Ensemble of best vocal models. Algorithm gives the highest possible quality for vocal and instrumental stems. The latest ensemble consists of BS Roformer, MelBand Roformer and SCNet XL IHF vocal models.
Vokal Oylik foydalanish: 6 696, Oylik reyting: 4.3462 (26 ovozlari)This ensemble is based on algorithm which took 2nd place at Music Demixing Track of Sound Demixing Challenge 2023. The main changes comparing to contest version is much better individual stem models.
Vokal Barabanlar Bass Oylik foydalanish: 1 666, Oylik reyting: 2.7500 (4 ovozlari)It's Ensemble (vocals, instrum, bass, drums, other) + more models included like guitars, piano, wind, strings, back/lead vocals and drumsep.
Tavsiya etilgan Vokal Barabanlar Bass Pianino Gitara Oylik foydalanish: 3 619, Oylik reyting: 3.9167 (12 ovozlari)BS Roformer SW model, which generates 6 stems at once with superior quality.
Tavsiya etilgan Vokal Barabanlar Bass Pianino Gitara Oylik foydalanish: 93 307, Oylik reyting: 4.5577 (563 ovozlari)BS Roformer model. Excellent quality for vocals/instrumental separation.
Tavsiya etilgan Vokal Oylik foydalanish: 83 403, Oylik reyting: 4.6468 (201 ovozlari)Algorithm for separating tracks into vocal and instrumental parts based on the MelBand Roformer neural network
Vokal Oylik foydalanish: 36 067, Oylik reyting: 4.6863 (102 ovozlari)Set of MDX23C models which is based on code released by kuielab for Sound Demixing Challenge 2023. Very good for vocals/instrumental separation.
Vokal Oylik foydalanish: 6 832, Oylik reyting: 4.1111 (18 ovozlari)Algorithm for separating tracks into vocal and instrumental parts based on the SCNet neural network
Vokal Oylik foydalanish: 4 440, Oylik reyting: 2.7143 (7 ovozlari)Algorithm Demucs4 HT. It's fast and gives relatively good quality for bass/drums/other stems.
Vokal Barabanlar Bass Oylik foydalanish: 14 922, Oylik reyting: 4.6667 (51 ovozlari)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.
Vokal Oylik foydalanish: 2 133, Oylik reyting: 4.0000 (3 ovozlari)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.
Vokal Oylik foydalanish: 11 274, Oylik reyting: 4.2500 (8 ovozlari)Demucs4 Vocals 2023 model - it's Demucs4 HT model fine-tuned on big vocals dataset.
Vokal Oylik foydalanish: 1 870, Oylik reyting: 5.0000 (2 ovozlari)Algorithm for extracting only lead vocals and everything else based on the MelBand Roformer model.
Vokal Oylik foydalanish: 32 103, Oylik reyting: 4.7588 (170 ovozlari)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.
Vokal Oylik foydalanish: 13 062, Oylik reyting: 4.0556 (18 ovozlari)MVSep Piano model is based on MDX23C, MelRoformer and SCNet Large architectures. It produces high quality separation for piano and other stems.
Pianino Oylik foydalanish: 5 857, Oylik reyting: 4.6154 (39 ovozlari)The MVSep Guitar model produces high-quality separation of music into a guitar part (including acoustic and electronic) and everything else.
Gitara Oylik foydalanish: 9 851, Oylik reyting: 3.8750 (24 ovozlari)The MVSep Bass model produces high-quality separation of music into a bass part and everything else.
Bass Oylik foydalanish: 7 706, Oylik reyting: 4.4286 (7 ovozlari)The MVSep Drums model produces high-quality separation of music into a drums part and everything else.
Barabanlar Oylik foydalanish: 13 323, Oylik reyting: 4.5556 (36 ovozlari)The MVSep Strings model is a model based on the MDX23C architecture for separating music into bowed string instruments and everything else.
Oylik foydalanish: 4 500, Oylik reyting: 3.7619 (21 ovozlari)The MVSep Wind model produces high-quality separation of music into a wind part and everything else.
Oylik foydalanish: 4 439, Oylik reyting: 4.0000 (25 ovozlari)The MVSep Organ model produces high-quality separation of music into an organ part and everything else.
Oylik foydalanish: 1 687, Oylik reyting: 4.3333 (3 ovozlari)No data found
Oylik foydalanish: 1 729, Oylik reyting: 3.7857 (14 ovozlari)No data found
Oylik foydalanish: 2 158, Oylik reyting: 4.6000 (5 ovozlari)The algorithm restores the quality of audio. For example MP3 files compressed to 128 kbps or lower and other types.
Super rezolyutsiya Oylik foydalanish: 9 189, Oylik reyting: 3.8750 (8 ovozlari)Set of different models to remove reverberation effect from music.
Oylik foydalanish: 10 273, Oylik reyting: 3.5714 (7 ovozlari)An unique model for removing crowd sounds from music recordings (applause, clapping, whistling, noise, laugh etc.).
