TalksDeep Learning for Signal Processing

Date
Type
Talk
Language
English
Length
25 minutes

About this talk

Deep learning is a powerful technique for tasks as classification or recognition. However, it can be used in signal processing for tasks that need to recover the full signal like denoising or source separation. I will present my work on deep learning for music source separation, particularly some strategies for data augmentation which makes the framework more robust to variations one might expect in real-life. This research is reproducible and is accompanied by a python library which makes it easy to work with large datasets.

Photos (1)

Photo of Deep Learning for Signal Processing
In the gallery of Python June Meetup, with the post it was published in.