An Enhanced Text Analysis Approach in Text-to-Speech Synthesis for Mandarin Chinese

An enhanced text analysis approach for Chinese text- to-speech (TTS) systems is presented in this paper, as the basic understanding process, the text analysis need provide a fine and effective linguistic information, which is marked explicitly with the corresponding notation. Two kinds of work are done to improve the TTS performance. Firstly, the shallow parsing information is introduced, which is processed by the conditional random fields, accordingly, the label bias problem is overcome; Secondly, considering the dictionary is very important not only in the Chinese word segmentation, but also in the Pinyin-to-Character conversion, we present a semi-automatic word extraction approach for general dictionary and the specialty dictionaries based on Information Entropy. The experiments show that CRF achieved 1.09% improvement in POS tagging task, and 0.67% in shallow parsing task in terms of F-measure. The specialty words can increases the precision by 1.80% to the word segmentation.