The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
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Updated
Feb 7, 2023 - Jupyter Notebook
The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
speech emotion recognition using a convolutional recurrent networks based on IEMOCAP
💎 A list of accessible speech corpora for ASR, TTS, and other Speech Technologies
Speaker independent emotion recognition
Lightweight and Interpretable ML Model for Speech Emotion Recognition and Ambiguity Resolution (trained on IEMOCAP dataset)
Bidirectional LSTM network for speech emotion recognition.
TensorFlow implementation of "Multimodal Speech Emotion Recognition using Audio and Text," IEEE SLT-18
How to use our public wav2vec2 dimensional emotion model
Using Convolutional Neural Networks in speech emotion recognition on the RAVDESS Audio Dataset.
This repository contains PyTorch implementation of 4 different models for classification of emotions of the speech.
A collection of datasets for the purpose of emotion recognition/detection in speech.
Wav2Vec for speech recognition, classification, and audio classification
[ACL 2024] Official PyTorch code for extracting features and training downstream models with emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation
Speech Emotion Recognition
Predicting various emotion in human speech signal by detecting different speech components affected by human emotion.
The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.
[ICASSP 2023] Official Tensorflow implementation of "Temporal Modeling Matters: A Novel Temporal Emotional Modeling Approach for Speech Emotion Recognition".
Official implementation of INTERSPEECH 2021 paper 'Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings'
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