BWSNet: Automatic Perceptual Assessment of Audio Signals
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866929216990216192 |
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| author | Veillon, Clément Le Moine Rosi, Victor Sarah, Pablo Arias Salais, Léane Obin, Nicolas |
| author_facet | Veillon, Clément Le Moine Rosi, Victor Sarah, Pablo Arias Salais, Léane Obin, Nicolas |
| contents | This paper introduces BWSNet, a model that can be trained from raw human judgements obtained through a Best-Worst scaling (BWS) experiment. It maps sound samples into an embedded space that represents the perception of a studied attribute. To this end, we propose a set of cost functions and constraints, interpreting trial-wise ordinal relations as distance comparisons in a metric learning task. We tested our proposal on data from two BWS studies investigating the perception of speech social attitudes and timbral qualities. For both datasets, our results show that the structure of the latent space is faithful to human judgements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_02592 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | BWSNet: Automatic Perceptual Assessment of Audio Signals Veillon, Clément Le Moine Rosi, Victor Sarah, Pablo Arias Salais, Léane Obin, Nicolas Audio and Speech Processing Sound This paper introduces BWSNet, a model that can be trained from raw human judgements obtained through a Best-Worst scaling (BWS) experiment. It maps sound samples into an embedded space that represents the perception of a studied attribute. To this end, we propose a set of cost functions and constraints, interpreting trial-wise ordinal relations as distance comparisons in a metric learning task. We tested our proposal on data from two BWS studies investigating the perception of speech social attitudes and timbral qualities. For both datasets, our results show that the structure of the latent space is faithful to human judgements. |
| title | BWSNet: Automatic Perceptual Assessment of Audio Signals |
| topic | Audio and Speech Processing Sound |
| url | https://arxiv.org/abs/2309.02592 |