Abstract
This paper presents an objective speech quality model, ViSQOL, the Virtual Speech Quality Objective Listener. It is a signal-based, full-reference, intrusive metric that models human speech quality perception using a spectro-temporal measure of similarity between a reference and a test speech signal. The metric has been particularly designed to be robust for quality issues associated with Voice over IP (VoIP) transmission. This paper describes the algorithm and compares the quality predictions with the ITU-T standard metrics PESQ and POLQA for common problems in VoIP: clock drift, associated time warping, and playout delays. The results indicate that ViSQOL and POLQA significantly outperform PESQ, with ViSQOL competing well with POLQA. An extensive benchmarking against PESQ, POLQA, and simpler distance metrics using three speech corpora (NOIZEUS and E4 and the ITU-T P.Sup. 23 database) is also presented. These experiments benchmark the performance for a wide range of quality impairments, including VoIP degradations, a variety of background noise types, speech enhancement methods, and SNR levels. The results and subsequent analysis show that both ViSQOL and POLQA have some performance weaknesses and under-predict perceived quality in certain VoIP conditions. Both have a wider application and robustness to conditions than PESQ or more trivial distance metrics. ViSQOL is shown to offer a useful alternative to POLQA in predicting speech quality in VoIP scenarios.
Highlights
Predicting how a user perceives speech quality has become more important as transmission channels for human speech communication have evolved from traditional fixed telephony to Voice over Internet Protocol (VoIP)-based systems
Network monitoring tools can give a good indicator of the quality of service (QoS), but predicting the quality of experience (QoE) for the end user of heterogeneous networked systems is becoming more important as transmission channels for human speech communication have a greater reliance on VoIP
This paper looks at situations where the degradation occurs in the communication channel, and assessing the signal directly using Neurogram Similarity Index Measure (NSIM) on the signal spectrograms rather than neurograms simplifies the model
Summary
Predicting how a user perceives speech quality has become more important as transmission channels for human speech communication have evolved from traditional fixed telephony to Voice over Internet Protocol (VoIP)-based systems. Objective measures aim to model this assessment, to give accurate estimates of quality when compared with subjective tests. PESQ (Perceptual Evaluation of Speech Quality) [1] and the more recent POLQA (Perceptual Objective Listening Quality Assessment) [2], described in ITU standards, are full-reference measures meaning they allow prediction of speech quality by comparing a reference to a received signal. Hines et al EURASIP Journal on Audio, Speech, and Music Processing (2015) 2015:13 addresses other limitations in PESQ, time alignment and warped speech It is slowly gaining more widespread use, so as yet, there has been limited publication of its performance outside of its own development and conformance tests. This work presents an alternative model, the Virtual Speech Quality Objective Listener, or ViSQOL, which has been developed to be a general full-reference objective speech quality metric with a particular focus on VoIP degradations.
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