Metadata-Version: 2.1
Name: audio_classification_models
Version: 1.0.9
Summary: Tensorflow Audio Classification Models. https://github.com/awsaf49/audio_classification_models
Home-page: https://github.com/awsaf49/audio_classification_models
Author: Awsaf
Author-email: awsaf49@gmail.com
License: MIT
Keywords: tensorflow audio speech classification
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.md

<div align=center><img src="https://user-images.githubusercontent.com/36858976/175043546-a32a0c92-3797-4a4f-a87b-ec8d046dba7f.png" width=300></div>
<p align="center">
<a href="https://github.com/TensorSpeech/TensorFlowASR/blob/main/LICENSE">
  <img src="https://img.shields.io/badge/License-MIT-yellow.svg">
</a>
<img alt="python" src="https://img.shields.io/badge/python-%3E%3D3.6-blue?logo=python">
<img alt="tensorflow" src="https://img.shields.io/badge/tensorflow-%3E%3D2.5.1-orange?logo=tensorflow">
<h2 align="center">
<p>Audio Classification Models in Tensorflow 2.0</p>
</h2>
</p>
<p align="center">
This library utilizes some automatic speech recognition architectures such as ContextNet, Conformer, etc for audio classification.
</p>

  
## Installation
```shell
pip install -U audio_classification_models
```
or
```shell
pip install git+https://github.com/awsaf49/audio_classification_models
```

## Usage
```py
import audio_classification_models as acm
model = acm.Conformer(pretrain=True)
```

## Acknowledgement
* [TensorflowASR](https://github.com/TensorSpeech/TensorFlowASR)


