有耗条件下短期预测参数的估计

D. Black, M. Sandler
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引用次数: 1

摘要

分组交换网络传输中固有的不一致性会严重损害实时语音传输的质量。本文将重点放在短时预测(STP)滤波器参数的重要性上,因为这些参数在感知上对可理解语音非常重要。我们介绍了几种基于外推和插值技术的以线谱频率(lfs)表示的丢失STP参数恢复的新方案。一些过去和/或未来框架的独特包含进一步赞扬了这项工作。提出并评价了在精度方面优于传统帧重复和线性插值的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of short term prediction parameters under lossy conditions
The inconsistencies inherent in packet switched network delivery can be seriously detrimental to the quality of a real-time speech transmission. This paper places its emphasis on the importance of the short term prediction (STP) filter parameters as these are perceptually important to intelligible speech. We introduces several novel schemes for the recovery of lost STP parameters represented as line spectral frequencies (LSFs) based on extrapolation and interpolation techniques. The unique inclusion of a number of past and/or future frames further commends this work. Methods which outperforms the traditional frame repetition and linear interpolation in terms of accuracy are presented and evaluated.
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