https://github.com/bagustris/w2v2-ag
Science Score: 26.0%
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○CITATION.cff file
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○Scientific vocabulary similarity
Low similarity (9.2%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: bagustris
- License: mit
- Language: Python
- Default Branch: master
- Size: 207 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Predict Age and Gender from Audio Files
This is a Python CLI wrappers for Audeering public age and gender model (Original repo: https://github.com/audeering/w2v2-age-gender-how-to). This script uses a pre-trained ONNX model to predict the age and gender of a person from an audio file and live microphone.
Installation
To use this script, you need to have Python 3 installed on your system. You also need to install the following Python packages:
numpyaudiofileaudresampleaudeeraudonnx
More details about these packages can be found in the requirements.txt file.
You can install these packages using pip -r requirements.txt under (Mini)conda environment:
```bash $ conda create -n w2v2-ag python=3.9 $ conda activate w2v2-ag $ pip install -r requirements.txt
```
Usage
To use the script, run the following command in your terminal:
$ python predict_ag_from_file.py [-h] [-i INPUT]
The script takes the following arguments:
-h,--help: Show the help message and exit.-i INPUT,--input INPUT: Path to input audio file. Default is./yachinene.wav.
The script outputs the predicted age and gender of the person in the audio file.
Here's an example usage of the script:
```bash
predicting age and gender from file
$ python predictagfrom_file.py -i input.wav Age: 21 Gender or Child: female
predicting age and gender from live microphone
$ python predictaglive.py ```
The first will predict the age and gender of the person in the input.wav file.
If you don't specify an input file, the script will use the default file ~/wav/yachinene.wav.
The latter command will predict the age and gender of the live microphone.
License
This script is licensed under the MIT License. See the LICENSE file for more information.
Owner
- Name: Bagus Tris Atmaja
- Login: bagustris
- Kind: user
- Location: Tsukuba
- Company: AIST
- Website: http://www.bagustris.blogspot.com
- Twitter: btatmaja
- Repositories: 221
- Profile: https://github.com/bagustris
Researcher @aistairc @VibrasticLab
GitHub Events
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| Name | Commits | |
|---|---|---|
| Bagus Tris Atmaja | b****s@y****m | 26 |
| Johannes Wagner | j****r@a****m | 4 |
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- Total pull request authors: 1
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