Metadata-Version: 2.1
Name: vistec-ser
Version: 0.2.3a1
Summary: Speech Emotion Recognition models and training using Tensorflow 2.x
Home-page: https://github.com/tann9949/vistec-ser
Author: Chompakorn Chaksangchaichot
Author-email: chompakorn.cc@gmail.com
License: UNKNOWN
Description: # Vistec-AIS Speech Emotion Recognition
        ![python-badge](https://img.shields.io/badge/python-%3E%3D3.6-blue?logo=python)
        ![tensorflow-badge](https://img.shields.io/badge/tensorflow-%3E%3D2.4.0-orange?logo=tensorflow)
        ![license](	https://img.shields.io/github/license/tann9949/vistec-ser)
        
        ![Upload Python Package](https://github.com/tann9949/vistec-ser/workflows/Upload%20Python%20Package/badge.svg)
        ![Training](https://github.com/tann9949/vistec-ser/workflows/Training/badge.svg)
        
        ![Code Grade](https://www.code-inspector.com/project/17426/status/svg)
        ![Code Quality Score](https://www.code-inspector.com/project/17426/score/svg)
        
        Speech Emotion Recognition Model and Inferencing using Tensorflow 2.x
        
        ## Installation
        ### From Pypi
        ```shell
        pip install vistec-ser
        ```
        
        ### From source
        ```shell
        git clone https://github.com/tann9949/vistec-ser.git
        cd vistec-ser
        python setup.py install
        ```
        
        ## Usage
        ### Train with Your Own Data
        We provide Google Colaboratory example for training `Emo-DB` dataset using our repository.
        
        [![VISTEC-depa Thailand Artificial Intelligence Research Institute](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1wc9CUuGrQHw29o3g9Iy-Wmjksebgtmau?usp=sharing)
        
        #### Preparing Data
        To train with your own data, you need to prepare 2 files:
        1. `config.yml` (see an example in [tests/config.yml](tests/config.yml)) - This file contains a
           configuration for extracting features and features augmentation.
        2. `labels.csv` - This will be a `.csv` file containing 2 columns mapping audio path to its emotion.
            - **Your `.csv` file should contain a header** (as we will skip the first line when reading).
            - **Currently, we only support 5 emotions (`neutral`, `anger`, `happiness`, `sadness`, and `frustration`) if
            you want to add more, modify `EMOTIONS` variable in [dataloader.py](vistec_ser/datasets/dataloader.py)**
              
        #### Preparing a model
        Now, prepare your model, you can implement your own model using `tf.keras.Sequential` or using provided model
        in [models.py](vistec_ser/models/network.py).
        
        #### Training
        For training a model, create a `DataLoader` object and use method `.get_dataset` to get `tf.data.Dataset` used 
        for training. `DataLoader` will also use `FeatureLoader` which will read `config.yml`. 
        The dataset will automatically pad a batch according to the longest sequence length.
        
        ### Inferencing
        *TODO*
        
        ## Reference
        This repository structure was inspired by [TensorflowASR](https://github.com/TensorSpeech/TensorFlowASR) by 
        Huy Le Nguyen ([@usimarit](https://github.com/usimarit)). Please check it out!
        
        
        ## Author & Sponsor
        [![VISTEC-depa Thailand Artificial Intelligence Research Institute](https://airesearch.in.th/assets/img/logo/airesearch-logo.svg)](https://airesearch.in.th/)
        
        Chompakorn Chaksangchaichot
        
        Email: [chompakornc_pro@vistec.ac.th](chompakornc_pro@vistec.ac.th)
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=3.6
Description-Content-Type: text/markdown
