Automatic speech-based classification of gender, age and accent

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6 Citations (Scopus)


This paper presents an automatic speech-based classification scheme to classify speaker characteristics. In the training phase, speech data are grouped into speaker groups according to speakers’ gender, age and accent. Voice features are then extracted to feature vectors which are used to train speaker characteristic models with different techniques which are Vector Quantization, Gaussian Mixture Model and Support Vector Machine. Fusion of classification results from those groups is then performed to obtain final classification results for each characteristic. The Australian National Database of Spoken Language (ANDOSL) corpus was used for evaluation of gender, age and accent classification. Experiments showed high performance for the proposed classification scheme
Original languageEnglish
Title of host publication11th International Workshop, PKAW 2010
EditorsB. H. Kang, D. Richards
Place of PublicationGermany
Number of pages12
ISBN (Print)9783642150364
Publication statusPublished - 2010
Event11th International Workshop, PKAW 2010 - Daegu, Korea, Republic of
Duration: 20 Aug 20103 Sept 2010


Conference11th International Workshop, PKAW 2010
Country/TerritoryKorea, Republic of


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