Expanding and Analyzing ODAQ -- the Open Dataset of Audio Quality
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909560696995840 |
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| author | Dick, Sascha Thompson, Christoph Wu, Chih-Wei Torcoli, Matteo Delgado, Pablo Williams, Phillip A. Habets, Emanuel |
| author_facet | Dick, Sascha Thompson, Christoph Wu, Chih-Wei Torcoli, Matteo Delgado, Pablo Williams, Phillip A. Habets, Emanuel |
| contents | The Open Dataset of Audio Quality (ODAQ) was recently introduced to address the scarcity of openly available audio datasets with corresponding subjective quality scores. The dataset, released under permissive licenses, comprises audio material processed using six different signal processing methods operating at five quality levels, along with corresponding subjective test results. To expand the dataset, we provided listener training to university students to conduct further subjective tests and obtained results consistent with previous expert listeners. We also showed how different training approaches affect the use of absolute scales and anchors. The expanded dataset now comprises results from three international laboratories providing a total of 42 listeners and 10080 subjective scores. This paper provides the details of the expansion and an in-depth analysis. As part of this analysis, we initiate the use of ODAQ as a benchmark to evaluate objective audio quality metrics in their ability to predict subjective scores |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_00742 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Expanding and Analyzing ODAQ -- the Open Dataset of Audio Quality Dick, Sascha Thompson, Christoph Wu, Chih-Wei Torcoli, Matteo Delgado, Pablo Williams, Phillip A. Habets, Emanuel Audio and Speech Processing The Open Dataset of Audio Quality (ODAQ) was recently introduced to address the scarcity of openly available audio datasets with corresponding subjective quality scores. The dataset, released under permissive licenses, comprises audio material processed using six different signal processing methods operating at five quality levels, along with corresponding subjective test results. To expand the dataset, we provided listener training to university students to conduct further subjective tests and obtained results consistent with previous expert listeners. We also showed how different training approaches affect the use of absolute scales and anchors. The expanded dataset now comprises results from three international laboratories providing a total of 42 listeners and 10080 subjective scores. This paper provides the details of the expansion and an in-depth analysis. As part of this analysis, we initiate the use of ODAQ as a benchmark to evaluate objective audio quality metrics in their ability to predict subjective scores |
| title | Expanding and Analyzing ODAQ -- the Open Dataset of Audio Quality |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2504.00742 |