Australian accent-based speaker classification

Research output: A Conference proceeding or a Chapter in BookConference contribution

6 Citations (Scopus)
13 Downloads (Pure)

Abstract

An automatic voice-based classification system of speaker characteristics including age, gender and accent is presented in this paper. Speakers are grouped according to their characteristics and their speech features are then extracted to train speaker group models using different classification techniques. Finally fusion of classification results for those speaker groups is performed to obtain results for each speaker characteristic. The ANDOSL Australian speech database consisting of 108 speakers and 21600 long utterances was used for system evaluation. Experiments showed high performance for the proposed classification of speaker characteristics.
Original languageEnglish
Title of host publication2010 Third International Conference on Knowledge Discovery and Data Mining: WKDD 2010
Place of PublicationPiscataway, N.J., USA
PublisherIEEE
Pages416-419
Number of pages4
ISBN (Print)9781424470556
DOIs
Publication statusPublished - 2010
Event2010 The 3rd International Conference on Knowledge Discovery and Data Mining (WKDD 2010) - Phuket, Thailand
Duration: 9 Jan 201010 Jan 2010

Conference

Conference2010 The 3rd International Conference on Knowledge Discovery and Data Mining (WKDD 2010)
CountryThailand
CityPhuket
Period9/01/1010/01/10

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Cite this

Tran, D., Huang, X., & Sharma, D. (2010). Australian accent-based speaker classification. In 2010 Third International Conference on Knowledge Discovery and Data Mining: WKDD 2010 (pp. 416-419). Piscataway, N.J., USA: IEEE. https://doi.org/10.1109/WKDD.2010.80
Tran, Dat ; Huang, Xu ; Sharma, Dharmendra. / Australian accent-based speaker classification. 2010 Third International Conference on Knowledge Discovery and Data Mining: WKDD 2010. Piscataway, N.J., USA : IEEE, 2010. pp. 416-419
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title = "Australian accent-based speaker classification",
abstract = "An automatic voice-based classification system of speaker characteristics including age, gender and accent is presented in this paper. Speakers are grouped according to their characteristics and their speech features are then extracted to train speaker group models using different classification techniques. Finally fusion of classification results for those speaker groups is performed to obtain results for each speaker characteristic. The ANDOSL Australian speech database consisting of 108 speakers and 21600 long utterances was used for system evaluation. Experiments showed high performance for the proposed classification of speaker characteristics.",
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Tran, D, Huang, X & Sharma, D 2010, Australian accent-based speaker classification. in 2010 Third International Conference on Knowledge Discovery and Data Mining: WKDD 2010. IEEE, Piscataway, N.J., USA, pp. 416-419, 2010 The 3rd International Conference on Knowledge Discovery and Data Mining (WKDD 2010), Phuket, Thailand, 9/01/10. https://doi.org/10.1109/WKDD.2010.80

Australian accent-based speaker classification. / Tran, Dat; Huang, Xu; Sharma, Dharmendra.

2010 Third International Conference on Knowledge Discovery and Data Mining: WKDD 2010. Piscataway, N.J., USA : IEEE, 2010. p. 416-419.

Research output: A Conference proceeding or a Chapter in BookConference contribution

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N2 - An automatic voice-based classification system of speaker characteristics including age, gender and accent is presented in this paper. Speakers are grouped according to their characteristics and their speech features are then extracted to train speaker group models using different classification techniques. Finally fusion of classification results for those speaker groups is performed to obtain results for each speaker characteristic. The ANDOSL Australian speech database consisting of 108 speakers and 21600 long utterances was used for system evaluation. Experiments showed high performance for the proposed classification of speaker characteristics.

AB - An automatic voice-based classification system of speaker characteristics including age, gender and accent is presented in this paper. Speakers are grouped according to their characteristics and their speech features are then extracted to train speaker group models using different classification techniques. Finally fusion of classification results for those speaker groups is performed to obtain results for each speaker characteristic. The ANDOSL Australian speech database consisting of 108 speakers and 21600 long utterances was used for system evaluation. Experiments showed high performance for the proposed classification of speaker characteristics.

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DO - 10.1109/WKDD.2010.80

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BT - 2010 Third International Conference on Knowledge Discovery and Data Mining: WKDD 2010

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Tran D, Huang X, Sharma D. Australian accent-based speaker classification. In 2010 Third International Conference on Knowledge Discovery and Data Mining: WKDD 2010. Piscataway, N.J., USA: IEEE. 2010. p. 416-419 https://doi.org/10.1109/WKDD.2010.80