11 citations · 14 across the 5 of their papers we have counts for
5 papers
SonicCaps: Large-Scale Diverse and Fine-Grained Captioning for Improved Audio-Retrieval
Zineb Lahrichi, Marc Ferras, Gaël Richard +1
Recent advances in audio-language modeling have been driven by large-scale audio captioning datasets. However, existing datasets remain limited by low semantic diversity, generic d…
Woosh: A Sound Effects Foundation Model
Gaëtan Hadjeres, Marc Ferras, Khaled Koutini +7
The audio research community depends on open generative models as foundational tools for building novel approaches and establishing baselines. In this report, we present Woosh, Son…
Unsupervised Cross-Domain Speech-to-Speech Conversion with Time-Frequency Consistency
Mohammad Asif Khan, Fabien Cardinaux, Stefan Uhlich +2
In recent years generative adversarial network (GAN) based models have been successfully applied for unsupervised speech-to-speech conversion.The rich compact harmonic view of the…
Closing the Training/Inference Gap for Deep Attractor Networks
Cyril Cadoux, Stefan Uhlich, Marc Ferras +1
This paper improves the deep attractor network (DANet) approach by closing its gap between training and inference. During training, DANet relies on attractors, which are computed f…
Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition
Pavel Denisov, Ngoc Thang Vu, Marc Ferras Font
In this paper, we investigate the use of adversarial learning for unsupervised adaptation to unseen recording conditions, more specifically, single microphone far-field speech. We…