Despite amplified speech, listeners with hearing loss often report more difficulties understanding speech in background noise compared to normalhearing listeners. Various factors such as deteriorated hearing sensitivity, age, suprathreshold temporal resolution, and reduced capacity of working memory and attention can attribute to their sentence-in-noise problems. The present study aims to determine a primary explanatory factor for sentence-in-noise recognition difficulties in adults with or without hearing loss.
Forty normal-hearing (NH) listeners (23-73 years) and thirty-four hearing-impaired (HI) listeners (24-80 years) participated for experimental testing. For both NH and HI group, the younger, middle-aged, older listeners were included. The sentence recognition score in noise was measured at 0 dB signal-to-noise ratio. The ability of temporal resolution was evaluated by gap detection performance using the Gaps-In-Noise test. Listeners’ short-term auditory working memory span was measured by forward and backward digit spans.
Overall, the HI listeners’ sentence-in-noise recognition, temporal resolution abilities, and digit forward and backward spans were poorer compared to the NH listeners. Both NH and HI listeners had a substantial variability in performance. For NH listeners, only the digit backward span explained a small proportion of the variance in their sentence-in-noise performance. For the HI listeners, all the performance was influenced by age, and their sentence-in-noise difficulties were associated with various factors such as high-frequency hearing sensitivity, suprathreshold temporal resolution abilities, and working memory span. For the HI listeners, the critical predictors of the sentence-in-noise performance were composite measures of peripheral hearing sensitivity and suprathreshold temporal resolution abilities.
The primary explanatory factors for the sentence-in-noise recognition performance differ between NH and HI listeners. Factors affecting sentence-in-noise recognition performance differed between NH and HI listeners. The working memory was the primary predictor of the sentence-in-noise scores for the NH individuals. In contrast, a combination of factors seemed to contributed to speech-in-noise understanding for the HI listeners. Given this, we must be careful not to generalize findings from the NH listeners to the HI individuals.
Background noise often leads to difficulties of speech communication for both normal-hearing (NH) and hearing-impaired (HI) listeners. Especially for the elderly with hearing impairment, speech understanding in noise has been a common problem of daily communication despite a use of modern digital hearing aids [
Since the previous studies on the age-related deficits in the speech-in-noise performance applied different methodologies, results varied depending on the criteria to recruit the listener groups, the type of test, and the degree of task demand. Given the discrepancies across findings, some researchers attempted to review earlier research to find any consistent evidence. For example, Humes and Young [
Although hearing loss is highly prevalent in the elderly, several previous studies have included older adults with audiometrically normal hearing, which may not represent performance of older adults with typical presbycusis. When determining age-related declines in the earlier studies, a lack of inclusion of middle-aged listeners was often observed. Also, the various types of speech and cognitive tests have been conducted on the sensory-cognitive interactions. Although this aims to observe what can be the best test, it may be hard to implement various laboratory tests in a time-efficient way to examine sources of highly individual factors in speech-innoise difficulties. These limitations above have led further research on the factors contributing to speech-in-noise performance for both NH and HI listeners with a wide range of age (younger, middle-aged, and older listeners). Considering the practical importance of the results, this study executed clinically applicable tests to measure listeners’ sentence-in-noise recognition, short-term auditory working memory span, and temporal resolution abilities. The present study attempted to explore factors predicting sentence-in-noise recognition performance with separate analysis of NH and HI listeners.
