cs230's People
cs230's Issues
Make a test set using the hydrophone
Build, train, and serialize a base model
Create/clean additional dataset sources
Train baseline model on Audioset (and validate)
Create splits of ESC50
Filter youtube videos through FIR filter before running them through vggish
Depends on #22
Write a pipeline to pull AudioSet data
Use the VGG-like features.
Bundle hyperparameters into the .env file
Integrate Github with slack
This is probably already working, but I want to make sure it's working.
Make a visualizer for the spectrograms
Test model on dev set with and without filtered data in train set
Modularize datasets and feature extractors
Construct a pipeline to reproduce vggish features from youtube videos
Find a fast way to build a tensorflow dataset from .tfrecord files
Write a MAKEFILE to download the dataset
Implement a linear regression baseline
Tune hyperparameters
Duplicate the results from github.com/anuragkr90/weak_feature_extractor
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.
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)
Build an software audio filter
Run audio through hardware filter
Split audioset into test/dev/train
Copy Piczak paper architecture
(slightly simplified, we don't need 5000 hidden units...)
Implement a Mel-frequency cepstrum
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