Modeling the identification of concurrent vowels with different fundamental frequencies.
Human listeners are better able to identify two simultaneous vowels if the fundamental frequencies of the vowels are different. A computational model is presented which, for the first time, is able to simulate this phenomenon at least qualitatively. The first stage of the model is based upon a bank of bandpass filters and inner hair-cell simulators that simulate approximately the most relevant characteristics of the human auditory periphery. The output of each filter/hair-cell channel is then autocorrelated to extract pitch and timbre information. The pooled autocorrelation function (ACF) based on all channels is used to derive a pitch estimate for one of the component vowels from a signal composed of two vowels. Individual channel ACFs showing a pitch peak at this value are combined and used to identify the first vowel using a template matching procedure. The ACFs in the remaining channels are then combined and used to identify the second vowel. Model recognition performance shows a rapid improvement in correct vowel identification as the difference between the fundamental frequencies of two simultaneous vowels increases from zero to one semitone in a manner closely resembling human performance. As this difference increases up to four semitones, performance improves further only slowly, if at all.
Meddis
R
R
Department of Human Sciences, University of Technology, Loughborough, United Kingdom.
Hewitt
M J
MJ
D000162:Acoustics; D001489:Basilar Membrane / Q000502:physiology; D004424:Ear Canal / Q000502:physiology; D004432:Ear, Middle / Q000502:physiology; D006199:Hair Cells, Auditory, Inner / Q000502:physiology; D006309:Hearing / Q000502:physiology*; D006801:Humans; D008954:Models, Biological; D010700:Phonetics; D010898:Pitch Perception / Q000502:physiology*; D013018:Sound Spectrography; D000159:Vestibulocochlear Nerve / Q000502:physiology