrasing for Chinese Text-to-Speech Systems. In: Shum, HY., Liao, M., Chang, SF. (eds) Advances in Multimedia Information Processing — PCM 2001. PCM 2001. Lecture Notes in Computer Science, vol 2195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45453-5_143
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DOI: https://doi.org/10.1007/3-540-45453-5_143
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