Forty NH listeners (13 males, 27 females) and 34 HI listeners (20 males, 14 females) participated for experimental testing. Among 40 NH listeners, 18 listeners were younger NH (YNH; mean age=25 years, age range=23-29 years), 11 listeners were middle-aged NH (MNH; mean age=52 years, age range=42-58 years), and 11 listeners were the elderly NH (ENH; mean age=68 years, age range=63-73 years). Considering the distributions of hearing thresholds as a function of age [
Among 34 HI listeners, 6 listeners were younger HI (YHI; mean age=32 years, age range=24-35 years), 12 listeners were middle-aged HI (MHI; mean age=51 years, age range=40-59 years), and 16 listeners were EHI (mean age=69 years, age range=60-80 years). All the HI listeners had symmetric mild-to-moderate hearing loss without any middle-ear pathology, and their individual hearing thresholds were greater than 30 dB HL at 2,000 Hz and greater than 35 dB HL at 4,000 Hz. The mean hearing threshold of test ear for the HI group was 20, 25, 32, 43, 58, and 71 dB HL in the frequencies from 250 Hz to 8,000 Hz at the octave scales. The mean WRS in quiet for the HI listeners was 76% (range= 36-96%).
The current study conducted three types of evaluations with clinical applicability: the sentence-in-noise recognition test, the gap detection test to evaluate auditory temporal resolution, and the digit forward and backward span test to measure short-term working memory.
For the measure of sentence-in-noise recognition, the sentences of the Korean Standard Sentence Lists for Adults [
For all measures described above, each subject was seated in a double-walled sound treated booth. All the stimuli were presented at each listener’s most comfortable listening level, and were delivered through a diagnostic audiometer (GSI 61; Grason-Stadler, Eden Prairie, MN, USA) and a loudspeaker located at 0 degrees azimuth nearly 1 meter. The root-meansquared value of each stimulus and background was controlled via Adobe Audition® (version 3.0; Adobe Systems Incorporated, San Jose, CA, USA) to equalize the overall intensity. The output level was periodically checked by the experimenter during testing.
Based on the mean WRS in quiet for the NH and HI participants (NH=95%, HI=76%), it would be not surprising to examine the poorer performance of HI listener than that of NH listeners. To examine whether sentence-in-noise recognition, temporal resolution, and short-term working memory would be affected by age for both NH and HI listeners, the current study executed one-way analysis of variance analyses for the NH and HI listeners separately, with an independent variable of age. The dependent variables were sentence-innoise recognition, GIN percent-correct score, and digit forward/backward span. The multiple post-hoc comparisons were conducted if needed. The relations of the sentence-in-noise recognition with short-term working memory and temporal resolution abilities were examined by the Pearson correlation analyses. To examine best predictors of the sentence-in-noise recognition scores, the stepwise multiple regressions estimated contribution of listeners’ age, high-frequency hearing sensitivity [puretone threshold average (PTA) across 1, 2, 4 kHz], digit forward/backward span, and the GIN score. All the analyses were conducted using SPSS version 19.0 (SPSS Inc., Chicago, IL, USA). A significance level of
The panels of
The mean percent-correct score of GIN was 70.9%, 59.0%, and 37.2% for the YNH, MNH, and ENH listeners, respectively. Their overall score of GIN was 58.4% across NH listeners (±15.8, range=22.5-77.5%). The results of multiple comparisons showed that the YHI listeners poorly detected gaps than MHI listeners who were poorer than YHI (
The panels of the
Since the age range was large for NH (23 to 73 years of age) and HI listeners (24 to 80 years of age) and each group showed a large individual variance on the SRS, the individual SRS in noise was plotted as a function of participant age for the NH (
Given a greater variability in the sentence-in-noise recognition score, Pearson correlation analyses were also executed to examine whether the listener’s sentence-in-noise recognition would be related to their short-term working memory, temporal resolution abilities, and other demographic information. The correlation analyses were computed for NH and HI listeners separately. For the NH individuals, the SRS in noise showed a significant (
Based on the differential correlation results for sentencein-noise performance between groups, the stepwise multiple regression analyses were administered to determine best predictors accounting for variances of the sentence-in-noise difficulties for NH and HI listeners separately. The entered independent variables were age, high-frequency hearing sensitivity (PTA across 1, 2, 4 kHz), digit forward/backward span, and GIN percent-correct score, with a dependent variable of the sentence-in-noise recognition score.
