Deep Learning with Audio Signals: Prepare, Process, Design, Expect

Transcript Choi: I’m Keunwoo Choi from Spotify, I’m working as a research scientist, and the talk title, Deep Learning with Audio Signal, will be a gentle, quick introduction about, what would you do, how would you do when you happen to be in a situation where you suddenly have to work on audio signal, or music maybe, speech, sound, whatever, with the machine learning. A very quick introduction of myself, I studied some of acoustic, a bit of machine learning and MIR, music information retrieval. Now I’m in a team called MIQ, which is mostly in New York and some in London, and everyone’s working on a slightly different topic within an umbrella named MIR, which is basically music and machine learning, mostly music signals and machine learning. After this talk you will probably have some idea about how you start with your task with the machine learning and audio signal, and maybe after working on and on you will quickly get to know a bit more about the thing that I cover with this talk, so think of it as a good starting point or baseline, I’m assuming you’re a beginner on audio, and music, and speech, or sound- and maybe also some of MIR, or deep learning and machine learning. We’ll be covering pretty much every bit of everything very shallowly and quickly. It doesn’t include how would you do music recommendation with Spotify, that’s a bit different topic from my talk. The content of the talk will be about these four different sections, this chronological order about the whole task. How would you prepare the dataset and how would you deal with the audio signal? How do you process the signals so that it could be better and it could be nicer to the model you […]

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