Text-Independent Speaker Recognition Using Neural Networks

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概要

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• This paper describes a text-independent speaker recognition method using predictive neural networks. For text-independent speaker recognition, an ergodic model which allows transitions to any other state, including self-transitions, is adopted as the speaker model and one predictive neural network is assigned to each state. The proposed method was compared to quantization distortion based methods, HMM based methods, and a discriminative neural network based method through text-independent speaker identification experiments on 24 female speakers. The proposed method gave the highest identification rate of 100.0%, and the effectiveness of predictive neural networks for representing speaker individuality was clarified.

• 一般社団法人電子情報通信学会の論文
• 1993-03-25

著者

• Hattori Hiroaki

  ATR Interpreting Telephony Research Laboratories

関連論文

• Speaker Weighted Training of HMM Using Multiple Reference Speakers
• Speaker Adaptation Based on Vector Field Smoothing
• Text-Independent Speaker Recognition Using Neural Networks

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