0

Vibravox: A Dataset of French Speech Captured with Body-conduction Audio Sensors

The Vibravox dataset, compliant with GDPR, includes audio recordings from various sensors under controlled acoustic conditions, with experiments performed to evaluate models on speech recognition, enhancement, and verification tasks.

Year
2024
Venue
arXiv 2024
Authors
7
Hosting
Abstract onlyARXIV-DEFAULT

Cite

Notes

Only stored in your browser.

Attribution

Abstract & full text
arxiv.org/abs/2407.11828v4ARXIV-DEFAULT
TL;DR
Semantic Scholar
Attribution policy →

Abstract

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.

Authors

7