The repo contains an audio emotion detection model, facial emotion detection model, and a model that combines both these models to predict emotions from a video

Emotion recognition methods through facial expression, speeches, audios, and multimodal data

This API utilizes a pre-trained model for emotion recognition from audio files. It accepts audio files as input, processes them using the pre-trained model, and returns the predicted emotion along with the confidence score. The API leverages the FastAPI framework for easy development and deployment.

Detection of emotion in audio using Machine Learning(SVM)

Emotion Recognition Using Audio Speech Files

In this project we classify negative audio emotions , data is combined between ( RAVDESS/ SAVEE/TESS and CREMA-D)

Video analysis system that extracts emotional patterns, audio characteristics, and visual elements from trailers and other content. Provides data-driven feedback on narrative flow, emotional engagement, pacing, and predictability through a pipeline of specialized Jupyter notebooks.