{"title":"Speaker adaptation of speaking rate-dependent hierarchical prosodic model for Mandarin TTS","authors":"Po-Chun Wang, I-Bin Liao, Chen-Yu Chiang, Yih-Ru Wang, Sin-Horng Chen","doi":"10.1109/ISCSLP.2014.6936616","DOIUrl":null,"url":null,"abstract":"In this paper, a speaker adaptation method to adapt an existing speaking rate-dependent hierarchical prosodic model (SR-HPM) of an SR-controlled Mandarin TTS system to new speaker's data for realizing a new voice is proposed. Two main problems are addressed: data sparseness for few adaptation utterances existing only in a small range of normal speaking rate and no adaptation data in both ranges of fast and slow speaking rates. The proposed method follows the idea of SR-HPM training to firstly normalize the prosodic-acoustic features of the new speaker's speech data, to then train an HPM by the prosody labeling and modeling algorithm, and to lastly refine the HPM to an SR-dependent model. The MAP adaptation method with model parameter extrapolation is applied to cope with the above two problems. Experimental results on a male speaker's adaptation data confirmed that the resulting adaptive SR-HPM has reasonable parameters covering a wide range of speaking rates and hence can be used in the TTS system to generate prosodic-acoustic features for synthesizing the new speaker's voice of any given SR.","PeriodicalId":271277,"journal":{"name":"International Symposium on Chinese Spoken Language Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Chinese Spoken Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCSLP.2014.6936616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In this paper, a speaker adaptation method to adapt an existing speaking rate-dependent hierarchical prosodic model (SR-HPM) of an SR-controlled Mandarin TTS system to new speaker's data for realizing a new voice is proposed. Two main problems are addressed: data sparseness for few adaptation utterances existing only in a small range of normal speaking rate and no adaptation data in both ranges of fast and slow speaking rates. The proposed method follows the idea of SR-HPM training to firstly normalize the prosodic-acoustic features of the new speaker's speech data, to then train an HPM by the prosody labeling and modeling algorithm, and to lastly refine the HPM to an SR-dependent model. The MAP adaptation method with model parameter extrapolation is applied to cope with the above two problems. Experimental results on a male speaker's adaptation data confirmed that the resulting adaptive SR-HPM has reasonable parameters covering a wide range of speaking rates and hence can be used in the TTS system to generate prosodic-acoustic features for synthesizing the new speaker's voice of any given SR.