Voice Gender Classifier

🚀 Voice gender classifier

This repository contains inference code for a pre - trained human voice gender classifier. You can also try the Huggingface online demo.

🚀 Quick Start

This repo provides an easy - to - use pre - trained voice gender classifier. You can quickly start using it following the steps below.

✨ Features

• Inference code for a pre - trained voice gender classifier is provided.
• An online demo on Huggingface is available for quick testing.

📦 Installation

First, clone the original github repository.

git clone https://github.com/JaesungHuh/voice-gender-classifier.git

Then, install the packages via pip.

cd voice-gender-classifier
pip install -r requirements.txt

💻 Usage Examples

Basic Usage

import torch

from model import ECAPA_gender

# You could directly download the model from the huggingface model hub
model = ECAPA_gender.from_pretrained("JaesungHuh/voice-gender-classifier")
model.eval()

# If you are using gpu .... 
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)

# Load the audio file and use predict function to directly get the output
example_file = "data/00001.wav"
with torch.no_grad():
    output = model.predict(example_file, device=device)
    print("Gender : ", output)

📚 Documentation

Pretrained weights

For those who need pretrained weights, please download it here.

Training details

State - of - the - art speaker verification model already produces good representation of the speaker's gender.

I used the pretrained ECAPA - TDNN from TaoRuijie's repository, added one linear layer to make two - class classifier, and finetuned the model with the VoxCeleb2 dev set.

The model achieved 98.7% accuracy on the VoxCeleb1 identification test split.

Caveat

⚠️ Important Note

The training dataset I've used for this model (VoxCeleb) may not represent the global human population. Please be careful of unintended biases when using this model.

Reference

• Original github repository
• I modified the model architecture from TaoRuijie's repository.
• For more details about ECAPA - TDNN, check the paper.

📄 License

This project is licensed under the MIT license.