Abstract
Linguistics, as every other empirical science, is a complex mixture of theory and observation. Extremely little is known about syntactic complexity, though this notion has come up in many discussions of style, readability, and, more recently, of mechanization of syntactic analysis. Often, information loss less transformation into syntactically simple sentences is regarded as a helpful, perhaps even necessary step prior to further processing. Autonomous, high-quality machine translation (MT) between natural languages according to rigid algorithms may safely be considered as dead. Such translation on the basis of learning abilities is stillborn. The combined interest in MT is sometimes defended on the grounds that though it is indeed extremely unlikely that computers working according to rigid algorithms will ever produce high-quality translations, there still exists a possibility that computers with considerable learning, or self-organizing, abilities will be able, through training and experience, to improve their initial algorithms and thereby constantly improve their output until adequate quality is achieved.
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