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nication. This, in turn, will result in a vast market of incalculable commercial value.
It is, of course, entirely possible that the majority opinion is correct, that a diligent effort resulting in a long sequence of rapid incremental improvements will yield the desired perfected speech recognition technology. It is, unfortunately, also possible that this strategy will run afoul of the "first-step fallacy" (Dreyfus, 1972), which warns that one cannot reach the moon by climbing a tree even though such an action initially appears to be a move in the right direction. Ultimately, progress stops far short of the goal when the top of the tree is reached.
If, as I argue, the latter possibility exists, what strategy should we use to defend against its undesirable outcome? The answer should be obvious. Openly acknowledge the risks of the incremental approach and devote some effort to achieving the paradigm shift from signal transcription to message comprehension alluded to earlier.
Perhaps more important, however, is recognition of the uniqueness of our technological goal. Unlike all other technologies that are integral parts of our daily lives because they provide us with capabilities otherwise unattainable, automatic speech recognition promises to improve the usefulness of a behavior at which we are already exquisitely proficient. Such a promise cannot be realized if the technology supporting it degrades our natural expertise in spoken communication. Since the present state of the art requires a serious diminution of our abilities and since we presently do not know how to leap the performance chasm between humans and machines, perhaps we should invest more in research aimed at finding a more nearly anthropomorphic and, by implication, potent technology. This would, of course, alter the subtle balance among science, technology, and the marketplace more toward precommercial experimentation with proportionately less opportunity for immediate profit. There is good reason to believe, however, that ultimately this strategy will afford the greatest intellectual, financial, and social rewards.
Dreyfus, H. L., What Computers Can't Do: A Critique of Artificial Reason, Harper, New York, 1972.
Goldstine, H. H., The Computer from Pascal to Von Neumann, Princeton University Press, Princeton, N.J., 1972, p. 344.
Kuhn, T. S., The Structure of Scientific Revolutions, 2nd ed., University of Chicago Press, Chicago, 1970, pp. 92 ff.
Oberteuffer, J., "Major Progress in Speech Technology Affirmed at National Academy of Sciences Colloquium," ASR News, Vol. 4, No. 2, Feb. 1993, pp. 5-7.