ICASSP2023 through my lens

It’s been amazing to re-meet my international friends and colleagues in person. It was nice to see PhD students to experience research and conferences firsthand (no beers allowed) 馃檪 I’m sure this meeting will foster future collaborations and new friendships, pushing the field of music/audio deep learning research forward!

This year I was there to present:

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ICASSP 2023: accepted papers

These are the papers we will be presenting at ICASSP 2023! Infinite thanks to all my collaborators for the amazing work 馃檪

Image by DALL路E with prompt: “audio synthesis and sound separation science”.

ICASSP 2022 鈥 my learnings

My biggest learning this year: I’LL NOT SURVIVE ANOTHER ONLINE CONFERENCE 馃挃 I really miss in-person discussion in exotic places! This year I attended ICASSP to present two papers:

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

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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!