Merge branch 'master' of github.com:ottokart/punctuator2

README.md

@@ -16,6 +16,8 @@ The model can be trained in two stages (second stage is optional):
 
 Remember that all the scores given below are on _unsegmented_ text and we did not use prosodic features, so, among other things, the model has to detect sentence boundaries in addition to the boundary type (?QUESTIONMARK, .PERIOD or !EXCLAMATIONMARK) based entirely on textual features. The scores are computed on the test set.
 
+Training speed with default settings, an optimal Theano installation and a modern GPU should be around 10000 words per second.
+
 ## English TED talks
 Training set size: 2.1M words. First stage only. More details can be found in [this paper](http://www.isca-speech.org/archive/Interspeech_2016/pdfs/1517.PDF).
 For comparison, our [previous model](https://github.com/ottokart/punctuator) got an overall F1-score of 50.8.