12 papers · 1 filter
Exploring Representation Autoencoders for Text-to-Audio Generation
Bernardo V. Miranda, Hugo Malard, Gaël Richard +2
Representation autoencoders (RAE), created by pairing a frozen pretrained self-supervised learning (SSL) encoder with a trained decoder, have recently demonstrated state-of-the-art…
The Internet Archive Music Dataset
Paraskevas Stamatiadis, Bernardo V Miranda, Clémentine Berger +3
We introduce the Internet Archive Music Dataset (IAMD), a large-scale collection of captioned music segments derived from the Internet Archive. To the best of our knowledge, IAMD c…
Neural Multichannel Distant Speaker Diarization with Heavy-tailed Source Separation Model
Sicheng Mao, Baihan Li, Mathieu Fontaine +2
Distant speaker diarization remains challenging due to difficult acoustic environments, varying numbers of speakers and overlapping speech. Model-driven methods are proposed to exp…
Neural Multichannel Distant Speaker Diarization and Source Separation with Beta Speaker Activity Prior
Sicheng Mao, Mathieu Fontaine, Anthony Larcher +1
Distant speaker diarization remains challenging due to adverse acoustic conditions, varying numbers of speakers and overlapping speech. While data-driven approaches have shown stro…
Contrastive Knowledge Distillation for Embedding Refinement in Personalized Speech Enhancement
Thomas Serre, Mathieu Fontaine, Éric Benhaim +1
Personalized speech enhancement (PSE) has shown convincing results when it comes to extracting a known target voice among interfering ones. The corresponding systems usually incorp…
GLA-Grad++: An Improved Griffin-Lim Guided Diffusion Model for Speech Synthesis
Teysir Baoueb, Xiaoyu Bie, Mathieu Fontaine +1
Recent advances in diffusion models have positioned them as powerful generative frameworks for speech synthesis, demonstrating substantial improvements in audio quality and stabili…
The silence of the weights: a structural pruning strategy for attention-based audio signal architectures with second order metrics
Andrea Diecidue, Carlo Alberto Barbano, Piero Fraternali +2
Transformer-based models have become the state of the art across multiple domains, from natural language processing to machine listening, thanks to the attention mechanisms. Howeve…
U-DREAM: Unsupervised Dereverberation guided by a Reverberation Model
Louis Bahrman, Marius Rodrigues, Mathieu Fontaine +1
This paper explores the outcome of training state-of-the-art dereverberation models with supervision settings ranging from weakly-supervised to virtually unsupervised, relying sole…
Speech dereverberation constrained on room impulse response characteristics
Louis Bahrman, Mathieu Fontaine, Jonathan Le Roux +1
Single-channel speech dereverberation aims at extracting a dry speech signal from a recording affected by the acoustic reflections in a room. However, most current deep learning-ba…
A lightweight dual-stage framework for personalized speech enhancement based on DeepFilterNet2
Thomas Serre, Mathieu Fontaine, Éric Benhaim +2
Isolating the desired speaker's voice amidst multiplespeakers in a noisy acoustic context is a challenging task. Per-sonalized speech enhancement (PSE) endeavours to achievethis by…
GLA-Grad: A Griffin-Lim Extended Waveform Generation Diffusion Model
Haocheng Liu, Teysir Baoueb, Mathieu Fontaine +2
Diffusion models are receiving a growing interest for a variety of signal generation tasks such as speech or music synthesis. WaveGrad, for example, is a successful diffusion model…
SpecDiff-GAN: A Spectrally-Shaped Noise Diffusion GAN for Speech and Music Synthesis
Teysir Baoueb, Haocheng Liu, Mathieu Fontaine +2
Generative adversarial network (GAN) models can synthesize highquality audio signals while ensuring fast sample generation. However, they are difficult to train and are prone to se…