Abstract

This chapter presents a statistical decision procedure for lexical ambiguity resolution in text-to-speech synthesis. Based on decision lists, the algorithm incorporates both local syntactic patterns and more distant collocational evidence, combining the strengths of decision trees, N-gram taggers and Bayesian classifiers. The algorithm is applied to 7 major types of ambiguity where context can be used to choose a word's pronunciation.

Citations

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