Gap detection and speech recognition in noise in younger versus older listeners

2015 ◽  
Vol 137 (4) ◽  
pp. 2436-2436
Author(s):  
Susan M. DeMetropolis ◽  
Janet R. Schoepflin ◽  
Lawrence J. Raphael
Keyword(s):  
Speech Recognition ◽  
Gap Detection ◽  
Speech Recognition In Noise

scholarly journals The Relationship between Random Gap Detection and Hearing in Noise Test Performances

2018 ◽  
Vol 29 (10) ◽  
pp. 948-954 ◽  
Author(s):  
Paige Heeke ◽  
Andrew J. Vermiglio ◽  
Emery Bulla ◽  
Keerthana Velappan ◽  
Xiangming Fang
Keyword(s):  
Speech Recognition ◽  
Temporal Resolution ◽  
Time Interval ◽  
Gap Detection ◽  
Speech Understanding ◽  
Noise Performance ◽  
Hearing In Noise ◽  
Noise Test ◽  
Speech Recognition In Noise ◽  
The Relationship

AbstractTemporal acoustic cues are particularly important for speech understanding, and past research has inferred a relationship between temporal resolution and speech recognition in noise ability. A temporal resolution disorder is thought to affect speech understanding abilities because persons would not be able to accurately encode these frequency transitions, creating speech discrimination errors even in the presence of normal pure-tone hearing.The primary purpose was to investigate the relationship between temporal resolution as measured by the Random Gap Detection Test (RGDT) and speech recognition in noise performance as measured by the Hearing in Noise Test (HINT) in adults with normal audiometric thresholds. The second purpose was to examine the relationship between temporal resolution and spatial release from masking.The HINT and RGDT protocols were administered under headphones according to the guidelines specified by the developers. The HINT uses an adaptive protocol to determine the signal-to-noise ratio where the participant recognizes 50% of the sentences. For HINT conditions, the target sentences were presented at 0° and the steady-state speech-shaped noise and a four-talker babble (4TB) was presented at 0°, +90°, or −90° for noise front, noise right, and noise left conditions, respectively. The RGDT is used to evaluate temporal resolution by determining the smallest time interval between two matching stimuli that can be detected by the participant. The RGDT threshold is the shortest time interval where the participant detects a gap. Tonal (0.5, 1, 2, and 4 kHz) and click stimuli random gap subtests were presented at 60 dB HL. Tonal subtests were presented in a random order to minimize presentation order effects.Twenty-one young, native English-speaking participants with normal pure-tone thresholds (≤25 dB HL for 500–4000 Hz) participated in this study. The average age of the participants was 20.2 years (SD = 0.66).Spearman rho correlation coefficients were conducted using SPSS 22 (IBM Corp., Armonk, NY) to determine the relationships between HINT and RGDT thresholds and derived measures (spatial advantage and composite scores). Nonparametric testing was used because of the ordinal nature of RGDT data.Moderate negative correlations (p < 0.05) were found between eight RGDT and HINT threshold measures and a moderate positive correlation (p < 0.05) was found between RGDT click thresholds and HINT 4TB spatial advantage. This suggests that as temporal resolution abilities worsened, speech recognition in noise performance improved. These correlations were not statistically significant after the p value reflected the Bonferroni correction for multiple comparisons.The results of the present study imply that the RGDT and HINT use different temporal processes. Performance on the RGDT cannot be predicted from HINT thresholds or vice versa.

scholarly journals Comparison of Clinical and Traditional Gap Detection Tests

2015 ◽  
Vol 26 (06) ◽  
pp. 540-546 ◽  
Author(s):  
Eric Hoover ◽  
Lauren Pasquesi ◽  
Pamela Souza
Keyword(s):  
Speech Recognition ◽  
Temporal Resolution ◽  
Gap Detection ◽  
Clinical Tests ◽  
Younger Adults ◽  
Speech In Noise ◽  
Data Collection And Analysis ◽  
Highly Correlated ◽  
Speech Recognition In Noise ◽  
The Relationship

