The Influence of Age, Hearing, and Working Memory on the Speech Comprehension Benefit Derived from an Automatic Speech Recognition System

Zekveld, Adriana A.; Kramer, Sophia E.; Kessens, Judith M.; Vlaming, Marcel S. M. G.; Houtgast, Tammo

doi:10.1097/aud.0b013e3181987063

Cited by 24 publications

(25 citation statements)

References 32 publications

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“…While Besser et al (2012) and Zekveld, Kramer, et al (2011) found associations between age and different TRT versions in groups of NH individuals with age ranges of 18 to 78 and 46 to 73 years, respectively, Koelewijn et al (2012) and Zekveld et al (2007) did not find such associations in NH groups with comparable age ranges. Also, in a secondary analysis of combined data from the studies by Zekveld et al (2007Zekveld et al ( , 2008Zekveld et al ( , 2009, no association between TRT performance and age was found (r = .16, p > .1) in a large group of NH individuals at ages between 18 and 78 years ).…”

Section: Linguistic Processing Abilitymentioning

confidence: 55%

How Linguistic Closure and Verbal Working Memory Relate to Speech Recognition in Noise—A Review

Besser

Koelewijn

Zekveld

et al. 2013

Trends in Amplification

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132

160

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The ability to recognize masked speech, commonly measured with a speech reception threshold (SRT) test, is associated with cognitive processing abilities. Two cognitive factors frequently assessed in speech recognition research are the capacity of working memory (WM), measured by means of a reading span (Rspan) or listening span (Lspan) test, and the ability to read masked text (linguistic closure), measured by the text reception threshold (TRT). The current article provides a review of recent hearing research that examined the relationship of TRT and WM span to SRTs in various maskers. Furthermore, modality differences in WM capacity assessed with the Rspan compared to the Lspan test were examined and related to speech recognition abilities in an experimental study with young adults with normal hearing (NH). Span scores were strongly associated with each other, but were higher in the auditory modality. The results of the reviewed studies suggest that TRT and WM span are related to each other, but differ in their relationships with SRT performance. In NH adults of middle age or older, both TRT and Rspan were associated with SRTs in speech maskers, whereas TRT better predicted speech recognition in fluctuating nonspeech maskers. The associations with SRTs in steady-state noise were inconclusive for both measures. WM span was positively related to benefit from contextual information in speech recognition, but better TRTs related to less interference from unrelated cues. Data for individuals with impaired hearing are limited, but larger WM span seems to give a general advantage in various listening situations.

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Section: Linguistic Processing Abilitymentioning

confidence: 55%

How Linguistic Closure and Verbal Working Memory Relate to Speech Recognition in Noise—A Review

Besser

Koelewijn

Zekveld

et al. 2013

Trends in Amplification

Self Cite

132

160

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“…This benefith as been verified to apply also to hearing impaired persons by comparing young normal hearing persons, middle aged normal hearing persons and hearing impaired persons [39]. From that is wass een that age and hearing impairment reduce the benefite ff ects, buto verall ab enefiti nt he order of 2dBi so bserved for ASR performance of 74% which reduces to 0.5 to 1dBb enefit at ASR accuracyo f3 7%.…”

Section: Automatic Speech Recognition To Assist Speech Understandingmentioning

confidence: 95%

HearCom: Hearing in the Communication Society

Vlaming¹,

Kollmeier²,

Dreschler³

et al. 2011

Acta Acustica united with Acustica

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Agroup of 28 research partners joined the EU-funded project HearCom with the overall aim to improve hearing communication. One of the main achievements has been the provision of advanced hearing screening tests by telephone and Internet. Next to that it wasaimed to harmonize hearing diagnostic tests for European languages. Forthis the concept of an Auditory Profile wasdefined on which anumber of diagnostic hearing tests were developed in several languages. As hearing problems are also aresult of adverse acoustical circumstances such as for room acoustics and telecom systems, these effects have been studied, modelled and evaluated for hearing impaired persons. In the area of rehabilitation alarge scale comparison study wasperformed on signal enhancement techniques for hearing devices. Both objective and subjective benefits were found for specificlistening conditions in relation to achosen signal processing method. As modern technology may assist on hearing and communication it wasstudied howthe use of automatic speech transcription or the use of handheld communication devices may help people with hearing problems. It is shown that communication benefits can be obtained, butt hat the benefiti sl imited in practice as processing power of today'sh andheld devices is still insufficient. An overview is givenonthe HearCom portal with sections for screening diagnostics, hearing information for the public and professionals, and anew HearCompanion service that provides step-by-step support for the hearing rehabilitation process.

