1 citations · 1 across the 16 of their papers we have counts for
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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…
Melody-Lyrics Matching with Contrastive Alignment Loss
Changhong Wang, Michel Olvera, Gaël Richard
The connection between music and lyrics is far beyond semantic bonds. Conceptual pairs in the two modalities such as rhythm and rhyme, note duration and syllabic stress, and struct…
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…
Multiple Choice Learning of Low-Rank Adapters for Language Modeling
Victor Letzelter, Hugo Malard, Mathieu Fontaine +4
We propose LoRA-MCL, a training scheme that extends next-token prediction in language models with a method designed to decode diverse, plausible sentence continuations at inference…
Of All StrIPEs: Investigating Structure-informed Positional Encoding for Efficient Music Generation
Manvi Agarwal, Changhong Wang, Gael Richard
While music remains a challenging domain for generative models like Transformers, a two-pronged approach has recently proved successful: inserting musically-relevant structural inf…
F-StrIPE: Fast Structure-Informed Positional Encoding for Symbolic Music Generation
Manvi Agarwal, Changhong Wang, Gael Richard
While music remains a challenging domain for generative models like Transformers, recent progress has been made by exploiting suitable musically-informed priors. One technique to l…
A Hybrid Model for Weakly-Supervised Speech Dereverberation
Louis Bahrman, Mathieu Fontaine, Gael Richard
This paper introduces a new training strategy to improve speech dereverberation systems using minimal acoustic information and reverberant (wet) speech. Most existing algorithms re…
Investigating the Sensitivity of Pre-trained Audio Embeddings to Common Effects
Victor Deng, Changhong Wang, Gael Richard +1
In recent years, foundation models have significantly advanced data-driven systems across various domains. Yet, their underlying properties, especially when functioning as feature…