Messenger For as long as we have been able to stand upright and speak, we have told stories. They explained the mysteries of the world:
All three explanations describe exactly the same theory — the same function from n to h, over the entire domain of possible values of n. Thus we could prefer A or B over C only for reasons other than the theory itself.
We might find that A or B gave us a better understanding of the problem. A and B are certainly more useful than C for figuring out what happens if Congress exercises its power to add an additional associate justice.
Theory A might be most helpful in developing a theory of handshakes at the end of a hockey game when each player shakes hands with players on the opposing team or in proving that the number of people who shook an odd number of hands at the MIT Symposium is even.
How successful are statistical language models? Chomsky said words to the effect that statistical language models have had some limited success in some application areas. Let's look at computer systems that deal with language, and at the notion of "success" defined by "making accurate predictions about the world.
Their operation cannot be described by a simple function.
Some commercial systems use a hybrid of trained and rule-based approaches. Of the language pairs covered by machine translation systems, a statistical system is by far the best for every pair except Japanese-English, where the top statistical system is roughly equal to the top hybrid system.
All systems use at least some statistical techniques. Now let's look at some components that are of interest only to the computational linguist, not to the end user: The majority of current systems are statistical, although we should mention the system of Haghighi and Kleinwhich can be described as a hybrid system that is mostly rule-based rather than trained, and performs on par with top statistical systems.
Part of speech tagging: Most current systems are statistical. The Brill tagger stands out as a successful hybrid system: There are many parsing systems, using multiple approaches. Almost all of the most successful are statistical, and the majority are probabilistic with a substantial minority of deterministic parsers.
Clearly, it is inaccurate to say that statistical models and probabilistic models have achieved limited success; rather they have achieved a dominant although not exclusive position. Another measure of success is the degree to which an idea captures a community of researchers.
As Steve Abney wrote in"In the space of the last ten years, statistical methods have gone from being virtually unknown in computational linguistics to being a fundamental given.
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