Algorithm Demucs4 HT. It's fast and gives relatively good quality for bass/drums/other stems.

BS Roformer model. Excellent quality for vocals/instrumental separation.

Algorithm for separating tracks into vocal and instrumental parts based on the MelBand Roformer neural network

Set of MDX23C models which is based on code released by kuielab for Sound Demixing Challenge 2023. Very good for vocals/instrumental separation.

Algorithm for separating tracks into vocal and instrumental parts based on the SCNet neural network

MDX B models are based on kuielab code from Music Demixing Challenge 2021. Models were retrained by UVR team on big dataset. For long time models were best for vocals/instrumental separation.

A set of models from the Ultimate Vocal Remover program, which are based on the old VR architecture. Most of the models are vocal, but there are also special models for karaoke, piano, removing reverberation effects, etc.

Demucs4 Vocals 2023 model - it's Demucs4 HT model fine-tuned on big vocals dataset.

The MDX-B Karaoke model was prepared as part of the Ultimate Vocal Remover project. The model produces high-quality lead vocal extraction from a music track.

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MVSep Piano model is based on MDX23C, MelRoformer and SCNet Large architectures. It produces high quality separation for piano and other stems.

The MVSep Guitar model produces high-quality separation of music into a guitar part (including acoustic and electronic) and everything else.

The MVSep Bass model produces high-quality separation of music into a bass part and everything else.

The MVSep Drums model produces high-quality separation of music into a drums part and everything else.

The MVSep Strings model is a model based on the MDX23C architecture for separating music into bowed string instruments and everything else.

The MVSep Wind model produces high-quality separation of music into a wind part and everything else.

The MVSep Organ model produces high-quality separation of music into an organ part and everything else.

Experimental model VitLarge23 based on Vision Transformers. In terms of metrics, it is slightly inferior to the MDX23C, but may work better in some cases.

Set of different models to remove reverberation effect from music.

An unique model for removing crowd sounds from music recordings (applause, clapping, whistling, noise, laugh etc.).

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BandIt Plus model for separating tracks into speech, music and effects.

Bandit v2 is a model for cinematic audio source separation in 3 stems: speech, music, effects/sfx. It was trained on DnR v3 dataset.

MVSep DnR v3 is a cinematic model for splitting tracks into 3 stems: music, sfx and speech.

The DrumSep model divides the drums stem into 4 types: 'kick', 'snare', 'cymbals', 'toms'.

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Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation.

Medley Vox is an algorithm for separating multiple singers within a single music track and evaluation dataset for this task.

MVSep Multichannel BS - uses the best vocal model to extract sound from multi-channel audio (5.1, 7.1, etc.).

A model for separating male and female voices within a single vocal track. The track should contain only voices, no music.

Algorithm Demucs3 (A and B versions)

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The LarsNet model divides the drums stem into 5 types: 'kick', 'snare', 'cymbals', 'toms', 'hihat'.

MVSep MultiSpeaker (MDX23C) - this model tries to isolate the most loud voice from all other voices.

The algorithm restores the quality of audio. For example MP3 files compressed to 128 kbps or lower and other types.

The algorithm adds "whispering" effect to vocals.

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