scholarly journals Age-Related Differences in Lexical Access Relate to Speech Recognition in Noise

2016 ◽  
Vol 7 ◽  
Author(s):  
Rebecca Carroll ◽  
Anna Warzybok ◽  
Birger Kollmeier ◽  
Esther Ruigendijk
Keyword(s):  
Speech Recognition ◽  
Lexical Access ◽  
Age Related ◽  
Speech Recognition In Noise

The influence of lexical-access ability and vocabulary knowledge on measures of speech recognition in noise

2015 ◽  
Vol 55 (3) ◽  
pp. 157-167 ◽  
Author(s):  
Marre W. Kaandorp ◽  
Annette M.B. De Groot ◽  
Joost M. Festen ◽  
Cas Smits ◽  
S. Theo Goverts
Keyword(s):  
Speech Recognition ◽  
Lexical Access ◽  
Vocabulary Knowledge ◽  
Speech Recognition In Noise

The Effects of Aging on Speech Perception in Noise: Comparison between Normal-Hearing and Cochlear-Implant Listeners

2014 ◽  
Vol 25 (07) ◽  
pp. 656-665 ◽  
Author(s):  
Su-Hyun Jin ◽  
Chang Liu ◽  
Douglas P. Sladen
Keyword(s):  
Speech Recognition ◽  
Aging Effect ◽  
Speech Understanding ◽  
Detection Thresholds ◽  
Speech Perception In Noise ◽  
Sentence Recognition ◽  
Hearing Status ◽  
Age Related ◽  
Effects Of Aging ◽  
Speech Recognition In Noise

Background: Speech understanding in noise is comparatively more problematic for older listeners with and without hearing loss, and age-related changes in temporal resolution might be associated with reduced speech recognition in complex noise. Purpose: The purpose of this study was to investigate the effects of aging on temporal processing and speech perception in noise for normal-hearing (NH) and cochlear-implant (CI) listeners. Research Design: All participants completed three experimental procedures: (1) amplitude modulation (AM) detection thresholds, (2) sentence recognition in quiet, and (3) speech recognition in steady or modulating noise. Study Sample: Four listener groups participated in the study: 11 younger (≤ 30 yr old, YNH) listeners and 12 older (> 60 yr old, ONH) listeners with NH and 7 younger (< 55 yr old, YCI) and 6 older (> 60 yr old, OCI) CI users. CI listeners have been wearing their device either monaurally or binaurally at least 1 yr. Data collection and Analysis: For speech recognition testing, there were eight listening conditions in noise (4 modulation frequencies × 2 signal-to-noise ratios) and one in quiet for each listener. For modulation detection testing, a broadband noise with a duration of 500 msec served as the stimuli at three temporal modulation frequencies of 2, 4, and 8 Hz, which were used to modulate the noise in the speech recognition experiment. We measured AM detection thresholds using a two-interval, two-alternative, forced-choice adaptive procedure. We conducted a series of analysis of variance tests to examine the effect of aging on each test result and measured the correlation coefficient between speech recognition in noise and modulation detection thresholds. Results: Although older NH and CI listeners performed similar to the younger listeners with the same hearing status for sentence recognition in quiet, there was a significant aging effect on speech recognition in noise. Regardless of modulation frequency and signal-to-noise ratio, speech recognition scores of the older listeners were poorer than those of the younger listeners when hearing status was matched. We also found a significant effect of aging on AM detection at each modulating frequency and a strong correlation between speech recognition in modulating noise and AM detection thresholds at 2 and 4 Hz. Conclusions: Regardless of differences in hearing status, the degree and pattern of aging effect on auditory processing of the NH listener groups were similar to those of the CI listener groups. This result suggests that age-related declines in speech understanding are likely multifactorial, including peripheral and central factors. Although the age cutoff of the current older age group was 10 yr less than in previous studies (Dubno et al, 2002; Lin et al, 2011), we still found the age-related differences on two auditory tasks. This study extends the knowledge of age-related auditory perception difficulties to CI listeners.

scholarly journals Lexical-Access Ability and Cognitive Predictors of Speech Recognition in Noise in Adult Cochlear Implant Users

2017 ◽  
Vol 21 ◽  
pp. 233121651774388 ◽  
Author(s):  
Marre W. Kaandorp ◽  
Cas Smits ◽  
Paul Merkus ◽  
Joost M. Festen ◽  
S. Theo Goverts
Keyword(s):  
Speech Recognition ◽  
Cochlear Implant ◽  
Lexical Access ◽  
Cognitive Predictors ◽  
Speech Recognition In Noise

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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