Benchmarking the First Realistic Dataset for Speech Separation
This paper presents a thorough benchmarking analysis of a recently introduced realistic dataset for speech separation tasks. The dataset contains audio mixtures that replicate real-life scenarios and is accompanied by ground truths, making it a valuable resource for researchers. Although the datase...
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| Format: | Article |
| Language: | English |
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Institute of Fundamental Technological Research Polish Academy of Sciences
2025-07-01
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| Series: | Archives of Acoustics |
| Subjects: | |
| Online Access: | https://acoustics.ippt.pan.pl/index.php/aa/article/view/4180 |
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| _version_ | 1849695817537945600 |
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| author | Rawad MELHEM Oumayma AL DAKKAK Assef JAFAR |
| author_facet | Rawad MELHEM Oumayma AL DAKKAK Assef JAFAR |
| author_sort | Rawad MELHEM |
| collection | DOAJ |
| description |
This paper presents a thorough benchmarking analysis of a recently introduced realistic dataset for speech separation tasks. The dataset contains audio mixtures that replicate real-life scenarios and is accompanied by ground truths, making it a valuable resource for researchers. Although the dataset construction methodology was recently disclosed, its benchmarking and detailed performance analysis have not yet been conducted. In this study, we evaluate the performance of four speech separation models using two distinct testing sets, ensuring a robust evaluation. Our findings underscore the dataset’s efficacy to advance speech separation research within authentic environments. Furthermore, we propose a novel approach for assessing metrics in real-world speech separation systems, where ground truths are unavailable. This method aims to improve accuracy evaluations and refine models for practical applications.We make the dataset publicly available to encourage innovation and collaboration in the field.
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| format | Article |
| id | doaj-art-76e1c85f750c4f87b4ea6533f641d21f |
| institution | DOAJ |
| issn | 0137-5075 2300-262X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Institute of Fundamental Technological Research Polish Academy of Sciences |
| record_format | Article |
| series | Archives of Acoustics |
| spelling | doaj-art-76e1c85f750c4f87b4ea6533f641d21f2025-08-20T03:19:39ZengInstitute of Fundamental Technological Research Polish Academy of SciencesArchives of Acoustics0137-50752300-262X2025-07-0110.24425/aoa.2025.154816Benchmarking the First Realistic Dataset for Speech SeparationRawad MELHEM0Oumayma AL DAKKAK1Assef JAFAR2Higher Institute for Applied Sciences and TechnologyHigher Institute for Applied Sciences and TechnologyHigher Institute for Applied Sciences and Technology This paper presents a thorough benchmarking analysis of a recently introduced realistic dataset for speech separation tasks. The dataset contains audio mixtures that replicate real-life scenarios and is accompanied by ground truths, making it a valuable resource for researchers. Although the dataset construction methodology was recently disclosed, its benchmarking and detailed performance analysis have not yet been conducted. In this study, we evaluate the performance of four speech separation models using two distinct testing sets, ensuring a robust evaluation. Our findings underscore the dataset’s efficacy to advance speech separation research within authentic environments. Furthermore, we propose a novel approach for assessing metrics in real-world speech separation systems, where ground truths are unavailable. This method aims to improve accuracy evaluations and refine models for practical applications.We make the dataset publicly available to encourage innovation and collaboration in the field. https://acoustics.ippt.pan.pl/index.php/aa/article/view/4180single-channelspeech separationdeep learningcorpusdatasets |
| spellingShingle | Rawad MELHEM Oumayma AL DAKKAK Assef JAFAR Benchmarking the First Realistic Dataset for Speech Separation Archives of Acoustics single-channel speech separation deep learning corpus datasets |
| title | Benchmarking the First Realistic Dataset for Speech Separation |
| title_full | Benchmarking the First Realistic Dataset for Speech Separation |
| title_fullStr | Benchmarking the First Realistic Dataset for Speech Separation |
| title_full_unstemmed | Benchmarking the First Realistic Dataset for Speech Separation |
| title_short | Benchmarking the First Realistic Dataset for Speech Separation |
| title_sort | benchmarking the first realistic dataset for speech separation |
| topic | single-channel speech separation deep learning corpus datasets |
| url | https://acoustics.ippt.pan.pl/index.php/aa/article/view/4180 |
| work_keys_str_mv | AT rawadmelhem benchmarkingthefirstrealisticdatasetforspeechseparation AT oumaymaaldakkak benchmarkingthefirstrealisticdatasetforspeechseparation AT assefjafar benchmarkingthefirstrealisticdatasetforspeechseparation |