Just trying to get Python up and running has been a big mess, but I think I finally have gotten the hang of it. I also found another paper explaining how NNs are used for speech recognition. I really should organize these papers into one post that I can edit for later really.
From what I can tell from reading some of the articles I've previously linked, I should try to build towards an RNN set up at some point, though undoubtedly not this week. I think I'll go through these tutorials this weekend and see how many I can get running just one their own merit and databases before worrying about gathering my own data.
Looks like I'll mainly be focusing on TensorFlow and how it works. Time to get the basics, I guess.
From what I can tell from reading some of the articles I've previously linked, I should try to build towards an RNN set up at some point, though undoubtedly not this week. I think I'll go through these tutorials this weekend and see how many I can get running just one their own merit and databases before worrying about gathering my own data.
Looks like I'll mainly be focusing on TensorFlow and how it works. Time to get the basics, I guess.
- Very basic TensorFlow NN example, to get used to the database and Python
- Another basic TensorFlow tutorial.
- TensorFlow's own speech recognition tutorial
This paper isn't a tutorial, but features a lot of the equations that goes behind the NN. Might be handy for reference even if Python/TensorFlow is handling all of it anyway.
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