[MODEL] RAVE.Cümbüş

[moiseshorta]

A brief description of what your model does

RAVE model trained by 𝔥𝔢𝔵𝔬𝔯𝔠𝔦𝔰𝔪𝔬𝔰 on recordings of Cümbüş sounds, a turkish instrument from early c.XX Used for timbre transfer.

Checklist

• [ x ] I have checked the model works properly loaded locally in the Neutone plugin on my machine. <Windows 10, Neutone Standalone app>
• [ ] I have uploaded the .nm model file at a publicly available location: https://www.dropbox.com/scl/fo/keh31579c39wh3s822507/h?rlkey=5qogdp26emkqlugz0nve5n8wf&dl=0

Extra information

The model was trained on custom recordings done by hexorcismos. No copyrighted audio data was used.

Metadata

The model export function should dump a json file. Please paste the contents here for review and discussions.

{
    "model_name": "RAVE.C\u00fcmb\u00fc\u015f",
    "model_authors": [
        "𝔥𝔢𝔵𝔬𝔯𝔠𝔦𝔰𝔪𝔬𝔰"
    ],
    "model_version": "1.0.0",
    "model_short_description": "stereo RAVE model trained by 𝔥𝔢𝔵𝔬𝔯𝔠𝔦𝔰𝔪𝔬𝔰 on recordings of C\u00fcmb\u00fc\u015f sounds, a turkish instrument from early c.XX",
    "model_long_description": "RAVE timbre transfer model trained on C\u00fcmb\u00fc\u015f (early XX century Turkish instrument) sounds. Useful for realistic strings and microtonal melodic sounds.",
    "technical_description": "RAVE model proposed by Caillon, Antoine et al.",
    "technical_links": {
        "Paper": "https://arxiv.org/abs/2111.05011",
        "Code": "https://github.com/acids-ircam/RAVE"
    },
    "tags": [
        "timbre transfer",
        "RAVE"
    ],
    "citation": "Caillon, A., & Esling, P. (2021). RAVE: A variational autoencoder for fast and high-quality neural audio synthesis. arXiv preprint arXiv:2111.05011.",
    "is_experimental": false,
    "neutone_parameters": {
        "p1": {
            "name": "Chaos",
            "description": "Magnitude of latent noise",
            "type": "knob",
            "used": "True",
            "default_value": "0.0"
        },
        "p2": {
            "name": "Z edit index",
            "description": "Index of latent dimension to edit",
            "type": "knob",
            "used": "True",
            "default_value": "0.0"
        },
        "p3": {
            "name": "Z scale",
            "description": "Scale of latent variable",
            "type": "knob",
            "used": "True",
            "default_value": "0.5"
        },
        "p4": {
            "name": "Z offset",
            "description": "Offset of latent variable",
            "type": "knob",
            "used": "True",
            "default_value": "0.5"
        }
    },
    "wet_default_value": 1.0,
    "dry_default_value": 0.0,
    "input_gain_default_value": 0.5,
    "output_gain_default_value": 0.5,
    "is_input_mono": true,
    "is_output_mono": true,
    "model_type": "mono-mono",
    "native_sample_rates": [
        48000
    ],
    "native_buffer_sizes": [
        2048
    ],
    "look_behind_samples": 0,
    "sdk_version": "1.4.2",
    "pytorch_version": "1.13.1+cu117",
    "date_created": 1706276356.2125454
}

[bogdanteleaga]

Thank you Moises, it's now part of the plugin!