Abstract
This work proposes a dynamic fixed-point arithmetic design for SVM-based speaker identification in embedded environment. The whole speaker identification system includes LPCC extraction, SVM training with sequential minimal optimization (SMO), and SVM recognition. The proposed dynamic fixed-point design is applied to each arithmetic procedure and fixed-point error analysis is also performed. The fixed-point SVM-based speaker identification system have been implemented and evaluated on ARM9 DMA2400. The experimental results show that the speaker identification accuracy is slightly degraded with the proposed dynamic fixed-point technique.
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Wang, JF., Kuan, TW., Wang, JC., Sun, TW. (2010). Dynamic Fixed-Point Arithmetic Design of Embedded SVM-Based Speaker Identification System. In: Zhang, L., Lu, BL., Kwok, J. (eds) Advances in Neural Networks - ISNN 2010. ISNN 2010. Lecture Notes in Computer Science, vol 6064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13318-3_65
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DOI: https://doi.org/10.1007/978-3-642-13318-3_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13317-6
Online ISBN: 978-3-642-13318-3
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