This model recognizes gender by analyzing real call recording. It is a Keras implementation of a CNN&LSTM which predict long audio with short audio.

• Python3.6+
• Keras2.3
• scipy, numpy, Pandas, pyAudioAnalysis, pydub, h5py
• Webrtcvad2.0.10
• Sklearn

Generate short audio by:

generate_sample.py

It will generate short audio from long audio by VAD(Voice Activity Detection),then you need to label them and put them in three folders.

Train data files:

├── ...
├── data
│   ├── long_audio          #wav files before VAD
│   ├── model                  #save model
│   └── short_audio         #wav files after VAD
│──────├── female          # wav files with label female
│──────├── male          #  wav files with label male
│──────└── noise          # wav files with label noise
└── ...

• Set train=true in:

	main.py

• It will create feature and label data at first time:

	x.npy y.npy label.txt

• If you use your own data, please delete them first.

• Set train=false and model_path in:

	main.py

• https://github.com/tyiannak/pyAudioAnalysis
• https://github.com/wiseman/py-webrtcvad