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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Density Ratio Approach to Language Model Fusion in End-To-End Automatic Speech Recognition · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2002.11268/</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/2002.11268/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Density Ratio Approach to Language Model Fusion in End-To-End Automatic Speech Recognition — mentioned by albertzeyer</title><link>https://news.ycombinator.com/item?id=25905709</link><guid isPermaLink="false">urn:hackerpapers:mention:2002.11268:25905709</guid><pubDate>Mon, 25 Jan 2021 17:07:34 GMT</pubDate><description>&lt;p&gt;This is like the density ratio approach (https://arxiv.org/abs/2002.11268). The Hybrid Autoregressive Transducer also uses a similar idea (https://arxiv.org/abs/2003.07705). Do you really need the renormalization, i.e. the outer softmax?&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2002.11268/"&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>
