Ease Of Language Understanding Research Articles

Recognition of Emotional Prosody in Mandarin-Speaking Children: Effects of Age, Noise, and Working Memory.

Age, babble noise, and working memory have been found to affect the recognition of emotional prosody based on non-tonal languages, yet little is known about how exactly they influence tone-language-speaking children's recognition of emotional prosody. In virtue of the tectonic theory of Stroop effects and the Ease of Language Understanding (ELU) model, this study aimed to explore the effects of age, babble noise, and working memory on Mandarin-speaking children's understanding of emotional prosody. Sixty Mandarin-speaking children aged three to eight years and 20 Mandarin-speaking adults participated in this study. They were asked to recognize the happy or sad prosody of short sentences with different semantics (negative, neutral, or positive) produced by a male speaker. The results revealed that the prosody-semantics congruity played a bigger role in children than in adults for accurate recognition of emotional prosody in quiet, but a less important role in children compared with adults in noise. Furthermore, concerning the recognition accuracy of emotional prosody, the effect of working memory on children was trivial despite the listening conditions. But for adults, it was very prominent in babble noise. The findings partially supported the tectonic theory of Stroop effects which highlights the perceptual enhancement generated by cross-channel congruity, and the ELU model which underlines the importance of working memory in speech processing in noise. These results suggested that the development of emotional prosody recognition is a complex process influenced by the interplay among age, background noise, and working memory.

A structural equation mediation model captures the predictions amongst the parameters of the ease of language understanding model.

The aim of the present study was to assess the validity of the Ease of Language Understanding (ELU) model through a statistical assessment of the relationships among its main parameters: processing speed, phonology, working memory (WM), and dB Speech Noise Ratio (SNR) for a given Speech Recognition Threshold (SRT) in a sample of hearing aid users from the n200 database. Hearing aid users were assessed on several hearing and cognitive tests. Latent Structural Equation Models (SEMs) were applied to investigate the relationship between the main parameters of the ELU model while controlling for age and PTA. Several competing models were assessed. Analyses indicated that a mediating SEM was the best fit for the data. The results showed that (i) phonology independently predicted speech recognition threshold in both easy and adverse listening conditions and (ii) WM was not predictive of dB SNR for a given SRT in the easier listening conditions (iii) processing speed was predictive of dB SNR for a given SRT mediated via WM in the more adverse conditions. The results were in line with the predictions of the ELU model: (i) phonology contributed to dB SNR for a given SRT in all listening conditions, (ii) WM is only invoked when listening conditions are adverse, (iii) better WM capacity aids the understanding of what has been said in adverse listening conditions, and finally (iv) the results highlight the importance and optimization of processing speed in conditions when listening conditions are adverse and WM is activated.

The cognitive hearing science perspective on perceiving, understanding, and remembering language: The ELU model.

The review gives an introductory description of the successive development of data patterns based on comparisons between hearing-impaired and normal hearing participants’ speech understanding skills, later prompting the formulation of the Ease of Language Understanding (ELU) model. The model builds on the interaction between an input buffer (RAMBPHO, Rapid Automatic Multimodal Binding of PHOnology) and three memory systems: working memory (WM), semantic long-term memory (SLTM), and episodic long-term memory (ELTM). RAMBPHO input may either match or mismatch multimodal SLTM representations. Given a match, lexical access is accomplished rapidly and implicitly within approximately 100–400 ms. Given a mismatch, the prediction is that WM is engaged explicitly to repair the meaning of the input – in interaction with SLTM and ELTM – taking seconds rather than milliseconds. The multimodal and multilevel nature of representations held in WM and LTM are at the center of the review, being integral parts of the prediction and postdiction components of language understanding. Finally, some hypotheses based on a selective use-disuse of memory systems mechanism are described in relation to mild cognitive impairment and dementia. Alternative speech perception and WM models are evaluated, and recent developments and generalisations, ELU model tests, and boundaries are discussed.