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“…Consequently, this implied that subjective rating is not a good measure of listening effort when speech intelligibility is high. In hindsight, it was not surprising that there was no correlation between subjectively rated listening effort and the objective measure of effort, since this also had been reported in other studies (Anderson Gosselin & Gagné, 2011;Fraser et al, 2010;Hicks & Tharpe, 2002;Larsby et al, 2005;Zekveld et al, 2010;Zekveld et al, 2009). As a result, subjectively rated listening effort was not used in study 3 or in study 4.…”

Section: Subjective Measure Of Listening Effortmentioning

confidence: 96%

“…Instead audiologists and hearing aid dispensers need inquire and ask the hearing aid user about their experienced listening effort. Many studies have involved a subjective measure of listening effort (Anderson Gosselin & Gagné, 2011;Fraser, Gagné, Alepins, & Dubois, 2010;Hicks & Tharpe, 2002;Larsby et al, 2005; N. Rönnberg et al, 2014b;Zekveld, Kramer, & Festen, 2010;Zekveld, Kramer, Kessens, Vlaming, & Houtgast, 2009). However, consistent for these studies is the lack of correlation between the objective and the subjective measure listening effort, regardless of experimental conditions or participants.…”

Section: Listening Effortmentioning

confidence: 99%

Assessing cognitive spare capacity as a measure of listening effort using the Auditory Inference Span Test

Rönnberg¹

2014

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Hearing loss has a negative effect on the daily life of 10-15% of the world’s population. One of the most common ways to treat a hearing loss is to fit hearing aids which increases audibility by providing amplification. Hearing aids thus improve speech reception in quiet, but listening in noise is nevertheless often difficult and stressful. Individual differences in cognitive capacity have been shown to be linked to differences in speech recognition performance in noise. An individual’s cognitive capacity is limited and is gradually consumed by increasing demands when listening in noise. Thus, fewer cognitive resources are left to interpret and process the information conveyed by the speech. Listening effort can therefore be explained by the amount of cognitive resources occupied with speech recognition. A well fitted hearing aid improves speech reception and leads to less listening effort, therefore an objective measure of listening effort would be a useful tool in the hearing aid fitting process. In this thesis the Auditory Inference Span Test (AIST) was developed to assess listening effort by measuring an individual’s cognitive spare capacity, the remaining cognitive resources available to interpret and encode linguistic content of incoming speech input while speech understanding takes place. The AIST is a dual-task hearing-innoise test, combining auditory and memory processing, and requires executive processing of speech at different memory load levels. The AIST was administered to young adults with normal hearing and older adults with hearing impairment. The aims were 1) to develop the AIST; 2) to investigate how different signal-to-noise ratios (SNRs) affect memory performance for perceived speech; 3) to explore if this performance would interact with cognitive capacity; 4) to test if different background noise types would interact differently with memory performance for young adults with normal hearing; and 5) to examine if these relationships would generalize to older adults with hearing impairment. The AIST is a new test of cognitive spare capacity which uses existing speech material that is available in several countries, and manipulates simultaneously cognitive load and SNR. Thus, the design of AIST pinpoints potential interactions between auditory and cognitive factors. The main finding of this thesis was the interaction between noise type and SNR showing that decreased SNR reduced cognitive spare capacity more in speech-like noise compared to speech-shaped noise, even though speech intelligibility levels were similar between noise types. This finding applied to young adults with normal hearing but there was a similar effect for older adults with hearing impairment with the addition of background noise compared to no background noise. Task demands, MLLs, interacted with cognitive capacity, thus, individuals with less cognitive capacity were more sensitive to increased cognitive load. However, MLLs did not interact with noise type or with SNR, which shows that different memory load levels were not affe...

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The Influence of Age, Hearing, and Working Memory on the Speech Comprehension Benefit Derived from an Automatic Speech Recognition System

Cited by 24 publications

References 32 publications

How Linguistic Closure and Verbal Working Memory Relate to Speech Recognition in Noise—A Review

How Linguistic Closure and Verbal Working Memory Relate to Speech Recognition in Noise—A Review

HearCom: Hearing in the Communication Society

Assessing cognitive spare capacity as a measure of listening effort using the Auditory Inference Span Test

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