"Acoustic-Phonetic Knowledge Representation in a            Statistically Based Classifier
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This research is aimed at the development of a speaker-                         independent phonetic classification system for continuous speech                which retains the statistical and automatic-training capabilities               of implicit representational strategies, while accommodating                    explicit and intuitive descriptions of recognition vocabularies.                The classifier is being implemented within a recognition                        framework with three main components: a finite-state                            pronunciation network whose branches correspond to linguistically               well-defined units; a set of generalized acoustic pattern                       matchers; and a segment-based dynamic programming search.  A                    primary feature of this framework is its ability to incorporate                 acoustic-phonetic features computed over variable-duration,                     segment-sized units of the speech signal, in addition to the                    general fixed-rate acoustic measures typically employed in                      traditional pattern-matching systems.
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[{'Code': '6840', 'Text': 'ROBOTICS'}, {'Code': '6845', 'Text': 'HUMAN COMPUTER INTER PROGRAM'}]
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