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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Adapting Speech Separation to Real-World Meetings Using Mixture Invariant Training · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2110.10739/</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/2110.10739/feed.xml" rel="self" type="application/rss+xml" /><item><title>Adapting Speech Separation to Real-World Meetings Using Mixture Invariant Training — mentioned by kajecounterhack</title><link>https://news.ycombinator.com/item?id=35185071</link><guid isPermaLink="false">urn:hackerpapers:mention:2110.10739:35185071</guid><pubDate>Thu, 16 Mar 2023 17:19:51 GMT</pubDate><description>&lt;p&gt;https://arxiv.org/abs/2110.10739 I haven&amp;#x27;t seen it provided as a commercial service or free model yet, but there is open source code for Mixit that lets you train using the open source / canned FUSS dataset.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2110.10739/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.SD</category></item></channel></rss>
