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

Human Emotion Understanding using multimodal dataset.

ADHD_Recognition with personal voice

Predictive modeling of users' interpersonal characteristics by the sound of their voices and manner of speaking.

CNN for language-independent emotion prediction on a dataset of English and French speech samples.

Visual Studio Code extension that adds syntax highlighting, diagnostics and IntelliSense features for openSMILE configuration files

speech emotion recognition, augmentation

Script to extract acoustic features from speech using OpenSmile toolkit.

acoustic low-level descriptors (LLD) feature extraction via the opensmile software

ADHD_Recognition with personal voice

Codes for extracting features of IEMOCAP with Open Smile tool kit

A stand-alone OpenSmile plugin for the Cordova framework.

Official PCL Team submission for the IEEE ICASSP 2026 SAND Challenge (Task 1). A hybrid framework fusing OpenSMILE acoustic features and Wav2Vec2 deep embeddings to classify dysarthria severity in ALS patients.

This is a project dedicated to the classification of emotional speech and was created in class with Prof. Dr. Burkhardt at Technische Universität Berlin.

This repository contains an emotion recognition system developed on 2,300+ WAV files using acoustic feature extraction and machine learning techniques.

A comprehensive framework for detecting hate speech in the low-resource Telugu language using multimodal (audio and text) analysis

Research project analyzing the impact of audio features on Spotify podcast performance.

Digit Recogniser step by step.

This repository contains a complete machine learning pipeline for Speech Emotion Recognition (SER) using Deep Neural Networks (DNNs).