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Automatic Speech-Based Classification of Gender, Age and Accent

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Book cover Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6232))

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Abstract

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.

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Authors and Affiliations

  1. Faculty of Information Sciences and Engineering, University of Canberra, ACT 2601, Australia

    Phuoc Nguyen, Dat Tran, Xu Huang & Dharmendra Sharma

Authors
  1. Phuoc Nguyen
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  2. Dat Tran
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  3. Xu Huang
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  4. Dharmendra Sharma
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Editor information

Editors and Affiliations

  1. School of Computing ad Information Systems, University of Tasmania, TAS7250, Launceton, Tasmania, Australia

    Byeong-Ho Kang

  2. Computing Department,Division of Information and Communication Sciences, Macquarie University, 2109, Sydney, NSW, Australia

    Debbie Richards

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Nguyen, P., Tran, D., Huang, X., Sharma, D. (2010). Automatic Speech-Based Classification of Gender, Age and Accent. In: Kang, BH., Richards, D. (eds) Knowledge Management and Acquisition for Smart Systems and Services. PKAW 2010. Lecture Notes in Computer Science(), vol 6232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15037-1_24

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  • DOI: https://doi.org/10.1007/978-3-642-15037-1_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15036-4

  • Online ISBN: 978-3-642-15037-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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