gender recognize using pre-processed voice data by deep neural networks
from kaggle and excel files are also attached in this repo
This repo contains two structures of neural networks to recognize gender of pre-processed voice data (2-classification problem)
to train a model using 3 fully connected layers, and finnaly a model parameters file would be saved. It is 2.07MB in size
and the accuracy in training set would approch nearly 100% and 96% in testing set.
python with_conv1d.py to train a model using conv1d with much more layers depth than the fully connected, and the residual learning strategy is used to handle the deeper depth training.
finnaly a model parameters file would be saved and it is 57.2MB in size (much bigger than fully connected layers model)
the accuracy in training set would approch nearly 100% and 97% in testing set (quite slight improvement~ but it works).
AFTER TRAINING, you can run
python test_model.py -f and
python test_model.py -c to test the trained fully connected model and conv1d model in test set respectively,
and it would produce a txt file contains the female probabilities of test data per row.