Oylik foydalanish: 7 538, Oylik reyting: 4.0000 (19 ovozlari)No data found
Oylik foydalanish: 3 088, Oylik reyting: 4.0000 (3 ovozlari)BandIt Plus model for separating tracks into speech, music and effects.
Oylik foydalanish: 2 777, Oylik reyting: 2.0000 (1 ovozlari)Bandit v2 is a model for cinematic audio source separation in 3 stems: speech, music, effects/sfx. It was trained on DnR v3 dataset.
Oylik foydalanish: 1 340, Oylik reyting: 0 (0 ovozlari)MVSep DnR v3 is a cinematic model for splitting tracks into 3 stems: music, sfx and speech.
Oylik foydalanish: 47 671, Oylik reyting: 4.0000 (3 ovozlari)The DrumSep model divides the drum track into several types: 'kick', 'snare', 'toms', 'cymbals' (it includes 'hh', 'ride', 'crash').
Barabanlar Oylik foydalanish: 8 374, Oylik reyting: 4.7115 (52 ovozlari)No data found
Oylik foydalanish: 8 093, Oylik reyting: 4.7105 (114 ovozlari)Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation.
Oylik foydalanish: 1 121, Oylik reyting: 3.3333 (9 ovozlari)Parakeet by NVIDIA is a state-of-the-art automatic speech recognition (ASR) model designed for accurate and efficient conversion of spoken English language into text.
Oylik foydalanish: 208, Oylik reyting: 2.5000 (2 ovozlari)Medley Vox is an algorithm for separating multiple singers within a single music track and evaluation dataset for this task.
Vokal Oylik foydalanish: 5 251, Oylik reyting: 2.1111 (9 ovozlari)MVSep Multichannel BS - uses the best vocal model to extract sound from multi-channel audio (5.1, 7.1, etc.).
Vokal Oylik foydalanish: 1 947, Oylik reyting: 5.0000 (2 ovozlari)A model for separating male and female voices within a single vocal track. The track should contain only voices, no music.
Vokal Oylik foydalanish: 4 792, Oylik reyting: 3.4118 (17 ovozlari)No data found
Vokal Barabanlar Bass Oylik foydalanish: 120, Oylik reyting: 0 (0 ovozlari)Algorithm Demucs3 (A and B versions)
Vokal Barabanlar Bass Oylik foydalanish: 236, Oylik reyting: 0 (0 ovozlari)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.
Vokal Oylik foydalanish: 138, Oylik reyting: 0 (0 ovozlari)No data found
Vokal Oylik foydalanish: 170, Oylik reyting: 1.0000 (1 ovozlari)No data found
Oylik foydalanish: 2 202, Oylik reyting: 0 (0 ovozlari)No data found
Vokal Oylik foydalanish: 106, Oylik reyting: 0 (0 ovozlari)No data found
Vokal Barabanlar Bass Oylik foydalanish: 86, Oylik reyting: 0 (0 ovozlari)No data found
Vokal Barabanlar Bass Oylik foydalanish: 36, Oylik reyting: 0 (0 ovozlari)No data found
Vokal Barabanlar Bass Oylik foydalanish: 37, Oylik reyting: 0 (0 ovozlari)No data found
Oylik foydalanish: 171, Oylik reyting: 0 (0 ovozlari)No data found
Oylik foydalanish: 142, Oylik reyting: 0 (0 ovozlari)No data found
Oylik foydalanish: 98, Oylik reyting: 0 (0 ovozlari)The LarsNet model divides the drums stem into 5 types: 'kick', 'snare', 'cymbals', 'toms', 'hihat'.
Barabanlar Oylik foydalanish: 183, Oylik reyting: 0 (0 ovozlari)Generating audio based on a given text prompt
Oylik foydalanish: 680, Oylik reyting: 3.7143 (7 ovozlari)MVSep MultiSpeaker (MDX23C) - this model tries to isolate the most loud voice from all other voices.
Oylik foydalanish: 526, Oylik reyting: 1.0000 (1 ovozlari)The algorithm adds "whispering" effect to vocals.
Oylik foydalanish: 410, Oylik reyting: 0 (0 ovozlari)No data found
Oylik foydalanish: 3 100, Oylik reyting: 5.0000 (2 ovozlari)Algorithm AudioSR: Versatile Audio Super-resolution at Scale. Algorithm restores high frequencies.
Super rezolyutsiya Oylik foydalanish: 3 541, Oylik reyting: 3.6667 (3 ovozlari)FlashSR - audio super resolution algorithm for restoring high frequencies
Super rezolyutsiya Oylik foydalanish: 3 376, Oylik reyting: 3.5000 (8 ovozlari) Ma’lumot topilmadi Eski tanlovga qaytingIshlab chiqilmagan fayllar queue: 317. Bugungi kunda GPU: 11
turbo@mvsep.com
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