Perceptual Optimization of the Chinese Accent-Index Detector

For a TTS system, only if a large size of corpus annotated with AI (Accent Index) is available, could it be practicable to build an AI-supported prosody module in a data-driven method. An approach had been proposed to label Chinese AI automatically. Although preliminary experiments showed its effectiveness and efficiency of the approach, there are still certain issues left unsolved: the evaluation and the optimization of the AI detector. A small size of sub-corpus has been labeled with AI manually, which is expected to be as a reference for evaluating the performance. And a measure CC (Correlative-Coefficient), the CC between the auto-detected and the manual-annotated AI set, is proposed as the criteria for optimizing the detector. Thanks to the use of CC, the detector has not only been refined and optimized, but also the autodetected AI has been assigned with prosody meaning subjectively.