Psychoacoustic Challenges Of Speech Enhancement On VoIP Platforms
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arXiv
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| Format: | Preprint |
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2023
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| _version_ | 1866916341970108416 |
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| author | Konan, Joseph Agnihotri, Shikhar Bhargave, Ojas Han, Shuo Zeng, Yunyang Shah, Ankit Raj, Bhiksha |
| author_facet | Konan, Joseph Agnihotri, Shikhar Bhargave, Ojas Han, Shuo Zeng, Yunyang Shah, Ankit Raj, Bhiksha |
| contents | Within the ambit of VoIP (Voice over Internet Protocol) telecommunications, the complexities introduced by acoustic transformations merit rigorous analysis. This research, rooted in the exploration of proprietary sender-side denoising effects, meticulously evaluates platforms such as Google Meets and Zoom. The study draws upon the Deep Noise Suppression (DNS) 2020 dataset, ensuring a structured examination tailored to various denoising settings and receiver interfaces. A methodological novelty is introduced via Blinder-Oaxaca decomposition, traditionally an econometric tool, repurposed herein to analyze acoustic-phonetic perturbations within VoIP systems. To further ground the implications of these transformations, psychoacoustic metrics, specifically PESQ and STOI, were used to explain of perceptual quality and intelligibility. Cumulatively, the insights garnered underscore the intricate landscape of VoIP-influenced acoustic dynamics. In addition to the primary findings, a multitude of metrics are reported, extending the research purview. Moreover, out-of-domain benchmarking for both time and time-frequency domain speech enhancement models is included, thereby enhancing the depth and applicability of this inquiry. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_07161 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Psychoacoustic Challenges Of Speech Enhancement On VoIP Platforms Konan, Joseph Agnihotri, Shikhar Bhargave, Ojas Han, Shuo Zeng, Yunyang Shah, Ankit Raj, Bhiksha Sound Computation and Language Audio and Speech Processing Within the ambit of VoIP (Voice over Internet Protocol) telecommunications, the complexities introduced by acoustic transformations merit rigorous analysis. This research, rooted in the exploration of proprietary sender-side denoising effects, meticulously evaluates platforms such as Google Meets and Zoom. The study draws upon the Deep Noise Suppression (DNS) 2020 dataset, ensuring a structured examination tailored to various denoising settings and receiver interfaces. A methodological novelty is introduced via Blinder-Oaxaca decomposition, traditionally an econometric tool, repurposed herein to analyze acoustic-phonetic perturbations within VoIP systems. To further ground the implications of these transformations, psychoacoustic metrics, specifically PESQ and STOI, were used to explain of perceptual quality and intelligibility. Cumulatively, the insights garnered underscore the intricate landscape of VoIP-influenced acoustic dynamics. In addition to the primary findings, a multitude of metrics are reported, extending the research purview. Moreover, out-of-domain benchmarking for both time and time-frequency domain speech enhancement models is included, thereby enhancing the depth and applicability of this inquiry. |
| title | Psychoacoustic Challenges Of Speech Enhancement On VoIP Platforms |
| topic | Sound Computation and Language Audio and Speech Processing |
| url | https://arxiv.org/abs/2310.07161 |