63 citations · 235 across the 27 of their papers we have counts for
5 papers · 1 filter
A Statistical Model for Predicting Generalization in Few-Shot Classification
Yassir Bendou, Vincent Gripon, Bastien Pasdeloup +5
The estimation of the generalization error of classifiers often relies on a validation set. Such a set is hardly available in few-shot learning scenarios, a highly disregarded shor…
Music Mixing Style Transfer: A Contrastive Learning Approach to Disentangle Audio Effects
Junghyun Koo, Marco A. Martínez-Ramírez, Wei-Hsiang Liao +3
We propose an end-to-end music mixing style transfer system that converts the mixing style of an input multitrack to that of a reference song. This is achieved with an encoder pre-…
Automatic music mixing with deep learning and out-of-domain data
Marco A. Martínez-Ramírez, Wei-Hsiang Liao, Giorgio Fabbro +3
Music mixing traditionally involves recording instruments in the form of clean, individual tracks and blending them into a final mixture using audio effects and expert knowledge (e…
AutoTTS: End-to-End Text-to-Speech Synthesis through Differentiable Duration Modeling
Bac Nguyen, Fabien Cardinaux, Stefan Uhlich
Parallel text-to-speech (TTS) models have recently enabled fast and highly-natural speech synthesis. However, they typically require external alignment models, which are not necess…
Distortion Audio Effects: Learning How to Recover the Clean Signal
Johannes Imort, Giorgio Fabbro, Marco A. Martínez Ramírez +3
Given the recent advances in music source separation and automatic mixing, removing audio effects in music tracks is a meaningful step toward developing an automated remixing syste…