NLP-gender-recognition

a simple neural network with LSTM node, that recognize voices genders.

feature extraction

I use MFCC and etc features for this task, u can see feature_extraction.py

Run

read libs.txt file, and install tensorflow and keras too.

for running with my train and test extracted features :

python train.py

for extraction your own vioces put your train *.wav files into this folders:

├── data
│   ├── test
│   │   ├── female
│   │   └── male
│   └── train
│       ├── female
│       └── male

then for extract features of your voices (it put them in saved_features folder) run:

python save_features.py 

then for train, run:

python train.py

Best result

train accuracy => ~100%

test accuracy => ~88%

train_male samples count => 121

train_female samples count => 121

test_male samples count => 36

test_female samples count => 36

LSTM nodes count => 20

epochs => 500

accuracy of the train data

loss of the train data

accuracy of the test data

loss of the test data

any better idea? please open an issue, thanks.