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Natural Language Part 1
 
 


A "natural language" is a human language such as English, Spanish, French, and so on. A very important task in artificial intelligence is getting intelligent systems to be more comfortable with human language. Natural language is both one of the oldest areas of artificial intelligence, and one of the most important and current areas of AI. Indeed, natural language work really predates the development of computers. As far back as the 1800's, plans for an Analytical Engine were designed by Lady Ada Lovelace and Charles Babbage. The Engine was never built (a previous version called the Difference Engine capable only of mathematical computation was partially built), but it was envisioned that natural language processing would be part of its capabilities. In the 1940's, Alan Turing developed something called the "Turing Test" to determine whether a computer has attained intelligence. At the time, a popular game involved asking typed questions of a man and a woman, both hidden from view, who would type their responses. The objective for the man was to try to pretend, through his answers, that he was really a woman; the objective for the woman was to try, through her answers, to expose the man as a fraud as quickly as possible; and the goal for the questioners was to try to guess who was who as quickly as possible. The sensibilities of the time generally prevented overly specific questions about, say, the responder's anatomy that a questioner, especially a female questioner, could use to discern the gender of the responder.

Around this time, mathematician Alan Turing began thinking about what capabilities a machine would need to have to be capable of thought. He designed an abstract machine called the "Turing machine" which could perform basic computation. And-perhaps in part because he was gay and had thought more about gender issues than many people of his time-he revised the game of a man pretending to be a woman so that instead a computer would pretend to be a human. This became known as the "Turing test"-if a machine, through conversation in human language over some type of teletype device, could successfully pass itself off as human, it had attained intelligence. Some versions of the "Turing test" combined the two tests, so that a computer would be deemed to be intelligent if it could imitate a woman better than a man could. Other versions placed restrictions on the questions similar in spirit to restricting overtly personal questions that a woman would be able to answer better than a man. And, ironically, the Internet has created many new opportunities to play the original parlor game. If someone shows up on an Internet bboard calling themselves "Lisa" or "Angela" or "Nadia", how can you really be sure they are a woman?

We still do not have a computer capable of passing the Turing Test, although an annual competition known as the Loebner Prize is devoted to finding programs which are able to pass the Turing Test in some very restricted area of human conversation. An annual prize is awarded to the most "human" computer program, although no program has succeeded in fooling a human. A significantly larger prize would be awarded for a machine which actually passed the Turing Test. As can be seen, the programs' performance does not really come close to matching that of a human being. However, we have made considerable progress in the years since Turing proposed his test. Grammar checkers, while not capable of determining the meaning underlying natural language, routinely correct grammatical errors in online documents. Voice recognition software is sufficiently reliable to be useful.

Natural language is difficult largely because the meaning of words is often not precise. Whereas in computer languages everything always has a very precise meaning, in natural language it depends heavily upon the context in which it is used. Consider, for example, the last sentence in the previous paragraph: "voice recognition software is sufficiently reliable to be useful." What does the word "useful" mean in this sentence? The meaning of this word isn't really defined. There is an assumption being made here that you have had the experience of using voice recognition software package, or speaking on the telephone to an automated customer service line, and have therefore had some experience in verbal communication with a computer. This gives you a clear basis to agree-or disagree-with my claim that this software is "useful". Without that background, it would be very difficult to even have a clue what the word "useful" means in this context, much less agree or disagree with me.

However, despite its difficulty, we are far better poised today than in the past to make serious inroads into natural language understanding. I recall late in 1993 writing a proposal for Rama about designing a natural language system based upon large amounts of human-computer interactions. The idea was that with copious human-computer conversations, together with advanced machine learning using neural networks, one could train a computer to successfully interact with humans using human language. The proposal, which I submitted inwardly to Rama but never sent in printed form, suffered from the weakness that it would be very costly to pay for humans to "talk" with computers enough to make it work. Nowadays, however, the Internet provides so many opportunities for computers to interact with humans and with human language, essentially free of charge, that this difficulty no longer exists.

In addition to capabilities such as grammar checkers and voice recognition software, another area in which natural language processing is being used is in automated email response software. This software, which is being produced by companies such as Brightware and Kana, is capable of providing automated response to email queries so that companies don't delay a long time in responding. The automated response generally takes the form of categorizing the message, sending a suitably customized response to the sender, and notifying the appropriate person at the recipient company. While it is not capable of general-purpose interpretation of natural language, it is capable of doing some intelligent work in parsing human language.

In the next couple of editions, we will explore in more detail some of these natural language technologies. In the meantime, for further information you might check out the following books: Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition and Natural Language Understanding.

Next edition: Natural Language Part 2 - Automated Email Response

 
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