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README.txt
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README.txt
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# KeywordSpotting
Keyword Spotting using Convolutional Neural Network
Reference:
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting
https://arxiv.org/abs/1703.05390
stream.py
- record .wav files in 3 seconds
- save in "data/name"
- the format of filename:
20171231_NAME_0000_0.wav (the last number = 0, without keyword)
20171231_NAME_0012_1.wav (the last number = 1, with keyword)
create_catalog.py
- read all .wav in data/ and create 2 catalogs of train.csv and validaiotn.csv
mfcc_tfrecord.py
- convert each .wav file in the certain catalog and save as .tfrecords
- enhance training efficiency
train_nontfrecord.py
- train model with raw .wav files
- save training result in graph/
- save model in ckpt/
train_tfrecord.py
- train model with .tfrecords
- save training result in graph/
- save model in ckpt/
inference.py
- edit line 21-22 to your own checkpoint(.meta) path
- continueously create(record) a test.wav(3 seconds) and do inference