{"url":"/dataset/odaq-open-dataset-of-audio-quality","name":"ODAQ: Open Dataset of Audio Quality","full_name":null,"description_markdown":"A dataset containing the results of a MUSHRA listening test conducted with expert listeners from 2 international laboratories. ODAQ contains 240 audio samples and corresponding quality scores. Each audio sample is rated by 26 listeners. The audio samples are stereo audio signals sampled at 44.1 or 48 kHz and are processed by a total of 6 method classes, each operating at different quality levels. The processing method classes are designed to generate quality degradations possibly encountered during audio coding and source separation, and the quality levels for each method class span the entire quality range. The diversity of the processing methods, the large span of quality levels, the high sampling frequency, and the pool of international listeners make ODAQ particularly suited for further research into subjective and objective audio quality. The dataset is released with permissive licenses, and the software used to conduct the listening test is also made publicly available.","description_withheld":null,"homepage":"https://github.com/Fraunhofer-IIS/ODAQ","introduced_date":"2023-12-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/odaq-open-dataset-of-audio-quality","title":"ODAQ: Open Dataset of Audio Quality","first_author":"Matteo Torcoli","url":null},"license":{"name":"Mixed CC BY, CC BY-NC, and CC0","url":"https://zenodo.org/doi/10.5281/zenodo.10405773"},"modalities":[{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[{"name":"Audio Quality Assessment","url":"/task/audio-quality-assessment","datasets_with_task":"/datasets/task/audio-quality-assessment"},{"name":"Music Quality Assessment","url":"/task/music-quality-assessment","datasets_with_task":"/datasets/task/music-quality-assessment"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ODAQ: Open Dataset of Audio Quality"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/audio-quality-assessment-on-odaq-open-dataset","task":"Audio Quality Assessment","dataset_variant":"ODAQ: Open Dataset of Audio Quality","rows":9,"metrics":["Pearson correlation coefficient (PCC)"],"first_row_in_archive_order":{"model":"NMR","paper":"/paper/odaq-open-dataset-of-audio-quality-benchmark","metrics":{"Pearson correlation coefficient (PCC)":"0.89"},"code_links":[{"title":"fraunhofer-iis/odaq","url":"https://github.com/fraunhofer-iis/odaq"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/odaq-open-dataset-of-audio-quality-benchmark","title":"ODAQ: Open Dataset of Audio Quality - Benchmark on GitHub","date":"2024-09-13","rows_on_this_dataset":9,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}