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Comparison of speech enhancement algorithms for forensic applications

机译:司法鉴定中语音增强算法的比较

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摘要

Speech enhancement algorithms play an essential role in forensic applications, and enhanced speech signals can be used in court as evidence in criminal cases. This paper compares the performance of single channel (spectral subtraction and level dependent wavelet threshold techniques) and multiple channel (independent component analysis or ICA) speech enhancement algorithms to remove real environmental noise from noisy audio recording signals. Experimental results demonstrate that ICA achieves a significant improvement in average signal to noise ratio (SNR) enhancement compared to single channel speech enhancement algorithms, when 100 sentences from a forensic voice comparison database were corrupted with a car, street and factory noise at input SNR (-10 to 10 dB).
机译:语音增强算法在法证应用中起着至关重要的作用,增强的语音信号可以在法庭上用作刑事案件的证据。本文比较了单通道(频谱减法和与水平相关的小波阈值技术)和多通道(独立分量分析或ICA)语音增强算法的性能,这些算法可从嘈杂的音频记录信号中消除真实的环境噪声。实验结果表明,与法医学相比,当取证语音比较数据库中的100个句子在输入SNR处受到汽车,街道和工厂噪声的破坏时,ICA的平均信噪比(SNR)增强效果显着提高。 -10至10 dB)。

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