在扬声器验证中对抗混响

J. Gammal, R. Goubran
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引用次数: 28

摘要

本文研究了说话人验证中的混响问题。混响测试语音会降低说话人验证算法的性能。研究了不同于测试语音的混响环境下的语音训练效果。研究发现,在使用房间脉冲响应的情况下,使用比测试演讲更少混响的演讲进行训练总是能提高表现。针对给定一组混响训练语音片段被不同的传递函数破坏的情况,提出了一种判断传递函数是否破坏语音的方法。分类率达96.5%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combating Reverberation in Speaker Verification
This paper investigates reverberation in speaker verification. Reverberant test speech degrades the performance of speaker verification algorithms. The effect of training with speech originating from reverberant environments that are different from that of the test speech is investigated. It was found that with the room impulse responses used, that training with speech that is less reverberant than the test speech always improved performance. A method was proposed to determine given a set of reverberant training speech segments corrupted with different transfer functions, which transfer function corrupted the speech. A classification rate of 96.5% was achieved
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