This paper presents a ubiquitous and robust text-independent speaker recognition architecture 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 recognition architecture.
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