A Hierarchical Bayesian Approach to Modeling Heterogeneity in Speech Quality Assessment

Mossavat, Iman; Petkov, Petko N.; Kleijn, W. Bastiaan; Amft, Oliver

doi:10.1109/tasl.2011.2158421

Cited by 14 publications

(21 citation statements)

References 22 publications

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“…Therefore, PESQ is the preferred method of testing voice quality in an IP network. On the other hand, a new algorithm (POLQA, "Perceptual Objective Listening Quality Analysis") was developed recently by leading industry experts for speech quality measurement [7,16]. POLQA is the next-generation voice quality testing technology for fixed, mobile, and IPbased networks.…”

Section: Speech Quality Evaluation and Benchmarkingmentioning

confidence: 99%

Quality of service assessment: a case study on performance benchmarking of cellular network operators in Turkey

Dalveren¹,

Kara²

2015

Turk J Elec Eng & Comp Sci

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This paper presents findings on performance benchmarking of cellular network operators in Turkey. Benchmarking is based on measurements of standard key performance indicators (KPIs) in one of the metropolitan cities of Turkey, Ankara. Performance benchmarking is formulated by incorporating customer perception by conducting surveys on how important KPIs are from the user's point of view. KPIs are measured, with standard test equipment, by drive test method on specified routes. According to the performance benchmarking results, the GSM and UMTS network operators achieving the best performance were determined in Ankara. Speech qualities of network operators, as the most popular service, were also evaluated by several statistical methods including pdf/cdf analysis and chi-square and Fisher's exact tests. The network operator providing the highest speech quality in Ankara was determined with the methods applied. Overall, the results and approaches on benchmarking of cellular networks in Turkey are reported for the first time in this paper. The approaches proposed in this paper could be adapted to wide-scale benchmarking of services in cellular networks.

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Section: Speech Quality Evaluation and Benchmarkingmentioning

confidence: 99%

Quality of service assessment: a case study on performance benchmarking of cellular network operators in Turkey

Dalveren¹,

Kara²

2015

Turk J Elec Eng & Comp Sci

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“…Finally the updates for iterative estimates of β are given by: The algorithm iteratively updates the estimates of model parameters in Equations (4), (5), (6), and (7) until convergence is achieved.…”

Section: Statistical Inference Frameworkmentioning

confidence: 99%

“…The main disadvantages of subjective tests are cost, human labor, and time. Objective quality measures provide an estimate for the speech or audio quality, but with less accuracy in comparison with subjective listening tests [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Reliable estimation of quality scores by a small calibrated listening panel

Mossavat

Kleijn

2013

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

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In this work we propose the calibrated-mean-opinion-score (CMOS), which accounts for varying levels of precision and bias across subjects in a listening test. We adopt the Bayesian statistical framework, where the hyper-parameters of priors are learned via empirical Bayes, and the posterior is approximated by a computationally inexpensive variational technique. As our experimental results show, CMOS is more robust to noisy and biased subjects than MOS. As a result, CMOS can be used to improve the reliability of listening test results when a small test panel is used. To correct for the subjects in the test panel, calibration signals are required. Calibration signals are rated by a panel larger than the test panel. The key to saving human labor and cost is that only a few calibration signals are required, and that it is possible to share calibration signals across listening tests.

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“…Following a divide-and-conquer strategy, complex mappings are set up using different submodels which are then combined. Examples for this approach are P.563 [5], ANIQUE [3], and [11].…”

Section: Conceptsmentioning

confidence: 99%

Quality Estimation Based on Regular Perception

Norrenbrock¹,

Hinterleitner²,

Heute³

et al. 2013

4th International Workshop on Perceptual Quality of Systems (PQS 2013)

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We present a novel approach for speech-quality prediction based on the observation that perception-relevant properties may cover a wide range of different values without significantly changing perceptual quality. To account for this nonlinear phenomenon, a semi-supervised discretization concept is proposed which is applied to temporal as well as aggregated properties as a preprocessing step prior to conventional modelling. The idea of perceptual regularization allows for integrating an assumed perceptual reference into the modelling process without neglecting the empirical cognition effects coded in the subjective test data. For the example of synthetic-speech quality we will demonstrate how the two main goals of quality estimation, namely interpretability and robustness, are addressed through the presented approach.

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A Hierarchical Bayesian Approach to Modeling Heterogeneity in Speech Quality Assessment

Cited by 14 publications

References 22 publications

Quality of service assessment: a case study on performance benchmarking of cellular network operators in Turkey

Quality of service assessment: a case study on performance benchmarking of cellular network operators in Turkey

Reliable estimation of quality scores by a small calibrated listening panel

Quality Estimation Based on Regular Perception

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