摘要
针对基于单元挑选的汉语语音合成系统中重音预测及实现,本文采用了知识指导下的数据驱动建模策略。首先,采用经过感知结果优化的重音检测器,实现了语音数据库的自动标注;其次,利用重音标注数据库,训练得到支持重音预测的韵律预测模型;用重音韵律预测模型替代原语音合成系统中的相应模型,从而构成了支持重音合成的语音合成系统。实验结果分析表明,基于感知结果优化的重音检测器的标注结果是可靠的;支持重音的韵律声学预测模型是合理的;新的合成系统能够合成出带有轻重变化的语音。
To aim to predict and realize Chinese accent in a unit-selection based speech synthesis system, a data-driven method was used to build an accent-supported prosody module. First, with the help of Accent-Index detector which had been optimized with perceptual annotations, a speech corpus had been auto-annotated with Accent-Index. Then, a prosody predictive module supporting accent had been trained with the corpus. Replaced with the new prosody predictive module, the speech synthesis system could synthesize speech with various levels of accent. The resuits on the experiments had proved the accuracy of auto-detected accents, and the validity of the prosody predictor, and also the capability of accent realizing of the speech synthesis system.
出处
《中文信息学报》
CSCD
北大核心
2007年第3期122-128,共7页
Journal of Chinese Information Processing
关键词
计算机应用
中文信息处理
重音
韵律模型
语音合成
computer application
Chinese information processing
accent
prosodic model
speech synthesis