Multi-dimensional Speech Quality Assessment in Crowdsourcing
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Abstract (arXiv)
Subjective speech quality assessment is the gold standard for evaluating speech enhancement processing and telecommunication systems. The commonly used standard ITU-T Rec. P.800 defines how to measure speech quality in lab environments, and ITU-T Rec.~P.808 extended it for crowdsourcing. ITU-T Rec. P.835 extends P.800 to measure the quality of speech in the presence of noise. ITU-T Rec. P.804 targets the conversation test and introduces perceptual speech quality dimensions which are measured during the listening phase of the conversation. The perceptual dimensions are noisiness, coloration, discontinuity, and loudness. We create a crowdsourcing implementation of a multi-dimensional subjective test following the scales from P.804 and extend it to include reverberation, the speech signal, and overall quality. We show the tool is both accurate and reproducible. The tool has been used in the ICASSP 2023 Speech Signal Improvement challenge and we show the utility of these speech quality dimensions in this challenge. The tool will be publicly available as open-source at https://github.com/microsoft/P.808.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Sep 2023.
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Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
- 2024EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberationcited by 62
- 2024ICASSP 2024 Speech Signal Improvement Challengecited by 15
- 2026The Limits of Reference-Free Speech Quality Metrics as Evaluators and Rewards on Modern Text-to-Speechcited by 1
- 2025Assessing speech quality metrics for evaluation of neural audio codecs under clean speech conditionscited by 0
- 2026The Limits of Reference-Free Speech Quality Metrics as Evaluators and Rewards on Modern Text-to-Speech2 Jul 2026
- 2025Assessing speech quality metrics for evaluation of neural audio codecs under clean speech conditions29 Sep 2025
- 2024EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation10 Jun 2024
- 2024ICASSP 2024 Speech Signal Improvement Challenge25 Jan 2024