cs230's Issues
Create splits of ESC50
Construct a pipeline to reproduce vggish features from youtube videos
Write a pipeline to pull AudioSet data
Use the VGG-like features.
Implement a linear regression baseline
Run audio through hardware filter
Query the audioset.sqlite3 file to build our dataset
taking the top 50 auduioset classes, and limiting them to no more than 10k examples per class. This way we could build a dataset that wouldn’t be 90% music and voice (as the current dataset from Google has)
Test model on dev set with and without filtered data in train set
Write a MAKEFILE to download the dataset
Make a test set using the hydrophone
Copy Piczak paper architecture
(slightly simplified, we don't need 5000 hidden units...)
Tune hyperparameters
Build, train, and serialize a base model
Integrate Github with slack
This is probably already working, but I want to make sure it's working.
Create/clean additional dataset sources
Bundle hyperparameters into the .env file
Duplicate the results from github.com/anuragkr90/weak_feature_extractor
Implement a Mel-frequency cepstrum
Split audioset into test/dev/train
Find a fast way to build a tensorflow dataset from .tfrecord files
Modularize datasets and feature extractors
Filter youtube videos through FIR filter before running them through vggish
Depends on #22
Train baseline model on Audioset (and validate)
Evaluate whether we need a CNN (as suggested by Shenoi)
Check to see performance when we consider just 3 seconds of data, then check performance when we consider 4 seconds, etc... and see if we get better.
Build an software audio filter
Make a visualizer for the spectrograms
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