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