Package: dsrt
Neural DSRT: Neural dialogue systems for humansNewborn from the University of Maryland, Neural DSRT (pronounceddessert) is a high-level neural dialogue systems API, written inPythonand running on top of familiar deep-learning (DL) and machine-learning (ML) libraries likeKeras,TensorFlow, andscikit-learn. It focuses on allowing for the easy construction, training, and testing ofneural dialogue models.Its key purpose isto enable rapid development and experimentationin a burgeoning field otherwise bereft of high-level libraries with busy researchers in mind.What is it for?Neural DSRTis all about building end-to-end dialogue systems using state-of-the-art neural dialogue models. It is a new project (born at the University of Maryland in the waining days and weeks of March, 2018), and it still has a lot of growing to do.In order to help that growth along, we adopt a few guiding principles liberally fromKeras:User-friendliness.Ease-of-use should be front and center, the library should expose consistent & simple APIs, and should minimize the amount of work involved in getting common use-cases up and running. The focus should be on enabling rapid, hassle-free experimentation with neural dialog models.Modularity.Dialogue experiments, and their constituent components -- dataset wrappers, data preprocessors, neural dialogue models, conversation objects -- should alike be implemented as fully-configurable modules that can be plugged together with as few restrictions as possible. Experiments, and their components, should be richly configurable -- but components should fall back on sensible defaults, so that configuration should never be necessaryExtensibility.New modules should be simple to add (as new classes and functions), and existing modules and scripts should provide ample andliberally documentedexamples.How do I use it? 90 seconds to Neural DSRTThis quickstart guide has yet to be written -- but it should be coming soon.How can I install it?Before attempting to install Neural DSRT, you'll need to install Keras (which it's built on):Keras installation instructionsIn installing Keras, you'll of course need to install a neural-network backend. We recommend TensorFlow:TensorFlow installation instructions.Once you've done this, you're ready to install DSRT. Currently, the only way to do this is from the GitHub source. Thankfully, this is pretty easy, so long as you havepipinstalled on your machine (did we mention you'll need Python? you'll need Python -- we recommend the latest version of Python 3).Just in case, instructions for installingpipmay be found here:pip installation instructionsAssuming you've followed up until this point, proceed toclone DSRTusinggit:gitclonehttps://github.com/sbarham/dsrt.gitNow,cdto the Neural DSRT folder and install usingpip:cddsrt
sudopipinstall.It's as easy as that. Now you're ready to use Neural DSRT!How can I help?As we mentioned above, DSRT is very young -- in fact, it's only a few weeks old at the moment. If you're a developer (and especially if you're confident with deep learning, machine learning, or neural dialogue systems) and you'd like to help, please contact the original authors directly atsbarham@cs.umd.edu. We'd love to collaborate with you.