ICASSP 2022 paper: “On loss functions and evaluation metrics for music source separation”

During his internship at Dolby, Enric run an exhaustive evaluation of various loss functions for music source separation. After evaluating those losses objectively and subjectively, we recommend training with the following spectrogram-based losses: L2freq, SISDRfreq, LOGL2freq or LOGL1freq with, potentially, phase- sensitive objectives and adversarial regularizers.

link to arXiv!

ICASSP 2022: accepted papers

These are the papers we will be presenting at ICASSP 2021! Infinite thanks to all my collaborators for the amazing work 🙂

  • On Loss Functions and Evaluation Metrics for Music Source Separation by Enric Gusó, Jordi Pons, Santiago Pascual, Joan Serrà [Zenodo, arXiv].
  • PixInWav: Residual Steganography for Hiding Pixels in Audio by Margarita Geleta, Cristina Punti, Kevin McGuinness, Jordi Pons, Cristian Canton, Xavier Giro-i-Nieto [arXiv].

ICASSP 2021: accepted papers

These are the papers we will be presenting at ICASSP 2021:

  • Xiaoyu Liu, Jordi Pons. On permutation invariant training for speech source separation. [arxiv]
  • Daniel Arteaga, Jordi Pons. Multichannel-based learning for audio object extraction. [arxiv]
  • Jordi Pons, Santiago Pascual, Giulio Cengarle, Joan Serrà. Upsampling artifacts in neural audio synthesis. [arXiv, code]
  • Christian J Steinmetz, Jordi Pons, Santiago Pascual, Joan Serrà. Automatic multitrack mixing with a differentiable mixing console of neural audio effects. [arXiv, demo]
  • Joan Serrà, Jordi Pons, Santiago Pascual. SESQA: semi-supervised learning for speech quality assessment. [arXiv]

Infinite thanks to all my collaborators for the amazing work 🙂