Stanford Artiflcial Intelligence Project
نویسنده
چکیده
Signature tree "machine learning" , pattern recognition heuristics are investigated for the specific problem of computer recognition of human speech. When the data base of given utterances is insufficient to establish trends with confidence, a large number of feature extractors must be employed and "recognition" of an unknown pattern made by comparing its feature values with those of known patterns. When the data base is replete, a "signature" tree can be constructed and recognition can be achieved by the evaluation of a select few features. Learning results from selecting an optimal minimal set of features to achieve recognition. Properties of signature trees and the heuristics for this type of learning are of primary interest in this exposition. The research reported here was supported in part by the Advanced Research Projects Agency of the Office of the Department of Defense (SD-183), and in part by a Public Health Service Post Doctoral Research Fellowship. Reproduced in the USA. Available from the Clearinghouse for Federal Scientific and Technical.Information, Springfield, Virginia 22151. Price: Full size copy $3.00; microfiche copy $ .65.
منابع مشابه
Stanford Artificial Intelligence Project Memo Aim - 158 Computer
PROGRAM SCHEMAS WITH EQUALITY
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تاریخ انتشار 1998