Abstract

It is well known that non-intrusive speech quality assessment methods are appropriate for real time monitoring of VoIP traffic. However, previous researches has proved that most of the non-intrusive speech quality assessment methods failed to estimate accurate speech quality using different languages. Consequently, intrusive methods are frequently chosen to provide a more accurate measurement, however they cannot be used for real time VoIP traffic monitoring. In this paper, the technique to enhanced simplified version of ITU-T recommendation G.107 E-model with a language impairment parameter was proposed. The method to estimate the function of language impairment by tuning the E-model with an intrusive objective method, PESQ was presented. The results from statistical analysis show that the modified E-model matches well with PESQ scores in eight languages.DOI: http://dx.doi.org/10.5755/j01.eee.21.1.7612

Highlights

  • The penetration of high speed mobile Internet access has created the current trend of speech communication over IP networks

  • The methodology to enhance the simplified E-model with a language impairment factor was proposed

  • Based on the concept of language impairment factor, the 3rd order polynomial regression model and coefficients of eight languages in G.729 codec are proposed for Il prediction

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Summary

Introduction

The penetration of high speed mobile Internet access has created the current trend of speech communication over IP networks. Voice over Internet Protocol (VoIP) is a technology that carries voice data in the form of a packet and sends it across the IP network. VoIP has become extremely popular because it is free or low cost when compared to traditional telephone services. VoIP is a delay sensitive application that relies on the best effort network. The speech quality can be impaired by the characteristics of the communication channel (e.g., delay, variation of delay and packet loss). In order to maintain a good Quality-ofService (QoS) to meet a commercial agreement, an efficient accurate speech quality assessment method is required

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