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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>High Resolution Guitar Transcription via Domain Adaptation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2402.15258/</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/2402.15258/feed.xml" rel="self" type="application/rss+xml" /><item><title>High Resolution Guitar Transcription via Domain Adaptation — mentioned by rrherr</title><link>https://news.ycombinator.com/item?id=41257776</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.15258:41257776</guid><pubDate>Thu, 15 Aug 2024 16:26:37 GMT</pubDate><description>&lt;p&gt;Here&amp;#x27;s the most impressive results I&amp;#x27;ve seen for automated guitar transcription: High-resolution guitar transcription via domain adaptation Demo Videos: https://xavriley.github.io/HighResolutionGuitarTranscription... Paper: https://arxiv.org/abs/2402.15258 &amp;gt; We propose the use of a high-resolution piano transcription model to train a new guitar transcription model. The resulting model obtains state-of-the-art transcription results on GuitarSet in a zero-shot context, improving on previously published methods.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.15258/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>eess.AS</category></item></channel></rss>
