Speech Emotion Recognition
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Updated
Aug 22, 2023 - Python
Speech Emotion Recognition
Code for the paper "Real Time Speech Emotion Recognition using Machine Learning"
Backend project to replicate a Kanban Board (like Trello or Jira). Implemented with Springboot, jOOQ and MySQL.
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.
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.
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.
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.
Serverside Active Directory authentication boilerplate user express and LDAP
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.
Utility and library to parse and modify SER movie file format.
Context and System Fusion in Post-ASR Emotion Recognition with Large Language Models | Submission to GenSEC Task 3 (LLM-Based Post ASR Speech Emotion Recognition Challenge)
Atualização de domínio da UNI7: de @uni7.edu.br para @sempreuni7.com.br
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