混合PSO-ANFIS用于说话人识别

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Cognitive Informatics and Natural Intelligence Pub Date : 2021-04-01 DOI:10.4018/ijcini.20210401.oa7

Samiya Silarbi, R. Tlemsani, A. Bendahmane

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引用次数: 1

摘要

介绍了一种基于自适应网络的模糊推理系统(ANFIS)的进化训练方法。之前的工作都是基于梯度下降法(GD);该算法收敛速度很慢，并且在局部极小值处陷入困境。本研究采用群体智能分支之一粒子群优化(particle swarm optimization, PSO)，其中规则的前提参数由粒子群优化，结论部分由最小二乘估计(least squares estimation, LSE)优化。采用混合PSO-ANFIS模型对链语音数据集上的说话人进行识别。与基于梯度下降优化的同类ANFIS相比，混合模型的精度得到了提高。

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Hybrid PSO-ANFIS for Speaker Recognition

This paper introduces an evolutionary approach for training the adaptive network-based fuzzy inference system (ANFIS). The previous works are based on gradient descendent (GD); this algorithm converges very slowly and gets stuck down at bad local minima. This study applies one of the swarm intelligent branches, named particle swarm optimization (PSO), where the premise parameters of the rules are optimized by a PSO, and the conclusion part is optimized by least-squares estimation (LSE). The hybrid PSO-ANFIS model is performed for speaker recognition on CHAINS speech dataset. The results obtained by the hybrid model showed an improvement on the accuracy compared to similar ANFIS based on gradient descendent optimization.

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来源期刊

International Journal of Cognitive Informatics and Natural Intelligence COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

2.00

自引率

11.10%

发文量

期刊介绍： The International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) encourages submissions that transcends disciplinary boundaries, and is devoted to rapid publication of high quality papers. The themes of IJCINI are natural intelligence, autonomic computing, and neuroinformatics. IJCINI is expected to provide the first forum and platform in the world for researchers, practitioners, and graduate students to investigate cognitive mechanisms and processes of human information processing, and to stimulate the transdisciplinary effort on cognitive informatics and natural intelligent research and engineering applications.