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Ubiquitous and Robust Text-Independent Speaker Recognition for Home Automation Digital Life

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Part of the book series:Lecture Notes in Computer Science ((LNISA,volume 5061))

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Abstract

This paper presents a ubiquitous and robust text-independent speaker recognitionarchitecture for home automation digital life. In this architecture, a multiple microphone configuration is adopted to receive the pervasive speech signals. The multi-channel speech signals are then added together with a mixer. In a ubiquitous computing environment, the received speech signal is usually heavily corrupted by background noises. An SNR-aware subspace speech enhancement approach is used as a pre-processing to enhance the mixed signal. Considering the text-independent speaker recognition, this paper applies a multi-class support vectors machine (SVM)[10][11] instead of conventional Gaussian mixture models (GMMs)[12]. In our experiments, the speaker recognition rate can averagely reach 97.2% with the proposed ubiquitous speaker recognitionarchitecture.

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Authors and Affiliations

  1. Department of Electrical Engineering, National Cheng-Kung University, No.1, Dasyue Rd., East District, Tainan City, 701, Taiwan, R.O.C.

    Jhing-Fa Wang, Ta-Wen Kuan, Jia-chang Wang & Gaung-Hui Gu

Authors
  1. Jhing-Fa Wang

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  2. Ta-Wen Kuan

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  3. Jia-chang Wang

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  4. Gaung-Hui Gu

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Editor information

Frode Eika Sandnes Yan Zhang Chunming Rong Laurence T. Yang Jianhua Ma

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© 2008 Springer-Verlag Berlin Heidelberg

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Wang, JF., Kuan, TW., Wang, Jc., Gu, GH. (2008). Ubiquitous and Robust Text-Independent Speaker Recognition for Home Automation Digital Life. In: Sandnes, F.E., Zhang, Y., Rong, C., Yang, L.T., Ma, J. (eds) Ubiquitous Intelligence and Computing. UIC 2008. Lecture Notes in Computer Science, vol 5061. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69293-5_24

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