Julius [1] is a pretty good offline speech recognition engine. In my tests it seems to have about 95% accuracy in grammar-based models, and it supports continuous dictation. There is also a decent Python module which supports Python 2, and Python 3 with a few tweaks.
HOWEVER:
The only continuous dictation models available for Julius are Japanese, as it is a Japanese project. This is mainly an issue of training data. The VoxForge models are working towards releasing one for English once they get 140 hours of training data (last time I checked they were around 130); but even so the quality is likely to be far less than commercial speech recognition products, which generally have thousands of hours of training.
Julius is my preferred speech recognition engine. I've built an application[0] which enables users to control their Linux desktops with their voices, and uses Julius to do the heavy lifting.
After a quick look, it seems Julius doesn't use the new deep-learning stuff?
In terms of data,
http://www.openslr.org/12/
says it has 300 hours + of speech+text from librivox audiobooks. Using Librovox recordings seemed a great idea for making a freely available large dataset.
HOWEVER:
The only continuous dictation models available for Julius are Japanese, as it is a Japanese project. This is mainly an issue of training data. The VoxForge models are working towards releasing one for English once they get 140 hours of training data (last time I checked they were around 130); but even so the quality is likely to be far less than commercial speech recognition products, which generally have thousands of hours of training.
[1] http://julius.osdn.jp/en_index.php