AWARD    MERL Intern and Researchers Win ICASSP 2023 Best Student Paper Award

Date:

June 9, 2023

Awarded to:

Darius Petermann, Gordon Wichern, Aswin Subramanian, Jonathan Le Roux

Description:

Former MERL intern Darius Petermann (Ph.D. Candidate at Indiana University) has received a Best Student Paper Award at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023) for the paper "Hyperbolic Audio Source Separation", co-authored with MERL researchers Gordon Wichern and Jonathan Le Roux, and former MERL researcher Aswin Subramanian. The paper presents work performed during Darius's internship at MERL in the summer 2022. The paper introduces a framework for audio source separation using embeddings on a hyperbolic manifold that compactly represent the hierarchical relationship between sound sources and time-frequency features. Additionally, the code associated with the paper is publicly available at https://github.com/merlresearch/hyper-unmix.

ICASSP is the flagship conference of the IEEE Signal Processing Society (SPS). ICASSP 2023 was held in the Greek island of Rhodes from June 04 to June 10, 2023, and it was the largest ICASSP in history, with more than 4000 participants, over 6128 submitted papers and 2709 accepted papers. Darius’s paper was first recognized as one of the Top 3% of all papers accepted at the conference, before receiving one of only 5 Best Student Paper Awards during the closing ceremony.

Research Areas:

Artificial Intelligence, Machine Learning, Speech & Audio

• Related Publications

   Petermann, D., Wichern, G., Subramanian, A.S., Le Roux, J., "Hyperbolic Audio Source Separation", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), DOI: 10.1109/​ICASSP49357.2023.10094943, May 2023, pp. 1-5.

  BibTeX TR2023-017 PDF Software

  • @inproceedings{Petermann2023may,
  • author = {Petermann, Darius and Wichern, Gordon and Subramanian, Aswin Shanmugam and Le Roux, Jonathan},
  • title = {Hyperbolic Audio Source Separation},
  • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
  • year = 2023,
  • pages = {1--5},
  • month = may,
  • publisher = {IEEE},
  • doi = {10.1109/ICASSP49357.2023.10094943},
  • url = {https://www.merl.com/publications/TR2023-017}
  • }