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Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch
Lightweight Python library for adding real-time multi-object tracking to any detector.
A Python library for audio data augmentation. Useful for making audio ML models work well in the real world, not just in the lab.
CREPE: A Convolutional REpresentation for Pitch Estimation -- pre-trained model (ICASSP 2018)
BirdNET analyzer for scientific audio data processing.
PyTorch Wildlife: a Collaborative Deep Learning Framework for Conservation.
Source code for models described in the paper "AudioCLIP: Extending CLIP to Image, Text and Audio" (https://arxiv.org/abs/2106.13043)
LEAF is a learnable alternative to audio features such as mel-filterbanks, that can be initialized as an approximation of mel-filterbanks, and then be trained for the task at hand, while using a ve…
Pytorch implementation of the CREPE pitch tracker
Python library for downloading, loading & working with sound datasets
Open source, scalable software for the analysis of bioacoustic recordings
Simplify camera trap image analysis with AI species recognition models based around the MegaDetector model
Package for aligning audio files through audio fingerprinting
PyTorch reimplementation of per-channel energy normalization for audio.
A python api for BirdNET-Lite and BirdNET-Analyzer
A tool to work with any format for annotating animal sounds
A python library for soundscape assessments
Koogu is a Python package for developing and using Machine Learning (ML) solutions in Animal Bioacoustics.
Pre-trained models for bioacoustic classification tasks
An Animal Independent Deep Learning Framework for Bioacoustic Signal Segmentation and Classification Including a Detailed User-Guide