From 0aeeca5dbe4a2d40ff6c4aadbd9d366b1e38acd4 Mon Sep 17 00:00:00 2001
From: lamipaul <paulobest25@gmail.com>
Date: Wed, 24 May 2023 15:06:51 +0200
Subject: [PATCH] readme

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 README.md | 9 ++-------
 1 file changed, 2 insertions(+), 7 deletions(-)

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 # Repertoire Embedder
 
 ## Description
-Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
-
-## Badges
-On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
-
-## Visuals
-Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
+This repository gathers python scripts to use auto-encoder neural networks on vocalisation spectrograms, allowing to cluster them by frequency-contour similarity.
+It was developped to assist bioacousticians in their repertoire discovery procedures, making deep self-supervised learning accessible to non-experts of the field.
 
 For a detailled description of the scientific motivation and experiments corresponding to this repository, please see
 Best, P., Marxer, R., Paris, S., & Glotin, H. (2023). Deep audio embeddings for vocalisation clustering. bioRxiv, 2023-03.
-- 
GitLab