Conferences | Jordi Pons

ICASSP2023 through my lens

By Jordi Pons in Conferences, Opinion June 12, 2023

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) 🙂 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:

Full-band General Audio Synthesis with Score-based Diffusion by Santi Pascual, Gautam Bhattacharya, Chunghsin Yeh, Jordi Pons and Joan Serrà.
Adversarial Permutation Invariant Training for Universal Sound Separation by Emilian Postolache, Jordi Pons, Santi Pascual and Joan Serrà.

ICASSP 2023: accepted papers

By Jordi Pons in Conferences February 15, 2023

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

Full-band General Audio Synthesis with Score-based Diffusion by Santi Pascual, Gautam Bhattacharya, Chunghsin Yeh, Jordi Pons and Joan Serrà.
Adversarial Permutation Invariant Training for Universal Sound Separation by Emilian Postolache, Jordi Pons, Santi Pascual and Joan Serrà.

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

Interspeech 2022 paper: “PodcastMix: A dataset for separating music and speech in podcasts”

By Jordi Pons in Conferences, Datasets, Deep learning, Paper is out July 18, 2022

Today we release “PodcastMix”, a dataset for separating music and speech in podcasts:

ICASSP 2022 – my learnings

By Jordi Pons in Conferences, Deep learning May 16, 2022

My biggest learning this year: I’LL NOT SURVIVE ANOTHER ONLINE CONFERENCE 💔 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 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 2022 paper: “On loss functions and evaluation metrics for music source separation”

By Jordi Pons in Conferences, Deep learning, Paper is out February 16, 2022

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!