Effects of Hearing Loss and Spectral Shaping on Identification and Neural Response Patterns of Stop-Consonant Stimuli in Young Adults

Harkrider, Ashley W.; Plyler, Patrick N.; Hedrick, Mark

doi:10.1097/aud.0b013e31818f359f

Cited by 19 publications

(37 citation statements)

References 34 publications

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“…The authors proposed that the lack of significant hearing aid benefit might be due to factors beyond simple audibility, such as central auditory deficits or poorer cognitive ability. Harkrider, Plyler, and Hedrick (2009) reported that hearing loss, independent of aging, adversely affected underlying neural spectral cues and resulted in deficient consonant identification among hearing-impaired individuals. In a similar vein, they stated that compensation by improving audibility does not reduce the deleterious effects of hearing loss on consonant identification.…”

Section: Consonant Identificationmentioning

confidence: 99%

Time is of the essence in speech perception! : Get it fast, or think about it

Moradi¹

2014

Studies From the Swedish Institute for Disability Research

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Speech recognition occurs when attending to speech stimuli in auditory, visual, or audiovisual modalities under optimum (e.g., in silence) or degraded listening conditions (i.e., in background noise or in individuals with hearing impairment). The present thesis contains details of the first study to show how background noise (steady-state white noise) delayed the identification of different types of speech stimuli (consonants, words, and final words in sentence) in auditory and audiovisual modalities by calculating the isolation points (IPs, the shortest time from the onset of an speech stimulus required for correct identification of that speech stimulus). The cognitive demands of perceiving speech stimuli under each type of listening condition (silence vs. noise) were also tested by measuring the correlations between IPs of each type of speech stimulus (in each type of listening condition) and tests of working memory capacity (i.e., the reading span test, Rönnberg, Arlinger, Lyxell, & Kinnefors, 1989) and attentional capacity (i.e., the Paced Auditory Serial Attention Gronwall, 1977). In addition, the speechreading of words in both silent and noisy (babble background noise and steady-state white noise) conditions was also investigated in above-average speechreaders. The present thesis also compared elderly hearing-aid (EHA) users and elderly normal-hearing (ENH) individuals, in terms of IPs and accuracy in the identification of different types of speech stimuli in silence. Furthermore, the extent to which the identification of auditory speech stimuli was cognitively demanding (for both EHA users and ENH individuals) was investigated by measuring the correlations between IPs and accuracies of different types of speech stimuli and working memory capacity.The results showed that background noise resulted in later IPs (in the auditory and audiovisual modalities) and reduced accuracy (in the auditory, visual, and audiovisual modalities). In visual speech recognition (speechreading), the adverse effect of noise on accuracy was dependent on the type of background noise: babble background noise reduced accuracy but the steady-state white noise did not. In addition, the audiovisual presentation of speech stimuli, relative to auditory presentation, resulted in earlier IPs and more accurate identification of speech stimuli in both silence and noise. In the silent condition, the IPs for perceiving different types of auditory and audiovisual speech stimuli were not correlated with performance on the tests of working memory and attention. In the noise condition, the IPs of consonants and words in the auditory-only condition were significantly correlated with tests for measuring explicit cognitive resources. Furthermore, there was a significant correlation between the results on a test of speech-in-noise performance (the HINT, Hällgren, Larsby, & Arlinger, 2006) and the results on tests of working memory (the reading span test, Rönnberg et al., 1989) and attention (PASAT, Gronwall, 1977). A secondary finding was that ...

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Section: Consonant Identificationmentioning

confidence: 99%

Time is of the essence in speech perception! : Get it fast, or think about it

Moradi¹

2014

Studies From the Swedish Institute for Disability Research

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“…The sum was divided over the total number of transition steps for the continuum. Additionally, phonetic boundary locations associated with 50% points were computed for every psychometric function (e.g., Harkrider et al 2009). The 50% points were defined by converting the percent unshaped /b/ scores to scores and using linear least-squares fit to get an estimation of the 50% point which is the phonemic boundary of this phoneme.…”

Section: Methods Of Data Analysis Behavioral Data Analysismentioning

confidence: 99%

“…Spectral shaping reduced gain for low frequencies; and increased gain for mid and high frequencies, which is the frequency region of F2 transitions. Spectral shaping was determined by measuring 1/3 octave root mean square (RMS) levels in a Zwislocki coupler via a sound level meter with slow averaging and C-weighting (Harkrider et al 2009). …”

Section: Stimulimentioning

confidence: 99%

“…80 dB SPL) to ensure that potential behavioral or electrophysiological response differences are due to shaping not because of differences in overall presentation levels (Harkrider et al 2009). However, more amplification was introduced to the frequencies of F2 formant transition in relation to the rest of the signal in the shaped condition, meanwhile equal amplification was delivered to all frequencies in the unshaped condition.…”

Section: Stimulimentioning

confidence: 99%

“…Vander Werff and Burns (2011) concluded that this impaired temporal coding found in older adults seems to be attributed to the decrement in neural synchrony caused by aging (e.g. Frisina & Frisina 1997;Harkrider et al 2005;Harkrider, Plyler & Hedrick 2009). …”

Section: Chapter 1 Introductionmentioning

confidence: 99%

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