Working-Memory, Alpha-Theta Oscillations and Musical Training in Older Age: Research Perspectives for Speech-on-speech Perception.

During the normal course of aging, perception of speech-on-speech or “cocktail party” speech and use of working memory (WM) abilities change. Musical training, which is a complex activity that integrates multiple sensory modalities and higher-order cognitive functions, reportedly benefits both WM performance and speech-on-speech perception in older adults. This mini-review explores the relationship between musical training, WM and speech-on-speech perception in older age (> 65 years) through the lens of the Ease of Language Understanding (ELU) model. Linking neural-oscillation literature associating speech-on-speech perception and WM with alpha-theta oscillatory activity, we propose that two stages of speech-on-speech processing in the ELU are underpinned by WM-related alpha-theta oscillatory activity, and that effects of musical training on speech-on-speech perception may be reflected in these frequency bands among older adults.

Cognitive Hearing Science: Three Memory Systems, Two Approaches, and the Ease of Language Understanding Model.

Purpose The purpose of this study was to conceptualize the subtle balancing act between language input and prediction (cognitive priming of future input) to achieve understanding of communicated content. When understanding fails, reconstructive postdiction is initiated. Three memory systems play important roles: working memory (WM), episodic long-term memory (ELTM), and semantic long-term memory (SLTM). The axiom of the Ease of Language Understanding (ELU) model is that explicit WM resources are invoked by a mismatch between language input-in the form of rapid automatic multimodal binding of phonology-and multimodal phonological and lexical representations in SLTM. However, if there is a match between rapid automatic multimodal binding of phonology output and SLTM/ELTM representations, language processing continues rapidly and implicitly. Method and Results In our first ELU approach, we focused on experimental manipulations of signal processing in hearing aids and background noise to cause a mismatch with LTM representations; both resulted in increased dependence on WM. Our second-and main approach relevant for this review article-focuses on the relative effects of age-related hearing loss on the three memory systems. According to the ELU, WM is predicted to be frequently occupied with reconstruction of what was actually heard, resulting in a relative disuse of phonological/lexical representations in the ELTM and SLTM systems. The prediction and results do not depend on test modality per se but rather on the particular memory system. This will be further discussed. Conclusions Related to the literature on ELTM decline as precursors of dementia and the fact that the risk for Alzheimer's disease increases substantially over time due to hearing loss, there is a possibility that lowered ELTM due to hearing loss and disuse may be part of the causal chain linking hearing loss and dementia. Future ELU research will focus on this possibility.

African Languages for Participatory Democracy and Sustainable Socioeconomic Development : The Case of Swahili in Tanzania

That language plays a pivotal and integral role in making political processes participatory and inclusive, and socioeconomic development sustainable has been commonsensically presumed to be a well-established fact. Language is not simply a means of mutual communication, but also a potent tool for social inclusion and exclusion, resulting in having both a positive and negative social impact. In this sense the use of African languages in all social domains for making sure of the concretization of inclusive political participation and representation as well as sustainable socioeconomic development. Despite being considered to be an exemplary country that has pursued an active endoglosic language policy, Tanzania has an uphill task in facilitating participatory democracy and sustainable socioeconomic development by virtue of the ease of language understanding with which people can make them understood in everyday life. What is imperatively needed in making participatory democracy and sustainable socioeconomic development possible and feasible is a strong political will and its implementation. In tandem with a strong political will and its implementation in the conduct of national affairs, a ceaseless and concerted effort needs to be made with a view to capacitating Swahili to make a meaningful contribution to participatory democracy and sustainable socioeconomic development. Furthermore, corpus planning that refers to an institutional effort for creating standards for Swahili has to be done.

Auditory, Cognitive, and Linguistic Factors Predict Speech Recognition in Adverse Listening Conditions for Children With Hearing Loss.

