<link rel="stylesheet" href="styles.cf390c6bfbe7555f.css"> Skip to main content

Chinese dialect identification using segmental and prosodic features

dc.citation.epage1913en_US
dc.citation.issue4en_US
dc.citation.spage1906en_US
dc.citation.volume108en_US
dc.citation.woscount2
dc.contributor.authorChang, WWen_US
dc.contributor.authorTsai, WHen_US
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.date.accessioned2014-12-08T15:44:46Z
dc.date.available2014-12-08T15:44:46Z
dc.date.issued2000-10-01en_US
dc.description.abstractSeveral approaches to Chinese dialect identification based on segmental and prosodic features of speech are described in this paper. When using segmental information only, the system performs phonotactic analysis after speech utterances have been tokenized into sequences of broad phonetic classes. The second scheme comprises prosodic models which are trained to capture tone sequence information for individual dialects. Also proposed is a novel approach that examines differences between Chinese dialects at broad phonetic and prosodic levels. These algorithms were evaluated via a multispeaker read-speech mode. Simulation results indicate that the combined use of Segmental and prosodic features allows the proposed system to discriminate among three major Chinese dialects spoken in Taiwan with 93.0% accuracy. (C) 2000 Acoustical Society of America. [S0001-4966(oo)03410-X].en_US
dc.identifier.doi10.1121/1.1289923en_US
dc.identifier.issn0001-4966en_US
dc.identifier.journalJOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICAen_US
dc.identifier.urihttp://dx.doi.org/10.1121/1.1289923en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/30228
dc.identifier.wosnumberWOS:000089894700053
dc.language.isoen_USen_US
dc.titleChinese dialect identification using segmental and prosodic featuresen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
000089894700053.pdf
Size:
245.49 KB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed to upon submission
Description: