Wednesday, February 02, 2005

http://en.wikipedia.org/wiki/Natural_language_processing

Some problems which make NLP difficult
Word boundary detection
In spoken language, there are usually no gaps between words; where to place the word boundary often depends on what choice makes the most sense grammatically and given the context. In written form, languages like Chinese do not signal word boundaries either.
Word sense disambiguation
Any given word can have several different meanings; we have to select the meaning which makes the most sense in context.
Syntactic ambiguity
The grammar for natural languages is not unambiguous, i.e. there are often multiple possible parse trees for a given sentence. Choosing the most appropriate one usually requires semantic and contextual information.
Imperfect or irregular input
Foreign or regional accents and vocal impediments in speech; typing or grammatical errors, OCR errors in texts.
Speech acts and plans
Sentences often don't mean what they literally say; for instance a good answer to "Can you pass the salt" is to pass the salt; in most contexts "Yes" is not a good answer, although "No" is better and "I'm afraid that I can't see it" is better yet. Or again, if a class was not offered last year, "The class was not offered last year" is a better answer to the question "How many students failed the class last year?" than "None" is.

1 comment:

Arthur said...

Dennis, thanks for for letting me know about your AI weblog. -Mentifex (Arthur)