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Deep Speech: Scaling up end-to-end speech recognition (arxiv.org)
63 points by lelf on Feb 14, 2015 | hide | past | favorite | 8 comments



I'll kick things off by linking to the comments from the last time this was posted: https://news.ycombinator.com/item?id=8769067.


>16.0% error on the full test set

Does anyone know, what was the error rate with previous approaches these days?


Look at Table 3 in the paper. Also, 16.5% error ;)


Oh thanks, and, wow!


Github repo that I can compile and try?


Providing the source would be a step to improve transparency and reproducibility (the text does not provide sufficient detail for even someone working in the field to reproduce what they did so that he would arrive at the same results); however, the more crucial thing is the data. Switchboard, Fisher, and WSJ are available (provided you have a few grand to spend), but they say they collected 5000 h of read speech from 9600 speakers.. That's a huge effort!


An alternative source of data that you can contribute to:

http://www.voxforge.org/


woo!




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