ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2502.15430
48
0

Audio signal interpolation using optimal transportation of spectrograms

21 February 2025
David Valdivia
Marien Renaud
Elsa Cazelles
Cédric Févotte
    OT
ArXivPDFHTML
Abstract

We present a novel approach for generating an artificial audio signal that interpolates between given source and target sounds. Our approach relies on the computation of Wasserstein barycenters of the source and target spectrograms, followed by phase reconstruction and inversion. In contrast with previous works, our new method considers the spectrograms globally and does not operate on a temporal frame-to-frame basis. Another contribution is to endow the transportation cost matrix with a specific structure that prohibits remote displacements of energy along the time axis, and for which optimal transport is made possible by leveraging the unbalanced transport framework. The proposed cost matrix makes sense from the audio perspective and also allows to reduce the computation load. Results with synthetic musical notes and real environmental sounds illustrate the potential of our novel approach.

View on arXiv
@article{valdivia2025_2502.15430,
  title={ Audio signal interpolation using optimal transportation of spectrograms },
  author={ David Valdivia and Marien Renaud and Elsa Cazelles and Cédric Févotte },
  journal={arXiv preprint arXiv:2502.15430},
  year={ 2025 }
}
Comments on this paper