基于统计方法的普通话情感语调模型

提出了一种基于数据驱动的语调建模方法．该方法采用主成分分析 (Principal component analysis, PCA) 技术, 给出了特征语调, 统计了语音情感模式在特征语调空间中的分布规律, 经过分析得出了普通话中情感模式所对应的情感语调．针对语音产生的机理复杂、语音语调受众多因素影响的特点, 为了避免这些干扰因素的影响, 设计了相应的情感语音库．利用所设计的语音库, 进行了相关实验．实验结果表明, 利用所提出的特征语调模型不仅能够非常完美地重构出语调样本的语调, 而且具有相当的情感表达能力．

Affective Intonation-modeling for Mandarin by Statistical Method

This paper proposes a data-driven intonation modeling method.With the principal component analysis (PCA)technique,the concept of eigenintonation is presented.The distribution of emotional states in the eigenintonation space is then studied and the corresponding emotional intonations in Mandarin are given out.In order to avoid the influences caused by the unwanted factors,the affective corpora for the purpose of evaluation are designed.With the corpora,the related experiments have been performed.The experimental results show that the eigenintonation model has a quite good ability of expressing emotions,and all intonation samples in our corpora can be well recovered with the eigenintonations.