Séminaire de l’axe IA d’IBISC, organisé par Dominique FOURER.
Le 10 juin 2026, 13h-14h, Amphithéâtre Ax12
Intervenant
Haoran SUN (doctorant, dir. Dominique Fourer, co-dir. Hichem Maaref, équipe SIAM)
Title
FlowSE: Efficient and High-Quality Speech Enhancement via
Flow Matching
Abstract
Generative models have excelled in audio tasks using approaches such as language models, diffusion, and flow matching. However, existing generative approaches for speech enhancement (SE) face notable challenges: language model-based methods suffer from quantization loss, leading to compromised speaker similarity and intelligibility, while diffusion models require complex training and high inference latency. To address these challenges, we propose FlowSE, a flow-matching-based model for SE. Flow matching learns a continuous transformation between noisy and clean speech distributions in a single pass, significantly reducing inference latency while maintaining high-quality reconstruction. Specifically, FlowSE trains on noisy mel spectrograms and optional character sequences, optimizing a conditional flow matching loss with ground-truth mel spectrograms as supervision. It implicitly learns speech’s temporal-spectral structure and text-speech alignment. During inference, FlowSE can operate with or without textual information, achieving impressive results in both scenarios, with further improvements when transcripts are available. Extensive experiments demonstrate that FlowSE significantly outperforms state-of-the art generative methods, establishing a new paradigm for generative-based SE and demonstrating the potential of flow matching to advance the field.
- Date: 10/06:2026
- Lieu : Amphithéâtre Ax12
- Organisateur: Dominique FOURER (MCF Univ. Évry, IBISC équipe SIAM)
- Site Web de l’axe transversal IA (Dominique Fourer)
