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ADPCM compression of speech signals using a frequency domain LMS algorithm

机译:使用频域LMS算法ADPCM压缩语音信号

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This work introduces the use of an improved version of the popular stochastic gradient LMS algorithm, the frequency domain LMS algorithm, for the predictor adaptation, in ADPCM speech compression systems. Tests made indicate that the FLMS version, which is shown to converge at a faster rate than the traditional LMS algorithm, does not improve ADPCM performance, thus demanding a more careful interpretation of the predictors operation. This leads to a series of conclusions involving the speech generation model that extend the understanding of the ADPCM speech coding schemes and unveils new strategies to improve these systems.
机译:本作品介绍了使用流行随机梯度LMS算法,频域LMS算法的改进版本,用于预测器适应,在ADPCM语音压缩系统中。测试结果表明,以比传统的LMS算法更快的速率显示的FLMS版本不会提高ADPCM性能,从而要求更仔细地解释预测器操作。这导致了一系列结论,涉及语音生成模型,可以扩展对ADPCM语音编码方案的理解,并推出新的策略来改进这些系统。

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