Tokenization, frequency profiles and N-gram models in Python 3

This is a brief description about how to use the Python 3 scripts to generate N-gram models for word tokens and characters from text. I expect you to have a Python 3 interpreter installed on your system.

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Updated Python code and tools

The Charty parser code is updated to Python 3.x (implementing an Earley parser for context-free grammars), and a compact module, TextStat.py, with some useful functions for N-gram models, frequency profiles, vector space models, statistical analyses, information theoretic measures (entropy, mutual information, etc.). If you have comments, or you find some bug or error, let me know.
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