https://hackerpaper.kaipfister.de/p/1904.08779/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=21711254urn:hackerpapers:mention:1904.08779:21711254Thu, 05 Dec 2019 10:21:06 GMT<p>LibriSpeech test clean is without background noise, with a good microphone, and most likely biased to native speakers (it is 50/50 male/female at least). In summary, it&#x27;s not what an ASR engine will encounter. However, the dataset is used as a common method to benchmark ASR engines and thus that number is valuable. The SpecAugment paper by Google for example claims a 2.5% word error rate [1] on that corpus (using only LibriSpeech for training data). [1]: https://arxiv.org/pdf/1904.08779.pdf</p><p><a href="https://hackerpaper.kaipfister.de/p/1904.08779/">Paper and discussion history</a>. A mention is not an endorsement.</p>eess.AS