2020 IEEE SPS Signal Processing Letters Best Paper Award

I'm thrilled to report that our paper Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification has won a 2020 IEEE SPS Signal Processing Letters Best Paper Award.

The paper appeared in the March 2017 issue of the IEE SPL journal. It was honored for its "exceptional merit and broad interest on a subject related to the Society's technical scope." (To be eligible for consideration, an article must have appeared in Signal Processing Letters within a five-year window.). Here's the NYU press release about the award.

The research was conducted in the context of the Sounds of New York City (SONYC) project:

The paper represents the culmination of several years of research on urban sound, and builds on our earlier work in this area including:

• A Dataset and Taxonomy for Urban Sound Research
  J. Salamon, C. Jacoby and J. P. Bello, 2014
• Unsupervised Feature Learning for Urban Sound Classification
  J. Salamon and J. P. Bello, 2015
• Feature Learning with Deep Scattering for Urban Sound Analysis
  J. Salamon and J. P. Bello, 2015
• The Implementation of Low-cost Urban Acoustic Monitoring Devices
  C. Mydlarz, J. Salamon and J. P. Bello, 2016

I want to express my sincere gratitude to my colleague and mentor Prof. Juan P. Bello of NYU for the years of fruitful collaboration that led to and made this work possible.

You can read the paper here:

Deep Convolutional Neural Networks and Data Augmentation For Environmental Sound Classification
J. Salamon and J. P. Bello
IEEE Signal Processing Letters, 24(3), pages 279 - 283, 2017.
[IEEE][PDF][BibTeX][Copyright]

Awkward screenshot of me talking about the work from the SONYC video