Predicting depression from acoustic features of speech using a Convolutional Neural Network.
-
Updated
Oct 29, 2018 - Python
8000
Predicting depression from acoustic features of speech using a Convolutional Neural Network.
A Python library for measuring the acoustic features of speech (simultaneous speech, high entropy) compared to ones of native speech.
VQ-VAE for Acoustic Unit Discovery and Voice Conversion
Source code complementing our paper for acoustic event classification using convolutional neural networks.
Vector-Quantized Contrastive Predictive Coding for Acoustic Unit Discovery and Voice Conversion
Acoustic mosquito detection code with Bayesian Neural Networks
The project is related to the development of labs for the ITMO Digital Signal Processes
The project is related to the development of labs for the ITMO Speaker Recognition Course.
Use machine learning models to detect lies based solely on acoustic speech information
Tools and functions for neural data processing and analysis in python
keras_multi_target_signal_recognition Underwater single channel acoustic multiple targets recognition using ResNet, DenseNet, and Complex-Valued convolutional nerual networks. keras-gpu 2.2.4 with tensorflow-gpu 1.12.0 backend.
🎵 A repository for manually annotating files to create labeled acoustic datasets for machine learning.
An ensemble bagged trees classification approach for monitoring of the engine conditions and fault diagnosis using Visual Dot Patterns of acoustic and vibration Signals
A curated collection of research papers with open-source implementations/datasets focused on in-situ process monitoring and adaptive control in laser-based additive manufacturing.
Mobile application that uses audio sampling to perform acoustic mapping 🔊
Script to extract acoustic features from speech using OpenSmile toolkit.
Calculate temporal and spectral envelope of vowel
A research-based voice analysis platform for mental health screening using machine learning
A BCNN prediction pipeline to discover mosquito sounds from audio.
predicting music track success (revenue) via acoustic and metadata features
Add a description, image, and links to the acoustic-features topic page so that developers can more easily learn about it.
To associate your repository with the acoustic-features topic, visit your repo's landing page and select "manage topics."