Predicting depression from acoustic features of speech using a Convolutional Neural Network.
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Updated
Oct 29, 2018 - Python
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
Use machine learning models to detect lies based solely on acoustic speech information
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.
Tools and functions for neural data processing and analysis in python
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.
🎵 A repository for manually annotating files to create labeled acoustic datasets for machine learning.
Mobile application that uses audio sampling to perform acoustic mapping 🔊
A dynamically adaptable neural network-based replay spoofing attack detection system.
Script to extract acoustic features from speech using OpenSmile toolkit.
Multimodal Exponentially Modified Gaussians with Optional Oscillation
Calculate temporal and spectral envelope of vowel
predicting music track success (revenue) via acoustic and metadata features
An ensemble bagged trees classification approach for monitoring of the engine conditions and fault diagnosis using Visual Dot Patterns of acoustic and vibration Signals
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