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. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Wang, J. F., Kuan, T. W., Wang, J. C., & Gu, G. H. (2008). Ubiquitous and robust text-independent speaker recognition for home automation digital life. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5061 LNCS, pp. 297–310). https://doi.org/10.1007/978-3-540-69293-5_24
Mendeley helps you to discover research relevant for your work.