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A New Robust Hybrid Approach to Enhance Speech in Mobile Communication Systems | Science Publications

机译:增强移动通信系统语音能力的新型鲁棒混合方法科学出版物

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> Problem statement: The received voice signal in mobile communication is often disturbed by background noise and hence there is a need for good noise reduction methods for enhancing Speech. It is well known that denoising is a compromise between the removal of the largest possible amount of noise and the preservation of signal integrity. To address this issue, a new method for enhancing speech from background interference is presented in this study by fusing dual band spectral subtraction with adaptive noise estimator and wavelet packet based thresholding method. Approach: The proposed system uses the combination of dual band Spectral Subtraction method with adaptive noise estimator for pre-processing, in order to initially reduce the noise level and further the quality of speech is improved by Wavelet Packet Transform (WPT) based level dependent thresholding method. The threshold value is determined by using Steins Unbiased Risk Estimator (SURE) and hard, soft, Garrotte, µ-law and a proposed modified soft thresholding functions are considered for denoising. Results: The proposed method was investigated by ten different clean speech samples (five male and five female) taken from TIMIT database and thirteen different noise sources to degrade the speech artificially and the energy level of the noise is scaled such that the overall SNR of the noisy speech is maintained at -5, 0,5,10 and 15 dB and finally the results are evaluated using objective and subjective measures. Conclusion/Recommendations: It is suggested from the experimental results that the proposed scheme gives improved spectral performance, reflects in better speech quality in all types of noisy environment. For better speech enhancement in noise dominated regions, the system efficiency is further improved by fusing threshold values for wavelet denoising.
机译: > 问题陈述:移动通信中接收到的语音信号通常会受到背景噪声的干扰,因此需要一种良好的降噪方法来增强语音。众所周知,降噪是在尽可能多的噪声去除与信号完整性保持之间的折衷方案。为了解决这个问题,本研究提出了一种新的方法,该方法通过将双频带频谱减法与自适应噪声估计器和基于小波包的阈值化方法相融合,来增强背景干扰语音。 方法:所提出的系统将双频带谱减法与自适应噪声估计器相结合进行预处理,以初步降低噪声水平,并通过小波包变换进一步提高语音质量。 (WPT)基于级别的阈值化方法。通过使用Steins无偏风险估计器(SURE)确定阈值,并考虑使用硬,软,Garrotte,μ律,并考虑使用建议的改进软阈值函数进行降噪。 结果:通过从TIMIT数据库中获取的十种不同的干净语音样本(五男五女)和十三种不同的噪声源对提出的方法进行了研究,从而人为地降低了语音质量,并确定了噪声的能级从而使嘈杂语音的整体SNR保持在-5、0.5、10和15 dB,最后使用客观和主观方法对结果进行评估。 结论/建议:从实验结果表明,该方案具有改进的频谱性能,反映了所有类型噪声环境中更好的语音质量。为了在噪声占主导的区域更好地增强语音,通过融合阈值进行小波降噪,可以进一步提高系统效率。

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