基于语音知识的音节切分

Syllable Segmentation Based on Chinese Speech Knowledge

在充分利用普通话水平测试试卷的文本信息、同一人的声母时长在常规语速下基本稳定、同一人的声母之间以及韵母之间的相对时长基本保持比例关系等先验知识的基础上,使用经小波变换后再重构的3个语音信号分量的累计能量特征为参数,提出了利用话者语音统计信息的两级音节切分算法,使音节切分精度达98.3%以上。

Many kinds of knowledge have been applied in this paper to separate the syllables,such as the prior information from the standard text of speech in Mandarin proficiency test,from the duration of initial in Mandarin speech which is stable in the normal speed speech,from the proportions of initials＇ durations in related to the finals＇ durations in one＇s speech and so on.A two-level syllable segmentation algorithm is proposed by using accumulating energies of the three wavelets which are re-constructured from wavelet transform.The experimental results demonstrat that the accuracy of syllable separation reaches to 98.3% at least.