关键词: 多音字消歧, 字音转换, 决策树, 基于转换的错误驱动的学习（TBL）

Abstract: Polyphone disambiguation is the core issue of the grapheme-to-phoneme conversion in Mandarin Text-To-Speech（TTS） system.This paper selects 33 key polyphones and 24 key polyphonic words which are most ambiguous and frequently used as study objects，and builds a polyphone corpus of 5 000 sentences per polyphone on average.Furthermore，a hybrid algorithm called Tree-Guided Transformation-Based Learning（TGTBL），which combines decision tree with Transformation-Based error-driven Learning（TBL），is proposed to resolve the polyphonic ambiguity.It automatically generates TBL templates，thereby avoiding manually summarizing templates，which is time-consuming and laborious in conventional TBL.Results of comparative experiments show that，for the task of polyphone disambiguation，templates automatically generated by decision tree achieve comparable performance to manually summarized templates，and the average precision of TGTBL reaches 90.36%，significantly higher than that of decision tree.

Key words: polyphone disambiguation, grapheme-to-phoneme, decision tree, Transformation-Based error-driven Learning（TBL）