crlandsc
Audio ML engineer and researcher with a passion for music and spatial audio.
WhitebalanceChicago, IL
crlandsc's Stars
suno-ai/bark
🔊 Text-Prompted Generative Audio Model
modularml/mojo
The Mojo Programming Language
facebookresearch/demucs
Code for the paper Hybrid Spectrogram and Waveform Source Separation
mdeff/fma
FMA: A Dataset For Music Analysis
archinetai/audio-diffusion-pytorch
Audio generation using diffusion models, in PyTorch.
jim-schwoebel/voice_datasets
🔊 A comprehensive list of open-source datasets for voice and sound computing (95+ datasets).
Audio-AGI/AudioSep
Official implementation of "Separate Anything You Describe"
acids-ircam/RAVE
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
haoheliu/versatile_audio_super_resolution
Versatile audio super resolution (any -> 48kHz) with AudioSR.
csteinmetz1/auraloss
Collection of audio-focused loss functions in PyTorch
lucidrains/ema-pytorch
A simple way to keep track of an Exponential Moving Average (EMA) version of your pytorch model
bytedance/uss
This is the PyTorch implementation of the Universal Source Separation with Weakly labelled Data.
Yuan-ManX/audio-development-tools
This is a list of sound, audio and music development tools which contains machine learning, audio generation, audio signal processing, sound synthesis, spatial audio, music information retrieval, music generation, speech recognition, speech synthesis, singing voice synthesis and more.
crlandsc/tiny-audio-diffusion
A repository for generating and training short audio samples with unconditional waveform diffusion on accessible consumer hardware (<2GB VRAM GPU)
amanteur/BandSplitRNN-PyTorch
Unofficial PyTorch implementation of Music Source Separation with Band-split RNN
gladia-research-group/multi-source-diffusion-models
crlandsc/Music-Demixing-with-Band-Split-RNN
An unofficial PyTorch implementation of Music Source Separation with Band-split RNN for MDX-23 ("Label Noise" Track)
satvik-venkatesh/you-only-hear-once
aim-qmul/sdx23-aimless
Source Separation training codebase for the Sound Demixing Challenge 2023.
crlandsc/Model-based-Bayesian-DoA-Analysis-for-Sound-Sources-Using-a-Spherical-Microphone-Array
A machine learning algorithm that estimates the directions of arrival and relative levels of an arbitrary number of sound sources using recorded data from a 16-channel spherical microphone array.