ravdess-dataset
There are 1 repository under ravdess-dataset topic.
marcogdepinto / emotion-classification-from-audio-files
Understanding emotions from audio files using neural networks and multiple datasets.
Language:Python 395IliaZenkov / transformer-cnn-emotion-recognition
Speech Emotion Classification with novel Parallel CNN-Transformer model built with PyTorch, plus thorough explanations of CNNs, Transformers, and everything in between
Language:Jupyter Notebook 211Data-Science-kosta / Speech-Emotion-Classification-with-PyTorch
This repository contains PyTorch implementation of 4 different models for classification of emotions of the speech.
Language:Jupyter Notebook 179An in-depth analysis of audio classification on the RAVDESS dataset. Feature engineering, hyperparameter optimization, model evaluation, and cross-validation with a variety of ML techniques and MLP
Language:Jupyter Notebook 67ElenaRyumina / EMO-AffectNetModel
Dynamic and static models for real-time facial emotion recognition
Language:Jupyter Notebook 48LetianLee / Speech-Emotion-Recognition
An implementation of Speech Emotion Recognition, based on HuBERT model, training with PyTorch and HuggingFace framework, and fine-tuning on the RAVDESS dataset.
Language:Jupyter Notebook 25rudrajikadra / Speech-Emotion-Recognition-using-Librosa-library-and-MLPClassifier
In this project we use RAVDESS Dataset to classify Speech Emotion using Multi Layer Perceptron Classifier
Language:Jupyter Notebook 19AndreaLombax / Speech_emotion_recognition
In this work is proposed a speech emotion recognition model based on the extraction of four different features got from RAVDESS sound files and stacking the resulting matrices in a one-dimensional array by taking the mean values along the time axis. Then this array is fed into a 1-D CNN model as input.
Language:Python 8ThomasRigoni7 / Audio-emotion-recognition-RAVDESS
Implementation of various models to address the speech emotion recognition (SER) task, using python and pytorch.
Language:Python 4niveditapatel / SER-models
This repository is an import of the original repository that contains some of the models we had tested on the RAVDESS and TESS dataset for our research on Speech Emotion Recognition Models.
Language:Jupyter Notebook 3Shreyasi2002 / Speech-Emotion-Recognition--1
Speech Emotion Recognition based on RAVDESS dataset, - Summer 2021, Brain and Cognitive Science.
Language:Jupyter Notebook 3billy-enrizky / Speech-Emotion-Recognition
This project focuses on real-time Speech Emotion Recognition (SER) using the "ravdess-emotional-speech-audio" dataset. Leveraging essential libraries and Long Short-Term Memory (LSTM) networks, it processes diverse emotional states expressed in 1440 audio files. Professional actors ensure controlled representation, with 24 actors contributing
Language:HTML 2ayoubelaamri / Speech_Emotion_Recognition
Web app to detect emotion from speech using a 67% accuracy model built with 2D ConvNets trained on RAVDESS & SAVEE datasets
Language:Jupyter Notebook 1danielathome19 / Sung-EmotioNN-Detector
A convolutional neural network trained to classify emotions in singing voices.
Language:Python 1SpooderManEXE / Speech-Emotion-Recognition-using-MLP
The SER model is capable of detecting eight different male/female emotions from audio speeches using MLP and RAVDESS model
Language:Jupyter Notebook 1vikrant-3009 / SpeechEmotionRecognition
Emotion Recognition using Speech with the help of Librosa library, MLPClassifier and RAVDESS Database.
Language:Jupyter Notebook 1anki005 / Speech-Emotion-Recognition-using-Deep-Learning
Detected different emotions from live audio sample and model is trained on the RAVDESS dataset.
Language:Jupyter Notebook 0- Language:Python 0
mitul-shalehin / Facial-Emotion-and-Voice-Detection
Emotion and Voice Detection using Machine Learning Python Project. This Project about to detect human Voice and Facial emotion
Language:Jupyter Notebook 0OmkarNarvekar001 / ART_GENERATION_USING_SPEECH_EMOTIONS
Translation of speech to image directly without text is an interesting and useful topic due to the potential application in computer-aided design, human to computer interaction, creation of an art form, etc. So we have focused on developing Deep learning and GANs based model which will take speech as an input from the user, analyze the emotions associated with it and accordingly generate the artwork which has been demanded by the user which will in turn provide a personalized experience. The approach used here is convolutional VQGAN to learn a codebook of context-rich visual parts, whose composition is subsequently modeled with autoregressive transformer architecture. Concept of CLIP-Contrastive Language Image-Pre-Training, also uses transformers which is a model trained to determine which caption from a set of captions best fits with a given image is used in our project. The input speech is classified into 8 different emotions using MLP classifier trained of RAVDESS emotional speech audio dataset and this acts as a base filter for the VQGAN model. Text converted from speech plays an important role in producing the final output image using CLIP model. VQGAN+CLIP model together utilizes both emotions and text to generate a more personalized artwork.
Language:Jupyter Notebook 0prernasingh05 / CodeClause_Speech_Emotion_Recognition
Speech Emotion Recognition project by using Multi-Layer Perceptron Model with several customized attributes for optimal performance.
Language:Jupyter Notebook 0raho0 / emotion-recognition-cnn
emotion recognition using the ravdess dataset with CNN and Time series
Language:Jupyter Notebook 0simrann20 / QiCNN-algorithm
Audio-image classification of emotions
