--- license: cc-by-nc-4.0 --- # RAVE Models This is a collection of [RAVE](https://github.com/acids-ircam/RAVE) models trained by the [Intelligent Instruments Lab](https://iil.is) for various projects. Most of these models are encoder-decoder only, no prior, and all use the `--causal` mode and are exported for streaming inference with [nn~](https://github.com/acids-ircam/nn_tilde), [NN.ar](https://github.com/elgiano/nn.ar) or [rave-supercollider](https://github.com/victor-shepardson/rave-supercollider). ## Musical Instruments ### guitar_iil_b2048_r48000_z16.ts Dataset: [IILGuitarTimbre](https://github.com/Intelligent-Instruments-Lab/IILGuitarTimbre), a timbre-oriented collection of plucking, strumming, striking scraping and more recorded dry from an electric guitar. Model: modified RAVE v1, 48kHz, block size 2048, 16 latent dimensions. ### sax_soprano_franziskaschroeder_b2048_r48000_z20.ts Dataset: Soprano sax improvisation by [Franziska Schroeder](https://improvisationai.wordpress.com/). Model: modified RAVE v1, 48kHz, block size 2048, 20 latent dimensions. ### organ_archive_b2048_r48000_z16.ts Dataset: various recordings of organ music sourced from archive.org. Small amounts of voice and other instruments were included, and vinyl record noises are prominent. Model: modified RAVE v1, 48kHz, block size 2048, 16 latent dimensions. ### organ_bach_b2048_sr48000_z16.ts Dataset: various recordings of J.S. Bach music for church organ. Model: modified RAVE v1, 48kHz, block size 2048, 16 latent dimensions. ## Voice ### voice_vocalset_b2048_r48000_z16.ts Dataset: [VocalSet](https://zenodo.org/record/1193957) singing voice dataset. Model: modified RAVE v1, 48kHz, block size 2048, 16 latent dimensions. ### voice_hifitts_b2048_r48000_z16.ts Dataset: [Hi-Fi TTS](http://arxiv.org/abs/2104.01497) audiobooks dataset. Model: modified RAVE v1, 48kHz, block size 2048, 16 latent dimensions. ### voice_jvs_b2048_r44100_z16.ts Dataset: [Hi-Fi TTS](http://arxiv.org/abs/2104.01497) speaker 9017 (John Van Stan). Model: RAVE v3, 44.1kHz, block size 2048, 16 latent dimensions. ### voice_vctk_b2048_r44100_z16.ts Dataset: [CSTR VCTK Corpus](https://datashare.ed.ac.uk/handle/10283/3443) multispeaker read speech dataset. Model: RAVE v3, 44.1kHz, block size 2048, 22 latent dimensions. ## *Pluma* Birds This model of bird sounds was curated by Giacomo Lepri for his instrument *[Pluma](http://www.giacomolepri.com/pluma)* ### birds_pluma_b2048_r48000_z12.ts Dataset: bird sounds. Model: modified RAVE v1, 48kHz, block size 2048, 12 latent dimensions. ## *Pond Brain* Marine Sounds These models of marine sounds were trained for [Jenna Sutela](https://jennasutela.com/)'s *Pond Brain* installations at [Copenhagen Contemporary](https://copenhagencontemporary.org/en/yet-it-moves-read-online/) and the [Helsinki Biennial](https://helsinkibiennaali.fi/en/artist/jenna-sutela/) Caution: these decoders sometimes produce a loud chirp on first initialization. ### water_pondbrain_b2048_r48000_z16.ts Dataset: water recordings from freesound.org.
list of freesound users inspectorj, inchadney, aesqe, vonfleisch, javetakami, atomediadesign, kolezan, zabuhailo, zaziesound, repdac3, al_sub, lgarrett, uzbazur, lydmakeren, frenkfurth, edo333, boredtoinsanity, owl, kaydinhamby, tliedes, ilmari_freesound, manoslindos, l3ardoc, alexbuk, s-light
Model: modified RAVE v1, 48kHz, block size 2048, 16 latent dimensions. ### humpbacks_pondbrain_b2048_r48000_z20.ts Dataset: humpback whale recordings from the [Watkins database](https://cis.whoi.edu/science/B/whalesounds/index.cfm), [MBARI](https://freesound.org/people/MBARI_MARS/), and BBC. Model: modified RAVE v1, 48kHz, block size 2048, 20 latent dimensions. ### marinemammals_pondbrain_b2048_r48000_z20.ts Dataset: various marine mammal sounds from [NOAA](https://www.fisheries.noaa.gov/national/science-data/sounds-ocean-mammals), the [Watkins database](https://cis.whoi.edu/science/B/whalesounds/index.cfm), freesound users `felixblume` and `geraldfiebig`, and sound effects databases. Model: modified RAVE v1, 48kHz, block size 2048, 20 latent dimensions.