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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2008.04259/</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/2008.04259/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech — mentioned by lawl</title><link>https://news.ycombinator.com/item?id=25646039</link><guid isPermaLink="false">urn:hackerpapers:mention:2008.04259:25646039</guid><pubDate>Tue, 05 Jan 2021 14:48:45 GMT</pubDate><description>&lt;p&gt;It&amp;#x27;s worth noting that RNNoise uses way less resources than RTX Voice and doesn&amp;#x27;t require a GPU. There&amp;#x27;s a new paper by Jean-Marc Valin (RNNoise author) about a new and improved version PercepNet[0] that&amp;#x27;s also very light on resource usage, but it&amp;#x27;s currently lacking an open source implementation. I found someone working on that here[1]. So if anyone here has the time and ML chops to open source a PercepNet implementation, that would bring open source noise suppression quite a bit forward. [0] https://arxiv.org/pdf/2008.04259.pdf [1] https://github.com/jzi040941/PercepNet&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2008.04259/"&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>
