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Calibrating Unsupervised Language Learning
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==========================================
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* Version of May 2021
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+ * Mothballed, late 2021
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- Ongoing project, continuing activity. See the
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+ Mothballed project, halted activity. This was a good idea, but it
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+ foundered on severeal practical and several theoretical issues.
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+ Cannot move foreward, until these are addressed. See below, "lessons
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+ learned". for a summary of these issues.
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+
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+ See also the
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[ language learning wiki] ( http://wiki.opencog.org/w/Language_learning )
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- for an alternate overview. See the diary at
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- ` learn-lang-diary/learn-lang-diary-part-two.lyx ` for a progress log.
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+ for an alternate overview. See
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+ [ Diary Part Two] ( learn-lang-diary/learn-lang-diary-part-two.pdf )
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+ for a log of the experimental efforts and results.
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Project Summary
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---------------
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adjustable parameters even "aligned" with the axes of human language
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complexity? How does one even judge this?
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+ * A serious, practical impediment is that there is no easy way to just
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+ "eyeball" the results. With English, one can just look at the stuff
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+ being generated, and its fairly clear when it's good and when its
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+ garbage. But with artificial langauges, it is impossible to glance at
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+ it and get any idea of what's going on. In order to track what's
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+ happpening, one would need to build a deep, complex and throuogh set
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+ of tools, carefully measuring everything at every step, to see if the
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+ process is working or has gone off the rails.
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+
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Additional details, results, questions and head-scartching can be found
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in the [ Language Learning Diary, Part
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Two] ( learn-lang-diary/learn-lang-diary-part-two.pdf ) .
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even dented the surface of grammar--corpus correspondence. Onward
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through the fog!
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-
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That's all for now!
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-------------------
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THE END.
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