Classification of Pitch Disguise Level with Artificial Neural Networks

Thiramdas Narendra, Athulya M S, Sathidevi P S
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引用次数: 4

Abstract

In audio forensics, voice disguise raises many serious challenges in finding the criminal suspects. Most of the criminals usually disguise their voice just before and/or after committing a crime. Hence, to perform forensic speaker verification, original voice is to be recovered from the disguised voice. Pitch disguise is one type of voice disguise which results in very low speaker recognition rate compared to other types of disguises. Original voice can be easily recovered from the pitch disguised voice if the level of disguise is known. Hence, this paper proposes a novel technique for finding the level of pitch disguise using Artificial Neural Networks (ANN) modelling. The performance of the system is measured in terms of accuracy and the proposed technique gives an accuracy of 96.23%
基于人工神经网络的基音伪装等级分类
在音频取证中,语音伪装对寻找犯罪嫌疑人提出了许多严峻的挑战。大多数罪犯通常在犯罪前后伪装自己的声音。因此,要进行法医说话人鉴定,就要从被伪装的声音中恢复原声。音高伪装是语音伪装的一种,与其他伪装相比,音高伪装的说话人识别率很低。如果知道音高伪装的程度,可以很容易地从音高伪装的声音中恢复原声。因此,本文提出了一种利用人工神经网络(ANN)建模来寻找音高伪装水平的新技术。系统的性能以精度来衡量,所提出的技术的精度为96.23%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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