Frequency dependency of the relationship between perceived auditory source width and the interaural cross-correlation coefficient for time-invariant stimuli

Previous research has indicated that the relationship between the interaural cross-correlation coefficient (IACC) of a narrow-band sound and its perceived auditory source width is dependent on its frequency. However, this dependency has not been investigated in sufficient detail for researchers to b...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Journal of the Acoustical Society of America 2005-03, Vol.117 (3), p.1337-1350
Hauptverfasser: MASON, Russell, BROOKES, Tim, RUMSEY, Francis
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Previous research has indicated that the relationship between the interaural cross-correlation coefficient (IACC) of a narrow-band sound and its perceived auditory source width is dependent on its frequency. However, this dependency has not been investigated in sufficient detail for researchers to be able to properly model it in order to produce a perceptually relevant IACC-based model of auditory source width. A series of experiments has therefore been conducted to investigate this frequency dependency in a controlled manner, and to derive an appropriate model. Three main factors were discovered in the course of these experiments. First, the nature of the frequency dependency of the perceived auditory source width of stimuli with an IACC of 1 was determined, and an appropriate mathematical model was derived. Second, the loss of perceived temporal detail at high frequencies, caused by the breakdown of phase locking in the ear, was found to be relevant, and the model was modified accordingly using rectification and a low-pass filter. Finally, it was found that there was a further frequency dependency at low frequencies, and a method for modeling this was derived. The final model was shown to predict the experimental data well.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.1853113