Effect of the Target and Conflicting Frequency and Time Ranges on Consonant Enhancement in Normal-Hearing Listeners

Dichotic spectral integration range for consonant recognition in listeners with normal hearing

Dichotic spectral integration range, or DSIR, was measured for consonant recognition with normal-hearing listeners. DSIR is defined as a frequency range needed from 0 to 8,000 Hz band in one ear for consonant recognition when low-frequency information of the same consonant was presented to the opposite ear. DSIR was measured under the three signal processing conditions: (1) unprocessed, (2) target: intensified target spectro-temporal regions by 6 dB responsible for consonant recognition, and (3) target minus conflicting: intensified target regions minus spectro-temporal regions that increase confusion. Each consonant was low-pass filtered with a cutoff frequency of 250, 500, 750, and 1,000 Hz, and then was presented in the left ear or low-frequency (LF) ear. To create dichotic listening, the same consonant was simultaneously presented to the right ear or high-frequency (HF) ear. This was high-pass filtered with an initial cutoff frequency of 7,000 Hz, which was adjusted using an adaptive procedure to find the maximum high-pass cutoff for 99.99% correct consonant recognition. Mean DSIRs spanned from 3,198-8,000 Hz to 4,668-8,000 Hz (i.e., mid-to-high frequencies were unnecessary), depending on low-frequency information in the LF ear. DSIRs narrowed (i.e., required less frequency information) with increasing low-frequency information in the LF ear. However, the mean DSIRs were not significantly affected by the signal processing except at the low-pass cutoff frequency of 250 Hz. The individual consonant analyses revealed that /ta/, /da/, /sa/, and /za/ required the smallest DSIR, while /ka/, /ga/, /fa/, and /va/ required the largest DSIRs. DSIRs also narrowed with increasing low-frequency information for the two signal processing conditions except for 250 vs. 1,000 Hz under the target-conflicting condition. The results suggest that consonant recognition is possible with large amounts of spectral information missing if complementary spectral information is integrated across ears. DSIR is consonant-specific and relatively consistent, regardless of signal processing. The results will help determine the minimum spectral range needed in one ear for consonant recognition if limited low spectral information is available in the opposite ear.

Effects of the intensified frequency and time ranges on consonant enhancement in bilateral cochlear implant and hearing aid users

A previous study demonstrated that consonant recognition improved significantly in normal hearing listeners when useful frequency and time ranges were intensified by 6 dB. The goal of this study was to determine whether bilateral cochlear implant (BCI) and bilateral hearing aid (BHA) users experienced similar enhancement on consonant recognition with these intensified spectral and temporal cues in noise. In total, 10 BCI and 10 BHA users participated in a recognition test using 14 consonants. For each consonant, we used the frequency and time ranges that are critical for its recognition (called “target frequency and time range”), identified from normal hearing listeners. Then, a signal processing tool called the articulation-index gram (AI-Gram) was utilized to add a 6 dB gain to target frequency and time ranges. Consonant recognition was monaurally and binaurally measured under two signal processing conditions, unprocessed and intensified target frequency and time ranges at +5 and +10 dB signal-to-noise ratio and in quiet conditions. We focused on three comparisons between the BCI and BHA groups: (1) AI-Gram benefits (i.e., before and after intensifying target ranges by 6 dB), (2) enhancement in binaural benefits (better performance with bilateral devices compared to the better ear alone) via the AI-Gram processing, and (3) reduction in binaural interferences (poorer performance with bilateral devices compared to the better ear alone) via the AI-Gram processing. The results showed that the mean AI-Gram benefit was significantly improved for the BCI (max 5.9%) and BHA (max 5.2%) groups. However, the mean binaural benefit was not improved after AI-Gram processing. Individual data showed wide ranges of the AI-Gram benefit (max −1 to 23%) and binaural benefit (max −7.6 to 13%) for both groups. Individual data also showed a decrease in binaural interference in both groups after AI-Gram processing. These results suggest that the frequency and time ranges, intensified by the AI-Gram processing, contribute to consonant enhancement for monaural and binaural listening and both BCI and BHA technologies. The intensified frequency and time ranges helped to reduce binaural interference but contributed less to the synergistic binaural benefit in consonant recognition for both groups.