Machine Learning through Signature Trees. Applications to Human Speech,
Abstract
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. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1970
- Accession Number
- AD0717600
Entities
People
- George M. White
Organizations
- Stanford University