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Language acquisition is the process by which humans acquire the capacity to perceive and comprehend language. In other words, it is how human beings gain the ability to be aware of language, to understand it, and to produce and use words and sentences to communicate. Language acquisition involves structures, rules, and representation.
Although AI seems to be evolving rapidly, it faces many technical challenges. For example, in many cases the language used by AI is very vague, and thus confusing for the user to understand. In addition, there is a "black-box problem" [11] [10] in which there is a lack of transparency and interpretability in the language of AI outputs. In ...
The fact that during language acquisition, children are largely only exposed to positive evidence, [8] meaning that the only evidence for what is a correct form is provided, and no evidence for what is not correct, [9] was a limitation for the models at the time because the now available deep learning models were not available in late 1980s. [10]
Prolog is particularly useful for symbolic reasoning, database and language parsing applications. Artificial Intelligence Markup Language (AIML) [11] is an XML dialect [12] for use with Artificial Linguistic Internet Computer Entity (A.L.I.C.E.)-type chatterbots. Planner is a hybrid between procedural and logical languages. It gives a ...
Natural-language processing is also the name of the branch of computer science, artificial intelligence, and linguistics concerned with enabling computers to engage in communication using natural language(s) in all forms, including but not limited to speech, print, writing, and signing.
Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
Further research and development in ICALL will benefit the fields of applied linguistics, computational linguistics, artificial intelligence, educational technology, to name a few. ICALL will also expand current knowledge about second language acquisition. [5] Despite its limitations, ICALL is a worthwhile field, especially as technology ...
Natural language understanding (NLU) or natural language interpretation (NLI) [1] is a subset of natural language processing in artificial intelligence that deals with machine reading comprehension. NLU has been considered an AI-hard problem.