基于演化Takagi-Sugeno模糊模型的VoIP系统LSP系数恢复

E. Jones, P. Angelov, C. Xydeas
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引用次数: 0

摘要

为了在基于分组的语音系统(如互联网协议语音,VoIP)中提供实时、高质量的语音服务,系统设计者必须解决与可能的数据包丢失相关的固有质量问题。为了对抗由于语音信息传输包丢失而导致的不可避免的语音质量下降,提供语音恢复过程所需的丢失信息估计的技术是相当有趣的。此外,在使用基于线性预测编码(LPC)的语音编码器的VoIP系统中,有很大比例的编码语音信息表示LPC系数的值,因此本文提出了一种估计缺失LPC滤波器系数的新方法。该方法采用了一种新的LSP恢复系统架构,其中部署了基于模糊规则的进化模型,特别是所谓的进化Takagi-Sugeno模型,以生成缺失LSP所需的估计。所提出的缺失参数估计技术是通用的,初步的实验结果表明它在提高基于LPC的VoIP解码语音质量方面具有很大的潜力
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recovery of LSP Coefficient in VoIP Systems using Evolving Takagi-Sugeno Fuzzy Models
In order to deliver real time, high quality voice services in packet based voice system (e.g. voice over Internet protocol, VoIP) system designers must tackle inherent quality problems related to possible packet loss. To combat the inevitable speech quality deterioration resulting from the loss of transmitted packets of speech information, techniques that provide estimates of the lost information that is needed by the speech recovery process are of considerable interest. Furthermore, in VoIP systems employing linear predictive coding (LPC) based speech coders, a significant percentage of the coded speech information represent the values of LPC coefficients and thus a new approach for estimating missing LPC filter coefficients is presented in this paper. This approach employs a new formulation of LSP recovery system architecture where evolving fuzzy rule-based models and particularly so-called evolving Takagi-Sugeno models are deployed to generate the required estimates of missing LSPs. The proposed missing parameters estimation technique is generic and initial experimental results demonstrate its considerable potential in improving the quality of LPC based decoded speech in VoIP applications
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