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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2106.07447/</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/2106.07447/feed.xml" rel="self" type="application/rss+xml" /><item><title>HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units — mentioned by codekansas</title><link>https://news.ycombinator.com/item?id=38299711</link><guid isPermaLink="false">urn:hackerpapers:mention:2106.07447:38299711</guid><pubDate>Fri, 17 Nov 2023 04:49:02 GMT</pubDate><description>&lt;p&gt;It&amp;#x27;s really interesting for me to see AI voice cloning taking off. A few years ago I worked on a paper called HuBERT (https://arxiv.org/abs/2106.07447) which has since really taken off for doing this kind of stuff (it&amp;#x27;s the speech representation that SoViTs uses, for example). At the time the main research focus was low-resource ASR; it was sort of a fluke that it works so well for voice conversion. It makes me feel confident that open-source ML will drive more value over the next five years than closed-source ML, despite all the hype around big tech, simply because random people building…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2106.07447/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
