Spell Checking Algorithm
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A Spell Checking Algorithm is an NLP algorithm that can be implemented by a spell checking system to solve a spell checking task.
- Context:
- It can range from being a Heuristic Spell Checking Algorithm to being a Data-Driven Spell Checking Algorithm (such as a supervised spell checking algorithm).
- Example(s):
- a Supervised Spell Checking Algorithm, such as: seq2spell.
- …
- Counter-Example(s):
- See: Language Translation Algorithm.
References
2017
- Harry Xue. (2017). “Context-sensitive Spell Correction with Deep Learning." Blog post
- QUOTE: ... in developing our context-sensitive spell correction system, which we aptly named seq2spell. Here, instead of translating from one language to another, we “translate” from possibly misspelled lines in English to their corrected versions. Seq2spell reads in a possibly misspelled line, encodes it into a representation of its “meaning” and then outputs the corrected line: ... Treating this subset as ground truth, we then inserted random typos (think randomly replacing, inserting, deleting or swapping characters) on the fly during the training process. ... we benchmarked it against Hunspell, the most popular open-source spell checker, by using both to correct food description typos and ingredient name typos not seen during the training process. Since Hunspell often offers multiple correction suggestions, for experimental purposes we always took the first one it offered. ...