基于韵律特征和语法信息的韵律边界检测模型

韵律短语边界的自动检测,对语音合成中语料库的韵律标注以及语音识别中韵律短语的自动划分都有重要意义。本文通过对影响韵律短语边界的声学、韵律等参量的分析,得到和韵律短语边界关联性较大的一组声学特征参数、韵律环境参数和语法信息;同时引入语音合成中的韵律预测思想,在假定所有音节边界均为非韵律短语边界时,预测每个音节的基频。最后使用决策树模型,将音节边界处的韵律环境信息、语法信息以及预测结果作为决策树的输入,利用决策树综合判定当前音节边界是否为韵律短语的边界。实验表明,这种方法对于基于确定性文本(text-dependent)的语音韵律短语边界的检测,具有较好效果,同时可以显著提高语音合成中语料库的标注效率和标注结果的一致性。

Detection Model of Prosodic Boundary Based on Prosodic Features and Syntactic Information

Automatic detection of prosodic boundary for continuous speech is very useful for labeling corpus in TTS system and for separating phrase in speech recognition. we propose an automatic break detection algorithm for mandarin Chinese speech. Our labeling model includes following steps : Firstly acoustic parameters are analyzed to select some useful parameters for detection model. Then relationship between syntactic information and prosodic word is obtained by statistical method. At the same time F0 value is estimated by F0 prediction model , in which all of syllable boundary is assumed as non-prosodic boundary. Finally all of the acoustic parameters、syntactic information and estimated F0 value are input into the decision tree for predicting potential prosodic word boundary. Experiments show this detection model can speed manual labeling of prosodic boundary and had little impact to label assignment .