ELIZA was an early natural language processing system capable of carrying on a limited form of conversation with a user. It was developed by Weizenbaum in 1966. It is a remarkably simple program that makes use of pattern matching to process the input and translate it into suitable outputs. Consider the following session with a version of ELIZA that limited the responses of a psychotherapist.
You are like my brother in some ways.
WHAT RESEMBLANCE DO YOU SEE?
You are not very intelligent but I think you don’t want me to notice that.
WHAT MAKES YOU THINK I AM NOT INTELLIGENT?
You don’t agree with me.
WHY DO YOU THINK I DON’T AGREE WITH YOU?
You are afraid of me.
DOES IT PLEASE YOU TO BELIEVE I AM AFRAID OF YOU?
I need some help, that much seems certain.
WHAT WOULD IT MEAN TO YOU IF YOU GOT SOME HELP?
This program is one of the most popular AI programs of all time since it carried the keyword based analysis approach to an absurd (but impressive) extreme. The success of this simple technique in this domain is due to the fact that ELIZA doesn’t actually need to know anything to a mimic a psychotherapist. As Weizenbaum notes, this is one of the few dialogue genres where the listener can act if they know nothing of the world. ELIZA’s deep relevance to Turing’s ideas is that many people who interacted with ELIZA cam to believe that it really understood them and their problems. Indeed, Weizenbaum (1976) notes that many of these people continued to believe in ELIZA’s abilities even after the program’s operation was explained to them.
It was developed by Woods in 1970. It is one of the largest and most successful question-answering system using AI techniques. This system had a separate syntax analyzer and a semantic interpreter. Its parser was written in ATN (Augmented Transition Network) form. The system was used in various tests and responded successfully to queries like followings:
® How many oak trees have height greater than 15 inches?
® What is the average concentration of hydrogen and oxygen in water?
® Which one is the oldest material between Iron, Bauxite and Aluminum?
The LUNAR system is mainly deal with queries. But the performance of the system is very good than other systems.
HAL is an artificial agent capable of such advanced language processing behaviour as speaking and understanding English. The HAL system was developed by Arthur C. Clarke. Generally HAL system is useful for language and speech recognition. By speech and language processing we have in mind those computational techniques that process spoken and written human language. HAL require much broader and deeper knowledge of language. To determine what the user is saying, HAL must be capable of analyzing an incoming audio signal and recovering the exact sequence of words user used to produce that signal. Similarly, in generating its response HAL must be able to take a sequence of words and generate an audio signal that the user can recognize. Both of these tasks require knowledge about phonetics and phonology which can help model how words are pronounced in colloquial speech.
It was developed by Winograd in 1970. It was a dialogue system which could converse with a human user about simple world containing building blocks. It is a simulation based programming system involving of a hand and eye. It is a syntax based system which is a combination of deep and surface structure. It contains a syntactic parser with a fairly wide coverage which builds surface structures that are not simply of trivial category labeling. It performs the combination and integration of many components which will create a total system. For example: User 1: Chose a green pen.
User 2: Write with the pen.
SHRDLU: I DON’T UNDERSTAND WHICH PEN YOU MEAN.
Copyright © 2018-2020 BrainKart.com; All Rights Reserved. Developed by Therithal info, Chennai.