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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.11828 |
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| _version_ | 1866912295931609088 |
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| author | Hauret, Julien Olivier, Malo Joubaud, Thomas Langrenne, Christophe Poirée, Sarah Zimpfer, Véronique Bavu, Éric |
| author_facet | Hauret, Julien Olivier, Malo Joubaud, Thomas Langrenne, Christophe Poirée, Sarah Zimpfer, Véronique Bavu, Éric |
| contents | Vibravox is a dataset compliant with the General Data Protection Regulation (GDPR) containing audio recordings using five different body-conduction audio sensors: two in-ear microphones, two bone conduction vibration pickups, and a laryngophone. The dataset also includes audio data from an airborne microphone used as a reference. The Vibravox corpus contains 45 hours per sensor of speech samples and physiological sounds recorded by 188 participants under different acoustic conditions imposed by a high order ambisonics 3D spatializer. Annotations about the recording conditions and linguistic transcriptions are also included in the corpus. We conducted a series of experiments on various speech-related tasks, including speech recognition, speech enhancement, and speaker verification. These experiments were carried out using state-of-the-art models to evaluate and compare their performances on signals captured by the different audio sensors offered by the Vibravox dataset, with the aim of gaining a better grasp of their individual characteristics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_11828 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Vibravox: A Dataset of French Speech Captured with Body-conduction Audio Sensors Hauret, Julien Olivier, Malo Joubaud, Thomas Langrenne, Christophe Poirée, Sarah Zimpfer, Véronique Bavu, Éric Audio and Speech Processing Machine Learning Vibravox is a dataset compliant with the General Data Protection Regulation (GDPR) containing audio recordings using five different body-conduction audio sensors: two in-ear microphones, two bone conduction vibration pickups, and a laryngophone. The dataset also includes audio data from an airborne microphone used as a reference. The Vibravox corpus contains 45 hours per sensor of speech samples and physiological sounds recorded by 188 participants under different acoustic conditions imposed by a high order ambisonics 3D spatializer. Annotations about the recording conditions and linguistic transcriptions are also included in the corpus. We conducted a series of experiments on various speech-related tasks, including speech recognition, speech enhancement, and speaker verification. These experiments were carried out using state-of-the-art models to evaluate and compare their performances on signals captured by the different audio sensors offered by the Vibravox dataset, with the aim of gaining a better grasp of their individual characteristics. |
| title | Vibravox: A Dataset of French Speech Captured with Body-conduction Audio Sensors |
| topic | Audio and Speech Processing Machine Learning |
| url | https://arxiv.org/abs/2407.11828 |