The Real-Time Speech Emotion Recognition Bot leverages OpenAI Whisper, Streamlit to analyze and identify emotions in spoken language in real-time.
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Updated
Dec 29, 2023 - Python
The Real-Time Speech Emotion Recognition Bot leverages OpenAI Whisper, Streamlit to analyze and identify emotions in spoken language in real-time.
This code is a fully functional speech emotion recognition algorithm
Official code for A Segment Level Approach to Speech Emotion Recognition using Transfer Learning, ACPR 2019
A script extracting features of emotionally charged speech
用于存放自然语言处理相关的代码。Store code related to NLP (Natural Language Processing).
The implementation of the paper, ``Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature-Based Decisions'' (pretraining-based part, acoustic features)
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.
A Django web application to detect emotion from the audio speech of a recording
SoulSyncopia: Emotion-Based Music Recommendation System
An attempt at the speech emotion recognition (SER) task on the CREMA-D dataset using TensorFlow 1D & 2D RCNN models.
Speech Emotion Recognition (SER) using CNNs and CRNNs Based on Mel Spectrograms and Mel Frequency Cepstral Coefficients (MFCCs)
Emotion Recognition using matlab (Machine Learning using SVM and Random Forest)
This project was for the pattern recognition course I studied in college. This was the beginning of dealing with neural networks and 2 CNN models were made, 1-d model and 2-d model to deal with different forms of the data, audio and image, respectively.
The PyTorch implementation of the additional temporal modeling on the DeepEmoCluster framework
speech_emotion_recognition
Final Year Project on Speech Emotion Recognition with CNN and LSTM.
SER and audio classification using both a Wav2Vec2 based model and an ASR->Bert pipeline, as well as utilizing a multimodal late-fusion model
This project is about Speech Emotion Recognition using machine learning models
Speech emotion recognition models for the Moody web application.
Solution for the LoopQ Prize 2022 - A speech emotion recognition ML solution
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