Dear all (apologies for cross-posting),
We’d like to invite you to the AES Virtual Symposium: Applications of Machine Learning in Audio
The Audio Engineering Society invites academic and industry audio researchers and practitioners to participate in the first AES event highlighting Machine Learning. The symposium will focus on machine learning as it relates to applications in digital signal processing and audio engineering. Topics will include, but are not limited to, practical applications of machine learning in audio engineering, including:
The virtual event will take place online September 28-29th and include nine hours of programming consisting of pre-recorded presentations with live Q and A and parallel sessions in dedicated breakout rooms.
To participate in the parallel session, please submit a Précis with less than or equal to 500 words, summarizing the work and highlighting novel unpublished or unpresented aspects of the work, using this form.
Accepted presenters will submit a pre-recorded video between 5 and 10 minutes long, which attendees of the symposium will have the opportunity to view beforehand. During the session, presenters will be online in an interactive video channel, where they may present more material (e.g., slides) and answer questions from attendees.
Note that submissions are not peer-reviewed, and one can present work that has been or will be submitted elsewhere (if the other venue does not explicitly forbid it). If the symposium receives more submissions than capacity allows, the program chairs will prioritize work that focuses on new results or unpublished work.
Andy Sarroff, Christian Uhle, and Gordon Wichern