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GitHub topics: audio-emotion-detection

rishiswethan/Video-Audio-Face-Emotion-Recognition

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

Language: Jupyter Notebook - Size: 126 MB - Last synced at: about 12 hours ago - Pushed at: over 1 year ago - Stars: 75 - Forks: 18

SaurabhJalendra/Trailer-Movie-Analysis-App

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.

Language: Jupyter Notebook - Size: 7.71 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

PrashanthaTP/audio-emotion-detector

Detection of emotion in audio using Machine Learning(SVM)

Language: Python - Size: 1.67 MB - Last synced at: about 2 months ago - Pushed at: almost 2 years ago - Stars: 6 - Forks: 3

Pegah-Ardehkhani/Speech-Emotion-Recognition

Emotion Recognition Using Audio Speech Files

Language: Jupyter Notebook - Size: 1.41 MB - Last synced at: 8 days ago - Pushed at: almost 3 years ago - Stars: 3 - Forks: 0

Jayanth-MKV/emotion2vec-speech-emotion-detection-api

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.

Language: Python - Size: 4.88 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 0

WangJingyao07/Multimodal-Sentiment-Analysis-for-Health-Navigation

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

Language: Jupyter Notebook - Size: 2.43 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 6 - Forks: 0