Speaker recognition based on improved ECAPA-TDNN network

Hongyan Chen, Xiaoming Ling, Xiaoyu Zhang, Zhen Zhang, Zeifei Dang, Xiang Ji
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Abstract

Speaker recognition, also known as voiceprint recognition, is a biometric technology with wide practicability at present. This paper summarizes and compares and analyzes the main research methods of speaker recognition at home and abroad at this stage, and proposes an improved ECAPA_TDNN algorithm. It is proved by experiments that the improved ECAPA_TDNN algorithm in this paper is superior to the classical algorithm in terms of accuracy and loss.
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基于改进ECAPA-TDNN网络的说话人识别
说话人识别又称声纹识别,是目前具有广泛实用性的一种生物识别技术。本文对现阶段国内外主要的说话人识别研究方法进行了总结和比较分析,提出了一种改进的ECAPA_TDNN算法。实验证明,本文改进的ECAPA_TDNN算法在准确率和损失方面都优于经典算法。
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