Presentation: Deep Learning with Audio Signal: Prepare, Process, Design, Expect

Track: Groking Timeseries & Sequential Data

Location: Cyril Magnin I + II

Duration: 12:00pm - 12:40pm

Day of week: Wednesday

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Abstract

Is deep learning Alchemy? No! But it heavily relies on tips and tricks, a set of common wisdom that probably works for similar problems. In this talk, I’ll introduce what the audio/music research societies have discovered while playing with deep learning when it comes to audio classification and regression -- how to prepare the audio data, pre- and post-process them, how to design the networks (or which one to steal from), and what we can expect as a result.

Speaker: Keunwoo Choi

Research Scientist @Spotify

  • 2018.07 - present: Spotify
  • 2014 - 2018: PhD student of Centre for Digital Music, Queen Mary University of London, UK

 

 

Find Keunwoo Choi at

2019 Tracks

  • Groking Timeseries & Sequential Data

    Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.