Abstract
Speech can be modeled as the sum of high frequency carrier signals (temporal fine structure; TFS) from different frequency bands modulated in amplitude by a low frequency modulator (amplitude envelope; ENV). Previous research revealed that ENV cues alone can be sufficient for speech intelligibility. The present research tested the role of signal periodicity to reconstruct ENV information. Signal periodicity was measured by harmonics-to-noise ratio (HNR) with HNR = 10*log10(signal/noise) in 60 msec windows at 10 msec steps in each of 6 frequency bands (Greenwood spacing) of different speech signals (bw = 8 kHz). Resulting HNR contours were correlated with respective ENVs in each frequency band and high correlations (r>0.8) could be obtained. This was also true when ENV was removed in each band (multiplying the signal with the inverse Hilbert ENV) prior to processing of the HNR contour. HNR contours were used to amplitude modulate noise (noise vocoding). The HNR vocoded speech revealed to be equally intelligible as ENV vocoded speech. Results give rise to the view that speech periodicity—which is extremely robust towards linear system distortions—might lend itself for recovering ENV cues in the auditory processing of speech.
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