## 陈狗翔 / gender-voice .gitee-modal { width: 500px !important; }

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# gender-voice

gender recognize using pre-processed voice data by deep neural networks

## Requirements

• tensorflow (for tensorboard logging)
• pytorch (>=1.0, 1.0.1 used in my experiment)
• pandas and other common python packages

## Dataset

from kaggle and excel files are also attached in this repo

## Usage

This repo contains two structures of neural networks to recognize gender of pre-processed voice data (2-classification problem)

run python with_fully_connect.py 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.

run 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.

gender recognize using pre-processed voice data by deep neural networks spread retract

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