16 citations · 17 across the 5 of their papers we have counts for
5 papers
Real-time speech enhancement in noise for throat microphone using neural audio codec as foundation model
Julien Hauret, Thomas Joubaud, Éric Bavu
We present a real-time speech enhancement demo using speech captured with a throat microphone. This demo aims to showcase the complete pipeline, from recording to deep learning-bas…
French Listening Tests for the Assessment of Intelligibility, Quality, and Identity of Body-Conducted Speech Enhancement
Thomas Joubaud, Julien Hauret, Véronique Zimpfer +1
This study evaluates the Extreme Bandwidth Extension Network (EBEN) model on body-conduction sensors through listening tests. Using the Vibravox dataset, we assess intelligibility…
Bringing Interpretability to Neural Audio Codecs
Samir Sadok, Julien Hauret, Éric Bavu
The advent of neural audio codecs has increased in popularity due to their potential for efficiently modeling audio with transformers. Such advanced codecs represent audio from a h…
Vibravox: A Dataset of French Speech Captured with Body-conduction Audio Sensors
Julien Hauret, Malo Olivier, Thomas Joubaud +4
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 microp…
EBEN: Extreme bandwidth extension network applied to speech signals captured with noise-resilient body-conduction microphones
Julien Hauret, Thomas Joubaud, Véronique Zimpfer +1
In this paper, we present Extreme Bandwidth Extension Network (EBEN), a Generative Adversarial network (GAN) that enhances audio measured with body-conduction microphones. This typ…