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Related Experiment Videos

Roving-level tone-in-noise detection.

G Kidd1, C R Mason, M A Brantley

  • 1Department of Communication Disorders, Boston University, Massachusetts 02215.

The Journal of the Acoustical Society of America
|October 1, 1989
PubMed
Summary
This summary is machine-generated.

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Detecting tones in noise is challenging when overall sound levels change. This study found that listeners can still detect tones by focusing on spectral shape, not just loudness, even with varying noise levels.

Area of Science:

  • Auditory perception
  • Psychoacoustics
  • Signal detection theory

Background:

  • Listener's ability to detect auditory signals in noise is crucial for understanding speech and environmental sounds.
  • Traditional models often assume fixed noise levels, which may not reflect real-world auditory environments.
  • Varying noise levels (roving) can complicate detection by preventing reliance on overall intensity cues.

Purpose of the Study:

  • To investigate the detectability of tones in random noise under fixed and roving overall sound levels.
  • To determine if listeners can detect tones when overall sound level varies within trials.
  • To test the validity of the critical-band energy-detector model under roving conditions.

Main Methods:

  • Measured the detectability of tones and intensity increments in bands of random noise.

Related Experiment Videos

  • Employed conditions with fixed overall sound levels and conditions with randomly roved levels within trials.
  • Analyzed masked thresholds as a function of noise bandwidth for both fixed and roving conditions.

    • Main Results:

    • At supracritical bandwidths, masked thresholds were similar regardless of level roving.
    • At subcritical bandwidths, some roving conditions showed higher thresholds.
    • Even with significant roving, thresholds were lower than predicted by level-detection models, suggesting alternative strategies.

    Conclusions:

    • The traditional critical-band energy-detector model is insufficient to explain detection performance under roving-level conditions.
    • Listeners likely utilize spectral shape or waveform characteristics for tone detection when overall level is unpredictable.
    • Auditory perception adapts to varying sound levels by employing more sophisticated discrimination mechanisms than simple energy detection.