Automatic Detection of Prosody Phrase Boundaries for Text-to-Speech System
نویسندگان
چکیده
Automatic acquisition of the prosodic phrase boundary detecting rules from the text and speech corpora has always been a difficulty for TTS systems. We collected over 5,000 sentences as the corpus, introduced a method based on the transform-based error-driven learning to get the rules for detecting prosodic phrase boundaries, and then used trees to organize the rules in the TTS system. For using the transformation-based error-driven learning, we designed a set of templates especially. Using 1,000 sentences to get rules for the TTS system can reach 92% accuracy in close-test and 73% accuracy in open-test.
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