基於發音知識以建構頻譜HMM 之國語語音合成方法 (A Mandarin Speech Synthesis Method Using Articulation-knowledge Based Spectral HMM Structure)[In Chinese]

Abstract

In this paper, a new HMM structure is proposed to work with a limited training corpus in order to obtain improved synthetic-speech fluency. Spectral fluency is improved because this HMM structure can model the context-dependent spectral characteristics of a speech unit. In addition, instead of using a decision tree to cluster contexts, the knowledge of phoneme articulation is based to cluster contexts and reduce the enormous quantity of context combinations. To evaluate the proposed HMM structure, we construct three Mandarin speech synthesis systems each uses one different HMM structure for comparisons. In these systems, the prosodic parameters are all generated with same ANN modules studied previously 國立臺灣科技大學資訊工程系 Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology E-mail: {guhy, M9615074, M10115035, M10215005}@mail.ntust.edu.tw

Cite this paper

@inproceedings{Gu2014HMM, title={基於發音知識以建構頻譜HMM 之國語語音合成方法 (A Mandarin Speech Synthesis Method Using Articulation-knowledge Based Spectral HMM Structure)[In Chinese]}, author={Hung-Yan Gu and Ming-Yen Lai and Wei-Siang Hong and Yan-Hua Chen}, booktitle={ROCLING}, year={2014} }