Application of Codebooks Clustering Vector Quantization Algorithm to Speaker Recognition
Journal Title: 河南科技大学学报（自然科学版） - Year 2016, Vol 37, Issue 1
Abstract
The vector quantization algorithm used in the speaker recognition system required full search of the existing codebooks in matching and recognition. The calculation time of full search was increased while the number of speaker increased,which impacted the performance of the system and was not conducive to the design and application of system on chip. In order to solve this problem,a codebooks clustering vector quantization algorithm was proposed in this paper. By clustering the codebooks obtained by the training algorithm,the classification of codebooks and eigen matrices of each cluster was obtained. In the matching and recognition step,the sub-category of unknown speaker was determined firstly,and then the unknown speaker voice feature was matched with the codebooks in the sub-category. At last,the speaker identity was determined. In this way the calculation time of matching with other impossible category codebooks was reduced. The results of experiments show that the optimal codebooks clustering algorithm can achieve a false recognition rate no more than 5. 00%,just by using 42. 56% calculation times of full search algorithm.
Authors and Affiliations
Bairui TAO, Qinglong LI, Fengjuan MIAO, Qin GUO, Hui SHAO
Keywords
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- EP ID EP459936
- DOI 10.15926/j.cnki.issn1672-6871.2016.01.008
- Views 86
- Downloads 0
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