IronMeta version 2.1 has been released.
Version 2.1 contains some refactoring, miscellaneous bug fixes, as well as:
- Better error handling and reporting.
- Added
IronMeta.Matcher.CharMatcher.Input() and IronMeta.Matcher.CharMatcher.Trimmed() for more convenient string handling.
- Added min/max repeats syntax (e.g.
'a' {1, 3}).
IronMeta is an implementation of Alessandro Warth’s OMeta metaprogramming system in C#. It provides a packrat parser generator that generates parsers for Parsing Expression Grammars that operate on arbitrary streams of objects.
Version 1.2.0 of the Neurocognitive Linguistics Laboratory is now
available at http://neurolab.bitbucket.org
Highlights of this release include:
- The primary new feature in this release is the “Grid Item”. This
type of network item allows you to create a small “template” network,
along with symmetrical connections to its top, bottom, and sides.
Then the program generates a huge grid consisting of repeated
instances of your template, with each instance connected to its
neighbors via the edge connections. The overall topology of the grid
is cylindrical; the sides wrap around, but the very top and bottom
rows can connect to other network items.
- A simple way to input and output text to a grid is provided via the
“Text IO Item”. This is a network item that has 256 connections in
and out; if you connect it to a grid item that has 256 horizontal
repeats it will feed your text (in UTF-8 format) byte by byte as
activation to the different grid repeats, and output results from the
grid if one of its outputs is activated.
- There are several UI improvements in version 1.2.0, including a
palette of network items from which you can drag items into the
network editing area.
- The underlying network automaton is vastly sped up in version 1.2.0
by using seqlocks instead of mutexes to manage memory consistency.
You can reply with questions or discussion about NeuroLab on this
mailing list. Please report bugs via the issue tracker:
https://bitbucket.org/kulibali/neurocogling/issues/new
Neurocognitive Linguistics is an approach to linguistics developed by
Sydney Lamb which uses relational
networks to model what the brain actually does when it handles
language. You can read more about it at the LangBrain site and Glottopedia.
Neurocognitive Linguistics Lab (“NeuroLab” for short) is a program for
Windows, Mac OS X and Linux that allows you to experiment with
relational networks using a convenient GUI, and record the results of
your experiments in tabular form.
Neurocognitive Linguistics Lab is Copyright (C) 2010,2011 Gordon
Tisher, and available under the terms of the BSD License.
So I’m re-reading the moderately popular The Name of the Wind now that its sequel The Wise Man’s Fear is out. My opinion is pretty much the same as the last time I read it: it’s entertaining, but the main character is a wee bit too ubercompetent.
I’m just jealous because he supposedly learned a language in a day and a half.
The question most often asked when people find out you’ve dabbled in linguistics is “How many languages do you speak?” Well, I’ve studied quite a few languages, but there are only a couple I’d be comfortable jumping in blind right now.
James McGrath has started a meme that widens the net a bit:
List every language that [you] have made some sort of concerted effort to learn, even if [you] didn’t get beyond the first lesson or so, or even if [you] are still learning it. No need to specify the degree of fluency in the blog post – if readers are curious how much Swahili you know, they can ask.
Here’s my list, in no order whatsoever:
Almost ended up bouncing off the hood of a car this morning. Said car had suddenly felt the need to cross 2 lanes of traffic and turn right in front of me. Luckily I have been practicing my quick turns.
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