@inbook{b0c617cac24341a3942d42d97adf69cf,
title = "INVERSYNTH II: SOUND MATCHING VIA SELF-SUPERVISED SYNTHESIZER-PROXY AND INFERENCE-TIME FINETUNING",
abstract = "Synthesizers are widely used electronic musical instruments. Given an input sound, inferring the underlying synthesizer{\textquoteright}s parameters to reproduce it is a difficult task known as sound-matching. In this work, we tackle the problem of automatic sound matching, which is otherwise performed manually by professional audio experts. The novelty of our work stems from the introduction of a novel differentiable synthesizer-proxy that enables gradient-based optimization by comparing the input and reproduced audio signals. Additionally, we introduce a novel self-supervised finetuning mechanism that further refines the prediction at inference time. Both contributions lead to state-of-the-art results, outperforming previous methods across various metrics. Our code is available at: https://github.com/inversynth/ InverSynth2.",
author = "Oren Barkan and Shlomi Shvartzman and Noy Uzrad and Moshe Laufer and Almog Elharar and Noam Koenigstein",
note = "Publisher Copyright: {\textcopyright} Barkan et al.; 24th International Society for Music Information Retrieval Conference, ISMIR 2023 ; Conference date: 05-11-2023 Through 09-11-2023",
year = "2023",
language = "אנגלית",
series = "24th International Society for Music Information Retrieval Conference, ISMIR 2023 - Proceedings",
publisher = "International Society for Music Information Retrieval",
pages = "642--648",
editor = "Augusto Sarti and Fabio Antonacci and Mark Sandler and Paolo Bestagini and Simon Dixon and Beici Liang and Gael Richard and Johan Pauwels",
booktitle = "24th International Society for Music Information Retrieval Conference, ISMIR 2023 - Proceedings",
}