Background: Temporal resolution is important for speech recognition and may contribute to variability in speech recognition among patients. Clinical tests of temporal resolution are available, but it is not clear how closely results of those tests correspond to results of traditional temporal resolution tests. Purpose: The purpose of this study was to compare the Gaps-in-Noise (GIN) test to a traditional measure of gap detection. Study Sample: This study included older adults with hearing loss and younger adults with normal hearing. Data Collection and Analysis: Participants completed one practice and two test blocks of each gap detection test, and a measure of speech-in-noise recognition. Individual data were correlated to examine the relationship between the tests. Results: The GIN and traditional gap detection were significantly, but not highly correlated. The traditional gap detection test contributed to variance in speech recognition in noise, while the GIN did not. Conclusions: The brevity and ease of implementing the GIN in the clinic make it a viable test of temporal resolution. However, it differs from traditional measures in implementation, and as a result relies on different cognitive factors. The GIN thresholds should be interpreted carefully and not presumed to represent an approximation of traditional gap detection thresholds.

Analysis of Correlation between Cognitive Function and Speech Recognition in Noise

2010 ◽  
Vol 53 (4) ◽  
pp. 215 ◽  
Author(s):  
Seong Jun Song ◽  
Hyun Joon Shim ◽  
Chul Ho Park ◽  
Seong Hee Lee ◽  
Sang Won Yoon
Keyword(s):  
Speech Recognition ◽  
Cognitive Function ◽  
Speech Recognition In Noise

Working Memory Capacity May Influence Perceived Effort during Aided Speech Recognition in Noise

2012 ◽  
Vol 23 (08) ◽  
pp. 577-589 ◽  
Author(s):  
Mary Rudner ◽  
Thomas Lunner ◽  
Thomas Behrens ◽  
Elisabet Sundewall Thorén ◽  
Jerker Rönnberg
Keyword(s):  
Working Memory ◽  
Hearing Loss ◽  
Speech Recognition ◽  
Hearing Aid ◽  
Recognition Performance ◽  
Cognitive Capacity ◽  
Subjective Ratings ◽  
Perceived Effort ◽  
Noise Type ◽  
Speech Recognition In Noise

Background: Recently there has been interest in using subjective ratings as a measure of perceived effort during speech recognition in noise. Perceived effort may be an indicator of cognitive load. Thus, subjective effort ratings during speech recognition in noise may covary both with signal-to-noise ratio (SNR) and individual cognitive capacity. Purpose: The present study investigated the relation between subjective ratings of the effort involved in listening to speech in noise, speech recognition performance, and individual working memory (WM) capacity in hearing impaired hearing aid users. Research Design: In two experiments, participants with hearing loss rated perceived effort during aided speech perception in noise. Noise type and SNR were manipulated in both experiments, and in the second experiment hearing aid compression release settings were also manipulated. Speech recognition performance was measured along with WM capacity. Study Sample: There were 46 participants in all with bilateral mild to moderate sloping hearing loss. In Experiment 1 there were 16 native Danish speakers (eight women and eight men) with a mean age of 63.5 yr (SD = 12.1) and average pure tone (PT) threshold of 47. 6 dB (SD = 9.8). In Experiment 2 there were 30 native Swedish speakers (19 women and 11 men) with a mean age of 70 yr (SD = 7.8) and average PT threshold of 45.8 dB (SD = 6.6). Data Collection and Analysis: A visual analog scale (VAS) was used for effort rating in both experiments. In Experiment 1, effort was rated at individually adapted SNRs while in Experiment 2 it was rated at fixed SNRs. Speech recognition in noise performance was measured using adaptive procedures in both experiments with Dantale II sentences in Experiment 1 and Hagerman sentences in Experiment 2. WM capacity was measured using a letter-monitoring task in Experiment 1 and the reading span task in Experiment 2. Results: In both experiments, there was a strong and significant relation between rated effort and SNR that was independent of individual WM capacity, whereas the relation between rated effort and noise type seemed to be influenced by individual WM capacity. Experiment 2 showed that hearing aid compression setting influenced rated effort. Conclusions: Subjective ratings of the effort involved in speech recognition in noise reflect SNRs, and individual cognitive capacity seems to influence relative rating of noise type.

The Longitudinal Relationship Between Speech Recognition in Noise, Need for Recovery After Work, Job Demand, and Job Control Over a Period of 5 Years

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Lisette M. van Leeuwen ◽  
Thadé Goderie ◽  
Marieke F. van Wier ◽  
Birgit I. Lissenberg-Witte ◽  
Ulrike Lemke ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Job Control ◽  
Need For Recovery ◽  
Job Demand ◽  
Speech Recognition In Noise
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