Speech Emotion Recognition

Code for the paper "Real Time Speech Emotion Recognition using Machine Learning"

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Speech Emotion Recognition (SER) - Project aim to recognize emotion through speech. Databases used - Ravdess,Tess & Savee. Feature Extractor used - MFCC, STFT & Chroma, with three different extractor able to recognize emotion with high accuracy.

For Korean speech emotion detect, this model is trained by Korean dataset. There is no enough Korean dataset, so i tried to make this repo.

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.

Exploration of different audio features and CNN-based architectures for building an effective Speech Emotion Recognition (SER) system. The goal is to improve the accuracy of detecting emotions embedded in speech signals. The repository contains code, notebook, and detailed explanations of the experiments conducted.

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Implementation of a Persian Speech Emotion Recognition system with SVM model, based on the ShEMO paper

A speech emotion recognition (SER) system that won 1st place in a competition for a deep learning master-course. It uses a parallel CNN built using Keras and Tensorflow.

Utility and library to parse and modify SER movie file format.

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O projeto SerDigital é um repositório no GitHub dedicado a uma landing page moderna e atraente que promove o conceito de transformação digital. O objetivo deste projeto é criar uma página de destino que apresente informações sobre os benefícios da transformação digital e como ela pode impactar positivamente os negócios.

A deep learning solution using Convolutional Neural Networks and Wavelet Transform to tackle the Speech Emotion Recognition task.

Speech Emotion Recognition for Audio Data

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Multimodal emotion recognition IEMOCAMP