Speech Quality Assessment in Crowdsourcing: Comparison Category Rating Method
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Abstract (arXiv)
Traditionally, Quality of Experience (QoE) for a communication system is evaluated through a subjective test. The most common test method for speech QoE is the Absolute Category Rating (ACR), in which participants listen to a set of stimuli, processed by the underlying test conditions, and rate their perceived quality for each stimulus on a specific scale. The Comparison Category Rating (CCR) is another standard approach in which participants listen to both reference and processed stimuli and rate their quality compared to the other one. The CCR method is particularly suitable for systems that improve the quality of input speech. This paper evaluates an adaptation of the CCR test procedure for assessing speech quality in the crowdsourcing set-up. The CCR method was introduced in the ITU-T Rec. P.800 for laboratory-based experiments. We adapted the test for the crowdsourcing approach following the guidelines from ITU-T Rec. P.800 and P.808. We show that the results of the CCR procedure via crowdsourcing are highly reproducible. We also compared the CCR test results with widely used ACR test procedures obtained in the laboratory and crowdsourcing. Our results show that the CCR procedure in crowdsourcing is a reliable and valid test method.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Apr 2021.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1; 2026: 1.
4 papers.
- 2022Iterative autoregression: a novel trick to improve your low-latency speech enhancement modelcited by 5
- 2025Audio Turing Test: Benchmarking the Human-likeness of Large Language Model-based Text-to-Speech Systems in Chinesecited by 4
- 2024Crowdsourced Multilingual Speech Intelligibility Testingcited by 0
- 2026UniPASE: A Generative Model for Universal Speech Enhancement with High Fidelity and Low Hallucinationscited by 0
- 2026UniPASE: A Generative Model for Universal Speech Enhancement with High Fidelity and Low Hallucinations16 Apr 2026
- 2025Audio Turing Test: Benchmarking the Human-likeness of Large Language Model-based Text-to-Speech Systems in Chinese16 May 2025
- 2024Crowdsourced Multilingual Speech Intelligibility Testing21 Mar 2024
- 2022Iterative autoregression: a novel trick to improve your low-latency speech enhancement model3 Nov 2022