Speech-Emotion-Classifier

General

This repository contains an emotion classifying pipeline based on python scripts. The pipeline takes as input audio files, processes them and feeds them to a pretrained model that will classify them based on what emotion they represent. The model was trained using approximately 600 audio files in Greek, each of them with a duration of 5 seconds. Due to the low number of samples, the accuracy of the model is about 75% which is not great, but not too bad either.

Environment

The project was created using Anaconda. The virtual environment's configuration is stored inside conda_venv.yml file. In order to recreate that environment, use the command (inside anaconda prompt):

conda env create -f conda_venv.yml

Data

The data used in this project were taken from Acted Emotional Speech Dynamic Database or AESDD for short. They can be found inside the data folder. To create the csv that will be used to train the model, execute the below command inside the Speech-Emotion-Classifier directory:

python3 preprocessing/audio_to_csv.py --src-dir data --dest-file converted/converted_audio.csv

Training

After creating the csv from the audio files, you can train the model by executing the command:

python3 training/model_training.py --src-file converted/converted_audio.csv --dest-file models/emotion_classifier.h5

In this repository, there is already a pretrained model inside the models folder, so the above step can be skipped. The optimal hyper parameters of the model, were choosen after an analysis that was perfomed. This analysis can be found inside Model_Tunning folder as a .ipynb file.

Deployment

The deployment of the model is executed through main.py script. The script, takes as input an audio file, and a .h5 file. The latter one, contains a pretrained model that will be used to predict the emotion of the audio file given. To run the script, use the following command:

python3 main.py --src-file my_audio_file.wav --model-file models/emotion_classifier.h5

The script will print the prediction, but if you want to save it in a file, you can use the '>' operator in UNIX-based systems

License

MIT

Free Software