A QUANTITATIVE MODEL FOR LOUDNESS DISCRIMINATION

Abstract

A loudness function based on detailed waveform manipulations and predicting well-known empirical results is hypothesized. The loudness function is stated for a sine wave signal as well as for a Gaussian signal in noise. Additional hypotheses provide analytic expressions which predict several psychoacoustic phenomena. One hypothesis leads to prediction of difference limens at both small and medium intensity levels and provides a major departure from the classic concepts due to Weber and Fechner. Another provides an accurate quantitative theory for masking. A third leads to an explanation for a type of monaural diplacusis and suggests a multicomponent pattern recognition representation for hearing which involves an artificial cochlea. The pattern system is extended to suggest mechanisms for language-independent bandwidth reduction to less than 10 cycles per second. The pertinent analog model may in addition display imperfections emulating human behavior. The theory suggests several test procedures which may be of use in clinical applications. Extensions to sense modalities other than hearing are indicated. (Author)

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1962
Accession Number
AD0282724

Entities

People

  • John L. Stewart

Organizations

  • University of Arizona

Tags

DTIC Thesaurus Topics

  • Bandwidth
  • Discrimination
  • Human Behavior
  • Hypotheses
  • Intensity
  • Loudness
  • Pattern Recognition
  • Recognition
  • Sine Waves
  • Waveforms
  • Waves

Readers

  • Auditory Neuroscience/Auditory Physiology.
  • Theoretical Analysis.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference