← 学习库 Speech and Language Processing 本册目录

1.6.7 On Multiple Discoveries

Even in this brief historical overview, we have mentioned a number of cases of multiple independent discoveries of the same idea. Just a few of the “multiples” to be discussed in this book include the application of dynamic programming to sequence comparison by Viterbi, Vintsyuk, Needleman and Wunsch, Sakoe and Chiba, Sankoff, Reichert et al., and Wagner and Fischer (Chapters 3, 5 and 6) the HMM/noisy channel model of speech recognition by Baker and by Jelinek, Bahl, and Mercer (Chapters 6, 9, and 10); the development of context-free grammars by Chomsky and by Backus and Naur (Chapter 12); the proof that Swiss-German has a non-context-free syntax by Huybregts and by Shieber (Chapter 15); the application of unification to language processing by Colmerauer et al. and by Kay in (Chapter 16).

Are these multiples to be considered astonishing coincidences? A well-known hypothesis by sociologist of science Robert K. Merton (1961) argues, quite the contrary, that

all scientific discoveries are in principle multiples, including those that on the surface appear to be singletons.

Of course there are many well-known cases of multiple discovery or invention; just a few examples from an extensive list in Ogburn and Thomas (1922) include the multiple

原书第 14 页

invention of the calculus by Leibnitz and by Newton, the multiple development of the theory of natural selection by Wallace and by Darwin, and the multiple invention of the telephone by Gray and Bell. $ ^{3} $ But Merton gives a further array of evidence for the hypothesis that multiple discovery is the rule rather than the exception, including many cases of putative singletons that turn out be a rediscovery of previously unpublished or perhaps inaccessible work. An even stronger piece of evidence is his ethnomethodological point that scientists themselves act under the assumption that multiple invention is the norm. Thus many aspects of scientific life are designed to help scientists avoid being “scooped”; submission dates on journal articles; careful dates in research records; circulation of preliminary or technical reports.

← 1.6.6 The Rise of Machine Learning: 2000–20071.6.8 A Final Brief Note on Psychology →