The present study aimed to determine the primary predictive variables for the sentence-in-noise performance of NH and HI listeners. Not surprisingly, the results revealed poorer performance of the HI listeners on the sentence-in-noise recognition, auditory working memory, and auditory temporal resolution compared to NH listeners, supporting the previous findings on the poorer performance of HI listeners [
The current study measured the digit forward and backward spans, being known to have different memory processes [
For the HI listeners, age, high-frequency hearing sensitivity, digit forward span, and GIN score were all related to their speech-in-noise performance. Results revealed a widely varying ability in sentence-in-noise recognition, gap detection in noise, and working memory performances for HI individuals. The large variance in the sentence-in-noise recognition difficulties was accounted for by declines in their high-frequency hearing sensitivity as well as suprathreshold temporal resolution. This is because, especially for the listener with deteriorated hearing sensitivity, it requires more work and efforts of the bottom-up systems to encode the target speech signal while ignoring noise and then relate the decoded information to stored knowledge. The current finding supports that the peripheral sensitivity and the auditory temporal resolution are important predictive variables of the sentence-in-noise problem for the HI listeners, consistent with some previous studies [
The present study has several limitations including a small sample size for each age group as well as use of a few simpletask evaluations. The exact contribution of working memory to the large individual differences in the speech-in-noise perception remains still unclear especially for the challenging listening situations. Taken this, future studies need to determine the factors predicting speech-in-noise performance using more complex stimuli and task.
In conclusion, the current study found differential predictive variables of the sentence-in-noise recognition abilities for NH and HI listeners. For the NH listeners, the ability of complex cognitive processing better explained their sentencein-noise recognition difficulties. For the HI listeners, loss of peripheral sensitivity and auditory temporal resolution could be the sources of speech-in-noise difficulties. This suggests that the primary explanatory factors for the sentence-in-noise recognition performance differ between NH and HI listeners. Considering this, we must be careful not to generalize findings from the NH individuals to the HI population.
This study was supported by the Ministry of Education of the Republic of Korea and National Research Foundation of Korea (NRF- 2016S1A5A8020353).
Mean hearing thresholds for YNH, MNH, ENH and YHI, MHI, EHI. The NH and HI average means the mean hearing thresholds across 40 NH listeners and 34 HI listeners, respectively (Error bars: standard deviation). NH: normal-hearing, HI: hearing-impaired, YNH: younger NH, MNH: middle-aged NH, ENH: elderly NH, YHI: younger HI, MHI: middle-aged HI, EHI: elderly HI.
Mean percent-correct score of SRS and GIN. A: NH listeners. B: HI listeners. SRS: sentence recognition score, GIN: Gapsin-Noise, NH: normal-hearing, HI: hearing-impaired, YNH: younger NH, MNH: middle-aged NH, ENH: elderly NH, YHI: younger HI, MHI: middle-aged HI, EHI: elderly HI.
Mean span of digit forward and digit backward span. A: NH listeners. B: HI listeners. NH: normal-hearing, HI: hearing-impaired, YNH: younger NH, MNH: middle-aged NH, ENH: elderly NH, YHI: younger HI, MHI: middle-aged HI, EHI: elderly HI.
Scatterplot of SRS in noise as a function of participant age. A: NH listeners. B: HI listeners. NH: normal-hearing, HI: hearing-impaired, SRS: sentence recognition score.
Summary of stepwise multiple regression analysis for the sentence-in-noise recognition score (only significant variables entered into the model are shown)
Variable | Coefficient | Adjusted R2 |
---|---|---|
NH group | ||
Digit backward span | 0.386 (13.88) |
0.127 |
HI group | ||
GIN score | 0.588 (12.20) |
0.326 |
GIN score+PTA across 1, 2, 4 kHz | 0.655 (11.58) |
0.392 |
Coefficient standard error in parentheses.
significant at 0.05 level,
significant at 0.01 level.
GIN: Gaps-In-Noise test, PTA: puretone threshold average, NH: normal-hearing, HI: hearing-impaired