Using statistical decision theory to predict speech intelligibility. III. Effect of audibility on speech recognition sensitivity.

The speech recognition sensitivity (SRS) model [H. Müsch and S. Buus, J. Acoust. Soc. Am. 109, 2896-2909 (2001)] is a macroscopic model for predicting speech intelligibility. The present study proposes a modification to the relation between the SRS model's audibility-noise variance and the signal-excitation to noise-excitation ratio (SNRE) in the auditory periphery. The modified relation is derived from data obtained in nine studies that measured normal-hearing listeners' consonant-recognition performance at several levels of speech-spectrum shaped noise. When the audibility-noise variance is directly proportional to the relative power of the noise excitation in the auditory periphery, the SRS model yields good predictions of the data. Four of the nine studies also reported consonant-recognition performance in various filtering conditions. Good predictions of these data were achieved with SRS model parameters that were consistent with the model parameters fitting the speech-in-noise data and with the model parameters used in the original SRS papers.

Identifying dead regions in the cochlea: psychophysical tuning curves and tone detection in threshold-equalizing noise.

OBJECTIVE: Recent studies indicate that high-frequency amplification may provide little benefit for listeners with moderate-to-severe high-frequency hearing loss, and may even reduce speech recognition. Moore and colleagues have proposed a direct link between this lack of benefit and the presence of regions of nonfunctioning inner hair cells (dead regions) in the basal cochlea and have suggested that psychophysical tuning curves (PTCs) and tone detection thresholds in threshold-equalizing noise (TEN) are psychoacoustic measures that allow detection of dead regions ([Moore, Huss, Vickers, Glasberg, & Alcántara, 2000]; [Vickers, Moore, & Baer, 2001]). The experiments reported here examine the consistency of TEN and PTC tasks in identifying dead regions in listeners with high-frequency hearing loss. DESIGN: Seventeen listeners (18 ears) with steeply sloping moderate-to-severe high-frequency hearing loss were tested in PTC and TEN tasks intended to identify ears with high-frequency dead regions. In the PTC task, pure-tone signals of fixed level were masked by narrowband noise that slowly increased in center frequency. For a range of signal frequencies, noise levels at masked threshold were determined as a function of masker frequency. In the TEN task, masked thresholds for pure-tone signals were determined for a fixed-level, 70 dB/ERB TEN masker (for some listeners, 85 or 90 dB/ERB TEN was also tested at selected probe frequencies). RESULTS: TEN and PTC results agreed on the presence or absence of dead regions at all tested frequencies in 10 of 18 cases (approximately 56% agreement rate). Six ears showed results consistent with either mid- or high-frequency dead regions in both tasks, and four ears did not show evidence of dead regions in either task. In eight ears, the TEN and PTC tasks produced conflicting results at one or more frequencies. In instances where the TEN and PTC results disagreed, the TEN results suggested the presence of dead regions whereas the PTC results did not. CONCLUSIONS: The 56% agreement rate between the TEN and PTC tasks indicates that at least one of these tasks was only partially reliable as a diagnostic tool. Factors unrelated to the presence of dead regions may contribute to excess masking in TEN without producing tip shifts in PTCs. Thus it may be appropriate to view tuning curve results as more reliable in cases where TEN and PTC results disagree. The current results do not provide support for the TEN task as a reliable diagnostic tool for identification of dead regions.