The relative strength of the tone and noise components in iterated rippled noise

Roy D. Patterson, Stephen Handel, William A. Yost, A. Jaysurya Datta

Research output: Contribution to journalArticle

108 Scopus citations

Abstract

Rippled noise is constructed by delaying a random noise and adding it back to the original. Iterated rippled noise (IRN) is constructed by repeating the delay-and-add process. IRN produces a two-component perception, i.e., a buzzy tone with a pitch equal to the reciprocal of the delay and a background noise that sounds like the original random noise. The perceived tone/noise ratio increases with the number of iterations. The effective tone/noise ratio in IRN sounds with 1-16 iterations was measured in a discrimination matching experiment; each IRN was paired with a range of standard sounds, having varying proportions of a broadband noise and a complex lone, to find the point where their perceived tone/noise ratios are the same. The experiment shows that the tone/noise ratio of the matching standard increases 3.8 dB per doubling of the number of iterations in the IRN stimulus. Spectral models of auditory perception explain the pitch of IRN in terms of peaks in the region of the first five to eight harmonics of the reciprocal of the delay. However, the matching data are unaffected when the sound is high-pass filtered at the twelfth harmonic of the delay-above the region of resolved harmonics. We show that a wide range of time-domain auditory models can explain the discrimination matching data by applying autocorrelation, either to the IRN waveform, or to the neural activity patterns produced by the cochlea in response to IRN waves.

Original languageEnglish (US)
Pages (from-to)3286-3294
Number of pages9
JournalJournal of the Acoustical Society of America
Volume100
Issue number5
DOIs
StatePublished - Nov 1 1996
Externally publishedYes

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Acoustics and Ultrasonics

Fingerprint Dive into the research topics of 'The relative strength of the tone and noise components in iterated rippled noise'. Together they form a unique fingerprint.

  • Cite this