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David Goedicke edited this page Aug 8, 2020
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a.k.a.
(As an homage to Tensorflow for Poets.)
In this workshop, we will teach you how to design audio classifiers using neural nets. We will guide you through the steps of collecting and organizing data, generating spectrographs, training a network, and the using that network to detect audio in realtime. We will use Jupyter notebooks, Python3, pyTorch, and Librosa to play with neural nets that can detect different music and different audio sources.
Time | Monday | Tuesday | Wednesday | Thursday | Friday |
---|---|---|---|---|---|
9am | Introductions | Review/Q&A | Review/Q&A | Review/Q&A | Review/Q&A |
10-noon | Neural Nets | Collecting & Analyzing Sounds, Introduce Final Project | Group-making | Applications of AI for Sound | Project time |
noon-1:30 | Lunch | Lunch | Lunch | Lunch | Lunch |
1:30-3:30 | Lab Setup | Home Sounds Dataset Activity | Designing Interaction | Final Project | Project Time/ Show and Tell |
3:30-4pm | Cats & Dogs Lab | Home Sounds Dataset Activity | Wizard Lab | Final Project | Happy Hour |
Lab 1. Cats and Dogs--binary classification
Lab 2. Making the Home Sounds Dataset
Day 2 slides: More on NNs
Collecting and Analyzing Sounds
Day 4 slides: Day4_presentation