speech-emotion-recognition

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

speech emotion recognition using a convolutional recurrent networks based on IEMOCAP

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.

Speech emotion recognition implemented in Keras (LSTM, CNN, SVM, MLP) | 语音情感识别

Bidirectional LSTM network for speech emotion recognition.

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Speaker independent emotion recognition

Lightweight and Interpretable ML Model for Speech Emotion Recognition and Ambiguity Resolution (trained on IEMOCAP dataset)

TensorFlow implementation of "Multimodal Speech Emotion Recognition using Audio and Text," IEEE SLT-18

Implementation of Speech Emotion Recognition using DNN-ELM

The code for our INTERSPEECH 2020 paper - Jointly Fine-Tuning "BERT-like'" Self Supervised Models to Improve Multimodal Speech Emotion Recognition

Speech Emotion Recognition from raw speech signals using 1D CNN-LSTM

Using Convolutional Neural Networks in speech emotion recognition on the RAVDESS Audio Dataset.

A collection of datasets for the purpose of emotion recognition/detection in speech.

Keras Implementation of Deepmind's WaveNet for Supervised Learning Tasks

Speech Emotion Recognition Using Deep Convolutional Neural Network and Discriminant Temporal Pyramid Matching

Wav2Vec for speech recognition, classification, and audio classification

Implementation of the paper "Improved End-to-End Speech Emotion Recognition Using Self Attention Mechanism and Multitask Learning" From INTERSPEECH 2019

This repository contains PyTorch implementation of 4 different models for classification of emotions of the speech.

[ICASSP19] An Interaction-aware Attention Network for Speech Emotion Recognition in Spoken Dialogs

TensorFlow implementation of "Attentive Modality Hopping for Speech Emotion Recognition," ICASSP-20

Classifying Audio to Emotion

Speech_Emotion_detection-CNN,SVM,RF,DT,MLP

Adversarial Auto-encoders for Speech Based Emotion Recogntion

In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity for their ability to perform well without any input hand-crafted features. Speech emotion on sets obtained from RAVDESS corpus is classified using a conventionally used Support Vector Machine (SVM) and its performance is compared to that of a bidirectional long short-term memory (LSTM).

Repository of code for Speech emotion recognition using voiced speech and attention model, submitted to ICSigSys 2019

Implementation of the paper "Emotion Identification from raw speech signals using DNNs"

Bimodal emotion recognition through facial expressions and speech

ShEMO: a large-scale validated database for Persian speech emotion detection

Speech Emotion Recognition using MLP Classifier.