{"title":"On analysis of eigenpitch in Mandarin Chinese","authors":"Jilei Tian, J. Nurminen","doi":"10.1109/CHINSL.2004.1409593","DOIUrl":null,"url":null,"abstract":"Prosody is an inherent supra-segmental feature of human speech that is being employed to express, e.g., attitude, emotion, intent and attention. Pitch is the most important feature among the prosodic information. For Mandarin Chinese speech, the pitch information is even more crucial because Mandarin is a tonal language in which the tone of each syllable is described by its pitch contour. In this paper, the concept of syllable-based eigenpitch is introduced and investigated using principal component analysis (PCA). The eigenpitch and the related eigenfeatures are analyzed, and it is shown that the tonal patterns are preserved in the eigenpitch representation. Furthermore, we show that the dimension of pitch in the eigenspace can be reduced while minimizing the energy loss of the original pitch contour. Finally, we briefly discuss the quantization properties of the eigenpitch representation. We also present experimental results obtained using a Mandarin speech database. They are in line with the theoretical reasoning and further prove the usefulness of the proposed pitch modeling technique.","PeriodicalId":212562,"journal":{"name":"2004 International Symposium on Chinese Spoken Language Processing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Symposium on Chinese Spoken Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CHINSL.2004.1409593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Prosody is an inherent supra-segmental feature of human speech that is being employed to express, e.g., attitude, emotion, intent and attention. Pitch is the most important feature among the prosodic information. For Mandarin Chinese speech, the pitch information is even more crucial because Mandarin is a tonal language in which the tone of each syllable is described by its pitch contour. In this paper, the concept of syllable-based eigenpitch is introduced and investigated using principal component analysis (PCA). The eigenpitch and the related eigenfeatures are analyzed, and it is shown that the tonal patterns are preserved in the eigenpitch representation. Furthermore, we show that the dimension of pitch in the eigenspace can be reduced while minimizing the energy loss of the original pitch contour. Finally, we briefly discuss the quantization properties of the eigenpitch representation. We also present experimental results obtained using a Mandarin speech database. They are in line with the theoretical reasoning and further prove the usefulness of the proposed pitch modeling technique.