The application of the articulation index (Al) model to the fitting of linear amplification was evaluated for 12 subjects with sensorineural hearing loss. Comparisons were made of amplification characteristics specified by the NAL (Byrne & Dillon, 1986) and POGO (McCandless & Lyregaard, 1983) prescriptions, as well as a procedure that attempted to maximize the Al (AlMax). For all subjects, the relationship between percent-correct scores on a nonsense syllable test and Als was monotonic for the two prescriptions, indicating that the Al was effective for comparing conditions typical of those recommended clinically. However, subjects having sloping high-frequency hearing losses demonstrated nonmonotonicity due to poor performance in the AlMax condition. For these subjects, the AlMax condition required much more gain at high than at low frequencies, circumstances that Skinner (1980) warned will cause less-than-optimal performance for individuals having sloping high-frequency hearing loss.

It is often assumed that the articulation index (AI) is a sensitive and appropriate metric for making comparisons among frequency-gain characteristics of hearing aids, and that the characteristic yielding the highest AI will result in the best speech intelligibility score. In evaluating these assumptions, 12 hearing-impaired subjects listened to nonsense syllables under conditions of amplification prescribed by the NAL [D. Byrne and H. Dillon, Ear Hear. 7, 257–265 (1986)] and POGO [G. A. McCandless and P. E. Lyregaard, Hear. Instrum. 34, 16–21 (1983)] hearing aid fitting formulas. These two prescriptive methods recommend similar frequency responses, although the POGO consistently provides more overall gain. In a third condition, the goal of amplification was to insure that the speech was fully audible (AI = 1.0). Results suggest that the articulation index is useful for predicting percent-correct intelligibility scores for some, but not all, of the hearing-impaired subjects. Interestingly, the AI = 1.0 condition did not necessarily yield the best percent-correct intelligibility score. [Work supported by NICHHD T32 HD-07151, NINCDS NS 12125, and the Bryng Bryngelson Communication Disorders Research Fund at the University of Minnesota.]

Some current single-microphone hearing aids employ techniques for adaptively varying the frequency-gain characteristics in an attempt to improve speech reception in noise. The potential benefit of this strategy depends on the spectral spread of masking and the degree to which it can be reduced by changing the frequency-gain characteristic. In this study these benefits were examined for subjects with normal hearing under static listening conditions. In the unprocessed condition, subjects were presented with nonsense syllables in an octave-band noise centered on 0.5, 1, or 2 kHz. The frequency-gain characteristic was then modified with the goal of reducing the intensity of the frequency region containing the octave-band noise. This processing resulted in increases as large as 60 percentage points in consonant-correct scores with the low- and mid-frequency octave noise bands, and a small increase with the high-frequency noise. Masking patterns produced by the octave noises were also measured and were related to the intelligibility results via an analysis based on Articulation Theory. The Articulation Index was also used to compare the effectiveness of three adaptive rules. A simple multiband volume control is expected to provide much of the benefit of more sophisticated systems without the need for separate estimation of input speech and noise spectra.

Recent studies of the relation between loudness and intensity difference limens (DLs) suggest that, if two tones of the same frequency are equally loud, they will have equal relative DLs [ R. S. Schlauch and C. C. Wier, J. Speech Hear. Res. 30, 13-20 ( 1987); J. J. Zwislocki and H. N. Jordan, J. Acoust. Soc. Am. 79, 772-780 (1986) ]. To test this hypothesis, loudness matches and intensity DLs for a 1000-Hz pure tone in quiet and in a 40-dB SPL spectrum level broadband noise were obtained for four subjects with normal heating. The DLs were obtained in both gated-and continuous-pedestal conditions. Contrary to previous reports, equally loud tones do not yield equal relative DLs at several midintensities in the gated condition and at many intensities in the continuous condition. While the equal-loudness, equal-relative-DL hypothesis is not supported by the data, the relation between loudness and intensity discrimination appears to be well described by a model reported by Houtsma et al. [J. Acoust. Soc. Am. 68, 807-813 (1980) ].

Vickers, Moore, and Baer [J. Acoust. Soc. Am. 110, 1164–1175 (2001)] reported that hearing-impaired subjects with cochlear “dead regions” benefited from amplification of frequencies up to an octave above the estimated edge frequency of the dead region, but not beyond, whereas hearing-impaired subjects without dead regions did show benefit beyond this boundary. Dead regions are thought to have no functioning inner hair cells. Vickers et al. indicated that a clinical test for detecting dead regions would provide supplementary information that is important for hearing aid fitting. Furthermore, they suggested that the articulation index (AI) may overestimate the potential benefit of amplification for listeners with dead regions because the AI does not account for the presence of dead regions. To evaluate their claims, we conducted an AI analysis [H. Fletcher, Speech and Hearing in Communication (Van Nostrand, New York, 1953); H. Fletcher and R. H. Galt, J. Acoust. Soc. Am. 22, 89–151 (1950)]. Results show that the AI is generally accurate in predicting the consonant recognition test scores of Vickers et al.’s subjects irrespective of the presence/absence of dead regions. This suggests that audiogram differences account for the observed performance differences; it was not necessary to invoke dead regions to explain the speech test results. The results of the AI analysis are sufficiently accurate to call in to question whether a clinical test for dead regions would offer additional predictive information.