https://github.com/devslem/fmcc
Female-Male Classification Challenge
https://github.com/devslem/fmcc
Last synced: 4 months ago
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Female-Male Classification Challenge
- Host: GitHub
- URL: https://github.com/devslem/fmcc
- Owner: DevSlem
- License: mit
- Created: 2023-05-18T03:40:09.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-06-17T14:56:22.000Z (almost 3 years ago)
- Last Synced: 2025-05-07T12:55:00.529Z (about 1 year ago)
- Language: Visual Basic 6.0
- Size: 389 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# FMCC
Female-Male Classification Challenge
1. 학습용 코드 `module/train.py`
2. 모델 `results/saved_model`
3. 테스트용 코드 `module/test.py`
4. 테스트 결과 파일 `results/voyager_test_results.txt`
5. 실행 설명서 `README.md`
6. 논문 형식 결과 보고서 `fmcc_report.hwp`
## Installation
If you use Anaconda, create an Anaconda environment first by entering the command below (optional):
```bash
conda create -n fmcc python=3.9 -y
conda activate fmcc
```
Install packages:
```bash
pip install ipykernel==6.23.1
pip install scikit-learn==1.2.2
pip install matplotlib==3.7.1
```
## Run
**Enter the following commands to run:**
```shell
python main.py # train
python main.py -e # evaluation
perl eval.pl results/voyager_test_results.txt data/fmcc_test_ref.txt # print accuracy
```
**Detail Options:**
```
Usage:
python main.py [options]
Options:
-p --plot Whether to plot [default: False].
-i --inference Whether to inference or test [default: False].
-e --eval Whether to evaluate [default: False].
```
- During the evaluation, the gender classification results for male and female voices are generated from unlabeled data and saved in the file `voyager_test_results.txt`.
- During inference, using the given test data, you can obtain results such as accuracy and other metrics.
- The trained model is saved in the `saved_model` file during training.
```
Config:
train_file_list file containing information about the train data list.
test_file_list file containing information about the test data list.
eval_file_list file containing information about the evaluation data list.
train_file_dir directory name where the train audio files are located.
test_file_dir directory name where the test audio files are located.
eval_file_dir directory name where the evaluation audio files are located.
```
- If you run evaluation mode (by entering `python main.py -e`), set the files for evaluation by configuring the `eval_file_dir` and `eval_file_list` in the `config.py`.