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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2008.03687/</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/2008.03687/feed.xml" rel="self" type="application/rss+xml" /><item><title>LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition — mentioned by shenberg</title><link>https://news.ycombinator.com/item?id=35153617</link><guid isPermaLink="false">urn:hackerpapers:mention:2008.03687:35153617</guid><pubDate>Tue, 14 Mar 2023 15:58:13 GMT</pubDate><description>&lt;p&gt;It&amp;#x27;s referred to as distillation in the literature in separate sub-fields (e.g. LRspeech, a paper about low-resource speech-to-text &amp;amp; text-to-speech from Microsoft Research, 2020, uses datasets generated by a large model to train a small one and refers to this as knowledge distillation: https://arxiv.org/abs/2008.03687 )&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2008.03687/"&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>
