Feature Selection in Auditory Perception

Abstract

Feature extraction plays a fundamental role in most theories of pattern recognition, but despite its importance, the extraction process is not well defined. Two contrasting views of feature extraction can be identified, one which emphasizes invariant feature detection and one which emphasizes flexible feature selection. The invariant detector approach assumes that the auditory system is equipped with finely tuned feature detectors that respond to specific stimulus properties. In this view, stimuli are described in terms of property lists of specific features. In contrast, the more flexible, process-oriented approach assumes that the auditory system is equipped with a set of rules and criteria for feature selection. In this view, the important perceptual features reflect the underlying structure of the stimuli. Research on timbre and pitch perception has supported a flexible, process-oriented approach. The flexibility of this approach offers particular advantages in that it can explain the effects of stimulus and task context on performance. Both types of context influence the perception of complex sounds. Stimulus context affects the structure of the stimulus space and consequently the features that would be extracted by a structure preserving transformation. Task context affects the relative importance of features in making similarity judgements and classification decisions. The two approaches to feature extraction have important implications for the development of auditory pattern recognition theory.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1978
Accession Number
ADA058423

Entities

People

  • James A. Ballas
  • James H. Howard Jr.

Organizations

  • The Catholic University of America

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Auditory Perception
  • Biological Sciences
  • Detection
  • Detectors
  • Engineering
  • Feature Extraction
  • Feature Selection
  • Frequency
  • Human Factors Engineering
  • Military Research
  • New York
  • Pattern Recognition
  • Probability
  • Psychology
  • Systems Engineering

Readers

  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • Space