This repository contains audio samples and supplementary materials accompanying publications by the "Speaker, Voice and Language" team at Google.
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Updated
Sep 21, 2024 - Python
This repository contains audio samples and supplementary materials accompanying publications by the "Speaker, Voice and Language" team at Google.
free website for client-side music demixing with Demucs + WebAssembly
Self-hostable web app for isolating the vocal, accompaniment, bass, and drums of any song. Supports Spleeter, D3Net, Demucs, Tasnet, X-UMX. Built with React and Django.
Self-hostable web app for isolating the vocal, accompaniment, bass, and drums of any song. Supports Spleeter, D3Net, Demucs, Tasnet, X-UMX. Built with React and Django.
EEG signal processing using various source separation methods such as GEVD, DSS, PCA, and ICA.
Biomedical Signal & Image Processing Lab Projects.
Repository for the ISMIR 2024 Paper "From Real to Cloned Singer Identification".
Implements ML audio separation algorithm on audio from YouTube or Spotify resulting in "stems" for download (e.g. vocals, drums, bass) in MP3, WAV or FLAC.
PodcastMix A dataset for separating music and speech in podcasts.
PodcastMix A dataset for separating music and speech in podcasts. Code of my Master Thesis in the Sound and Music Computing Master Program Universitat Pompeu Fabra
hyperspectral galaxy modeling and deblending
Isolate vocals, drums, bass, and other instrumental stems from any song
Source Separation of Multi-source Raw Music using a Residual Quantized variational Autoencoder
Collection of EM algorithms for blind source separation of audio signals
Tools of soundscape information retrieval, this repository is a developing project. Please go to https://github.com/meil-brcas-org/soundscape_IR for full releases.
Banquet: A Stem-Agnostic Single-Decoder System for Music Source Separation Beyond Four Stems
Unofficial PyTorch implementation of Google AI's VoiceFilter system
An open toolbox of soundscape information retrieval
Code to partially reproduce results in "Martian time-series unraveled: A multi-scale nested approach with factorial variational autoencoders"
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