output
20062025
most citedMorpheuS: generating structured music with constrained patterns and tension

80 citations

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14 papers · 1 filter

cs.SD2025

Gelina: Unified Speech and Gesture Synthesis via Interleaved Token Prediction

Téo Guichoux, Théodor Lemerle, Shivam Mehta +5

Human communication is multimodal, with speech and gestures tightly coupled, yet most computational methods for generating speech and gestures synthesize them sequentially, weakeni…

cs.SD2024★ 1 cited

Tipping Points, Pulse Elasticity and Tonal Tension: An Empirical Study on What Generates Tipping Points

Canishk Naik, Elaine Chew

Tipping points are moments of change that characterise crucial turning points in a piece of music. This study presents a first step towards quantitatively and systematically descri…

cs.SD2024★ 2 cited

Combining audio control and style transfer using latent diffusion

Nils Demerlé, Philippe Esling, Guillaume Doras +1

Deep generative models are now able to synthesize high-quality audio signals, shifting the critical aspect in their development from audio quality to control capabilities. Although…

cs.SD2023★ 8 cited

SingSong: Generating musical accompaniments from singing

Chris Donahue, Antoine Caillon, Adam Roberts +8

We present SingSong, a system that generates instrumental music to accompany input vocals, potentially offering musicians and non-musicians alike an intuitive new way to create mus…

cs.SD2022★ 1 cited

A Model You Can Hear: Audio Identification with Playable Prototypes

Romain Loiseau, Baptiste Bouvier, Yann Teytaut +3

Machine learning techniques have proved useful for classifying and analyzing audio content. However, recent methods typically rely on abstract and high-dimensional representations…

cs.SD2022★ 1 cited

Zero-Shot Style Transfer for Gesture Animation driven by Text and Speech using Adversarial Disentanglement of Multimodal Style Encoding

Mireille Fares, Michele Grimaldi, Catherine Pelachaud +1

Modeling virtual agents with behavior style is one factor for personalizing human agent interaction. We propose an efficient yet effective machine learning approach to synthesize g…