基于数据驱动方法的汉语文本-可视语音合成

计算机文本-可视语音合成系统(TTVS)可以增强语音的可懂度,并使人机交互界面变得更为友好.给出一个基于数据驱动方法(基于样本方法)的汉语文本-可视语音合成系统,通过将小段视频拼接生成新的可视语音.给出一种构造汉语声韵母视觉混淆树的有效方法,并提出了一个基于视觉混淆树和硬度因子的协同发音模型,模型可用于分析阶段的语料库选取和合成阶段的基元选取.对于拼接边界处两帧图像的明显差别,采用图像变形技术进行平滑并.结合已有的文本-语音合成系统(TTS),实现了一个中文文本视觉语音合成系统.

Text-To-Visual Speech in Chinese Based on Data-Driven Approach

Text-To-Visual speech (TTVS) synthesis by computer can increase the speech intelligibility and make the human-computer interaction interfaces more friendly. This paper describes a Chinese text-to-visual speech synthesis system based on data-driven (sample based) approach, which is realized by short video segments concatenation. An effective method to construct two visual confusion trees for Chinese initials and finals is developed. A co-articulation model based on visual distance and hardness factor is proposed, which can be used in the recording corpus sentence selection in analysis phase and the unit selection in synthesis phase. The obvious difference between bound ary images of the concatenation video segments is smoothed by image morphing technique. By combining with the acoustic Text-To-Speech (TTS) synthesis, a Chinese text-to-visual speech synthesis system is realized.