|
|
The code and data for the DISCERN story processing model and the SPEC sentence understanding model are now available from our ftp/WWW site. These software packages are not general-purpose neural network simulators, but cleaned-up code for specific connectionist NLP models. I am making them available because they contain implementations of general ideas for debugging complex neural network systems through X11 graphics interface, for analyzing the performance of the models, and running experiments with such models. I've tried to pay special attention on making the code portable across platforms (it is based on ANSI/K&R C and X11R5 with Athena Widgets), and making the software easy to modify and built on. I hope the software can serve as a starting point for other experiments in connectionist NLP --- where building simulation programs from scratch turned out to be a heck of a lot of work :-) To get a quick feel of what these programs are like (without having to port them), take a look at the DISCERN demo under WWW at http://www.cs.utexas.edu/~nn/discern.html or by "telnet cascais.cs.utexas.edu 30000". The demo runs on remotely on cascais.cs.utexas.edu, with a display on your X11 screen. -- Risto Miikkulainen Here's a short discription of the software: DISCERN ------- DISCERN is a large modular system for processing script-based stories. It includes component models for lexical processing, episodic memory, and parsing, paraphrasing and question answering. The main reference is Miikkulainen (1993): "Subsymbolic Natural Language Processing: An integrated Model of Scripts, Lexicon and Memory", Cambridge, MA: MIT Press (a precis of this book was recently posted in the connectionists list). The DISCERN software consists of four components: (1) the full DISCERN performance system (i.e. the "demo" program), (2) training the simple recurrent and feedforward backprop networks for parsing, generating, and question answering, (3) training the lexicon feature maps and Hebbian associative connections, and (4) training the hierarchical feature maps of the episodic memory. All these are available by anonymous ftp from cs.utexas.edu:pub/neural-nets/discern, or in WWW, from http://www.cs.utexas.edu/~nn. SPEC ---- SPEC is a model of parsing sentences with embedded relative clauses. It consists of the parser (a simple recurrent network), the stack (a RAAM network) and the segmenter (feedforward) networks that are trained together and generalize to novel sentence structures. For a quick description of the model, see our paper in AAAI-94, or a longer tech. report version from our ftp/www site. The SPEC software and papers are available by anonymous ftp from cs.utexas.edu:pub/neural-nets/spec or in WWW, from http://www.cs.utexas.edu/~nn.
|
Maintained by Bob Duin, e-mail:
duin@ph.tn.tudelft.nl
Last update: February 17, 2004 |
Return to the home page
|