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Titlebook: Computer Models of Speech Using Fuzzy Algorithms; Renato Mori Book 1983 Plenum Press, New York 1983 algorithms.artificial intelligence.pat

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https://doi.org/10.1007/978-3-8350-9523-6Task-dependent knowledge contains syntax, semantics, and pragmatics. Its purpose is the solution of ambiguities and recovery from errors which still remain at the lexical level. Furthermore, task-dependent knowledge may be used to transform the surface structure of a recognized sentence into its conceptual representation.
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Computer Models for Speech Understanding,Research on Automatic Speech Recognition (ASR) began in the early fifties by the attempt to extract significant features from acoustic data and to classify them, using methodologies developed in the area of Pattern Recognition.
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On the Use of Syntactic Pattern Recognition and Fuzzy Set Theory,The scheme introduced in Section 4 of Chapter 1 represents an active model for understanding speech.
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Rules for Characterizing Sonorant Sounds,The purpose of this chapter is to introduce and describe the rules which may be applied when the feature “sonorant” is hypothesized for a segment.
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Automatic Learning of Fuzzy Relations,The problem considered in this chapter refers to those cases for Which pattern descriptions cannot always be obtained in a precise way and, furthermore, in which the interpretation of a pattern is controlled by knowledge sources whose content may also be imprecise.
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Generation and Recognition of Acoustic Patterns,f the Language we intend to speak. The structure of the sentence determines the so called suprasegmental features of the corresponding spoken message. These features affect durations of phonemes (the units of speech) and the time evolution of the frequency of the signal exciting the vocal tract for producing the speech signal.
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