The amplitude modulations (AMs) in speech signals are useful cues for speech recognition. Several adaptation mechanisms may make the detection of AM in noisy backgrounds easier when the AM carrier is presented later rather than earlier in the noise. The aim of the present study was to characterize temporal adaptation to noise in AM detection. AM detection thresholds were measured for monaural (50 ms, 1.5 kHz) pure-tone carriers presented at the onset ('early' condition) and 300 ms after the onset ('late' condition) of ipsilateral, contralateral, and bilateral (diotic) broadband noise, as well as in quiet. Thresholds were 2-4 dB better in the late than in the early condition for the three noise lateralities. The temporal effect held for carriers at equal sensation levels, confirming that it was not due to overshoot on carrier audibility. The temporal effect was larger for broadband than for low-band contralateral noises. Many aspects in the results were consistent with the noise activating the medial olivocochlear reflex (MOCR) and enhancing AM depth in the peripheral auditory response. Other aspects, however, indicate that central masking and adaptation unrelated to the MOCR also affect both carrier-tone and AM detection and are involved in the temporal effects.
Previous studies have employed signal detection theory to analyze data from speech and nonspeech experiments. Typically, signal distributions were assumed to be Gaussian. Schouten and van Hessen [J. Acoust. Soc. Am. 104, 2980–2990 (1998)] explicitly tested this assumption for an intensity continuum and a speech continuum. They measured response distributions directly and, assuming an interval scale, concluded that the Gaussian assumption held for both continua. However, Pastore and Macmillan [J. Acoust. Soc. Am. 111, 2432 (2002)] applied ROC analysis to Schouten and van Hessen’s data, assuming only an ordinal scale. Their ROC curves suppported the Gaussian assumption for the nonspeech signals only. Previously, Lopez-Bascuas [Proc. Audit. Bas. Speech Percept., 158–161 (1997)] found evidence with a rating scale procedure that the Gaussian model was inadequate for a voice-onset time continuum but not for a noise-buzz continuum. Both continua contained ten stimuli with asynchronies ranging from −35 ms to +55 ms. ROC curves (double-probability plots) are now reported for each pair of adjacent stimuli on the two continua. Both speech and nonspeech ROCs often appeared nonlinear, indicating non-Gaussian signal distributions under the usual zero-variance assumption for response criteria.
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