Scientists teach computer to speak

By Will Knight, ZDNet UK
Wednesday, April 18, 2001 12:00 AM
Could tutoring a computer be the way to develop machines that talk back?

Scientists in Israel are treating their computer like an unruly child, correcting its mistakes and punishing it for errors.

If you've ever felt the urge to reprimand your PC after it accidentally deletes a day's work then you might sympathise with this behaviour, but there is more to this than meets the eye. These researchers are, in fact, conducting pioneering work into the development of personal computer that they hope could eventually carry out a meaningful relationship with its owner.

The company behind this work, Dutch-based firm Artificial Intelligence (AI), caused a stir in technology circles recently by claiming to have developed a computer that had learnt language to the level of a 15 month-old child. At a research facility in Tel-Aviv, Israel, Artificial Intelligence (AI) demonstrated its computerised toddler -- named HAL -- for the first time and revealed that it is betting million pounds on the scheme.

For such ambitious goals, HAL's design is surprisingly simple. Running on top of Windows 2000, HAL is little more than handful of simple learning algorithms. But from these simple building blocks, HAL's creators hope to generate a computer capable of holding its own in conversation.

Past attempts have typically involved programming computers with basic rules of language, a technique that has always fallen short of providing stimulating and, at times, even comprehensible conversation. This may be because, according to linguistic theorists, the rules of language are virtually impossible to pin down, existing only in a state of flux.

In contrast to these previous attempts, HAL is designed to learn language for itself. Simple learning algorithms allow HAL to mimic different patterns of text characters. The real innovation occurring at AI, however, is that a child psychologist interacts with HAL, correcting mistakes and nurturing correct use of words and sentences.

At the heart of the learning algorithm is the interplay between the computer's prior experience and its ability to predict what output will be rewarded. The approach is taken from Bayesian statistical analysis; an area of mathematics that involves calculating probabilities according to newly accumulated knowledge. Andrew Blake, a mathematics and electronics researcher at Cambridge University, describes this as "a very strong field in AI at the moment".

Jason Hutchens, chief scientist and programmer on the HAL project, says that this basic probabilistic approach enable the computer to form its own "atoms" of language, which turn out to be coherent words and sentences. Hutchens has a growing reputation in the field of artificial intelligence. In 1996, he won the Loebner prize, awarded by the Cambridge Centre for Behavioural Studies in Australia to the most human-like conversational program entered, with a simulator called Hex. He also helped design the artificial intelligence engine in the popular and impressive new computer game Black and White.

"Hutchens is a very clever guy," says Professor Yorick Wilks, head of the Department of Computer Science at the University of Sheffield, who's own research has been entered into the Loebner prize in the past. "He's proved that he can create a convincing conversational machine already."

However, as Hutchens says, he is not concerned with creating a machine that is genuinely intelligent, assuming such an abstract thing as intelligence can ever be measured. Instead, he and the rest of AI simply hope to create a computer with the appearance of intelligence.

According to some measurements, this is all it takes. In 1950, British mathematician Alan Turing proposed a test for intelligence whereby any machine capable of convincing a human that it was talking to another human should be considered intelligent. This test still used by some artificial intelligence researchers today.

Ironically, because HAL is not programmed with hard and fast rules, just basic learning ability, Hutchens cannot know how exactly HAL processes language. "I have an understanding of the algorithms and I have my expectations but HAL is constantly surprising me," he says. "Hal knows that cat and dog are associated through a set of symbols. It is working at the moment and working beautifully."


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