DocumentCode :
430194
Title :
On analysis of eigenpitch in Mandarin Chinese
Author :
Tian, Jilei ; Nurminen, Jani K.
Author_Institution :
Multimedia Technol. Lab., Nokia Res. Center, Tampere, Finland
fYear :
2004
fDate :
15-18 Dec. 2004
Firstpage :
89
Lastpage :
92
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.
Keywords :
eigenvalues and eigenfunctions; feature extraction; frequency estimation; linguistics; minimisation; principal component analysis; signal representation; speech coding; speech recognition; speech synthesis; Mandarin Chinese speech; Mandarin speech database; PCA; attention; attitude; eigenfeatures; eigenpitch analysis; eigenpitch representation; emotion; energy loss minimization; human speech; intent; pitch contour; pitch modeling; principal component analysis; prosody; quantization properties; supra-segmental feature; syllable-based eigenpitch; tonal language; tonal patterns; Africa; Asia; Energy loss; Laboratories; Natural languages; Pattern analysis; Principal component analysis; Quantization; Spatial databases; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Chinese Spoken Language Processing, 2004 International Symposium on
Print_ISBN :
0-7803-8678-7
Type :
conf
DOI :
10.1109/CHINSL.2004.1409593
Filename :
1409593
Link To Document :
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