Maximum Likelihood-based Character-Level Language Model (LM) Training System

A Maximum Likelihood-based Character-Level Language Model (LM) Training System is a Character-Level Language Modeling System that is a Maximum Likelihood-based LM system and that implements a Maximum Likelihood-based Character-Level Language Modeling Algorithm.

• Example(s):
  • a Python-based Maximum Likelihood-based Character-Level LM System (such as in Goldberg, 2015),
  • a Character-Level MLE Language Model-based WikiFixer,
  • an Unsmoothed Maximum-Likelihood Character-level Language Modeling System.
  • …
• Counter-Example(s):
  • A Word-Level Maximum Likelihood-based Language Modeling System.
  • A Neural-based Character-Level Language Modeling System.
• See: Unsmoothed Maximum-Likelihood Character-level Language Modeling Algorithm, Language Model, Maximum Likelihood.

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References

2015

• (Goldberg, 2015) ⇒ Yoav Goldberg. (2015). “The Unreasonable Effectiveness of Character-level Language Models (and Why RNNs Are Still Cool).” In: Blog Post.

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