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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Solos: A Dataset for Audio-Visual Music Analysis · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2006.07931/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2006.07931/feed.xml" rel="self" type="application/rss+xml" /><item><title>Solos: A Dataset for Audio-Visual Music Analysis — HN submission</title><link>https://news.ycombinator.com/item?id=30467328</link><guid isPermaLink="false">urn:hackerpapers:submission:2006.07931:30467328</guid><pubDate>Fri, 25 Feb 2022 13:59:59 GMT</pubDate><description>&lt;p&gt;Show HN: Cloning a musical instrument from 16 seconds of audio&lt;/p&gt;&lt;p&gt;In 2020, Magenta released DDSP [1], a machine learning algorithm / python library which made it possible to generate good sounding instrument synthesizers from about 6-10 minutes of data. While working with DDSP for a project, we realised how it was actually quite hard to find 6-10 minute of clean recordings of monophonic instruments. In this project, we have combined the DDSP architecture with a domain adaptation technique from speech synthesis [2]. This domain adaptation technique works by pre-training our model on many different recordings from the Solos dataset [3] first and then…&lt;/p&gt;&lt;p&gt;185 points; 72 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2006.07931/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>eess.AS</category></item></channel></rss>
