List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.

Pitch-shift audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

⚡ Blazing fast audio augmentation in Python, powered by GPU for high-efficiency processing in machine learning and audio analysis tasks.

A tool/script for batch speech data enhancement with speed/volume/RIRS/MUSAN

A python library for generating different permutations of audible segments from audio files.

A ready-to-use pytorch dataloader for audio classification, speech classification, speaker recognition, etc. with in-GPU augmentations

Implementation of audio, image, and spectrogram augmentation techniques provided by the librosa, Keras and audiomentations

Audio data loading and augmentations in JAX

End-to-end pipeline for training a custom keyword detection model with TensorFlow & TFLite expor

Python augmentation toolkit for Automatic Music Transcription datasets

This repository contains the code and methodology used for the BirdCLEF 2024 Kaggle competition, where I achieved a rank of 55th out of 974 participants, earning a bronze medal. The goal of this competition was to build a model that can accurately classify bird sounds.

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.

A Convolutional Neural Network that distinguishes between the speakers emotions. Comes with multiple preprocessors to improve the models performance.

Converting text to audio and applying audio augmentation