⚡ Blazing fast audio augmentation in Python, powered by GPU for high-efficiency processing in machine learning and audio analysis tasks.
-
Updated
Jan 19, 2024 - Python
⚡ Blazing fast audio augmentation in Python, powered by GPU for high-efficiency processing in machine learning and audio analysis tasks.
List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.
Converting text to audio and applying audio augmentation
Pitch-shift audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.
A ready-to-use pytorch dataloader for audio classification, speech classification, speaker recognition, etc. with in-GPU augmentations
Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.
A python library for generating different permutations of audible segments from audio files.
Implementation of audio, image, and spectrogram augmentation techniques provided by the librosa, Keras and audiomentations
A Convolutional Neural Network that distinguishes between the speakers emotions. Comes with multiple preprocessors to improve the models performance.
SoundScaper is an audio augmented reality mobile application that allows users to author, save and reload virtual, and spatially interactive, three-dimensional binaural soundscapes within physical, real world spaces.
Add a description, image, and links to the audio-augmentation topic page so that developers can more easily learn about it.
To associate your repository with the audio-augmentation topic, visit your repo's landing page and select "manage topics."