Objectives: Children with hearing loss listen and learn in environments with noise and reverberation, but perform more poorly in noise and reverberation than children with normal hearing. Even with amplification, individual differences in speech recognition are observed among children with hearing loss. Few studies have examined the factors that support speech understanding in noise and reverberation for this population. This study applied the theoretical framework of the Ease of Language Understanding (ELU) model to examine the influence of auditory, cognitive, and linguistic factors on speech recognition in noise and reverberation for children with hearing loss.Design: Fifty-six children with hearing loss and 50 age-matched children with normal hearing who were 7–10 years-old participated in this study. Aided sentence recognition was measured using an adaptive procedure to determine the signal-to-noise ratio for 50% correct (SNR50) recognition in steady-state speech-shaped noise. SNR50 was also measured with noise plus a simulation of 600 ms reverberation time. Receptive vocabulary, auditory attention, and visuospatial working memory were measured. Aided speech audibility indexed by the Speech Intelligibility Index was measured through the hearing aids of children with hearing loss.Results: Children with hearing loss had poorer aided speech recognition in noise and reverberation than children with typical hearing. Children with higher receptive vocabulary and working memory skills had better speech recognition in noise and noise plus reverberation than peers with poorer skills in these domains. Children with hearing loss with higher aided audibility had better speech recognition in noise and reverberation than peers with poorer audibility. Better audibility was also associated with stronger language skills.Conclusions: Children with hearing loss are at considerable risk for poor speech understanding in noise and in conditions with noise and reverberation. Consistent with the predictions of the ELU model, children with stronger vocabulary and working memory abilities performed better than peers with poorer skills in these domains. Better aided speech audibility was associated with better recognition in noise and noise plus reverberation conditions for children with hearing loss. Speech audibility had direct effects on speech recognition in noise and reverberation and cumulative effects on speech recognition in noise through a positive association with language development over time.

Speech Processing Difficulties in Attention Deficit Hyperactivity Disorder.

The large body of research that forms the ease of language understanding (ELU) model emphasizes the important contribution of cognitive processes when listening to speech in adverse conditions; however, speech-in-noise (SIN) processing is yet to be thoroughly tested in populations with cognitive deficits. The purpose of the current study was to contribute to the field in this regard by assessing SIN performance in a sample of adolescents with attention deficit hyperactivity disorder (ADHD) and comparing results with age-matched controls. This population was chosen because core symptoms of ADHD include developmental deficits in cognitive control and working memory capacity and because these top-down processes are thought to reach maturity during adolescence in individuals with typical development. The study utilized natural language sentence materials under experimental conditions that manipulated the dependency on cognitive mechanisms in varying degrees. In addition, participants were tested on cognitive capacity measures of complex working memory-span, selective attention, and lexical access. Primary findings were in support of the ELU-model. Age was shown to significantly covary with SIN performance, and after controlling for age, ADHD participants demonstrated greater difficulty than controls with the experimental manipulations. In addition, overall SIN performance was strongly predicted by individual differences in cognitive capacity. Taken together, the results highlight the general disadvantage persons with deficient cognitive capacity have when attending to speech in typically noisy listening environments. Furthermore, the consistently poorer performance observed in the ADHD group suggests that auditory processing tasks designed to tax attention and working memory capacity may prove to be beneficial clinical instruments when diagnosing ADHD.

High-Variability Sentence Recognition in Long-Term Cochlear Implant Users: Associations With Rapid Phonological Coding and Executive Functioning.

The objective of the present study was to determine whether long-term cochlear implant (CI) users would show greater variability in rapid phonological coding skills and greater reliance on slow-effortful compensatory executive functioning (EF) skills than normal-hearing (NH) peers on perceptually challenging high-variability sentence recognition tasks. We tested the following three hypotheses: First, CI users would show lower scores on sentence recognition tests involving high speaker and dialect variability than NH controls, even after adjusting for poorer sentence recognition performance by CI users on a conventional low-variability sentence recognition test. Second, variability in fast-automatic rapid phonological coding skills would be more strongly associated with performance on high-variability sentence recognition tasks for CI users than NH peers. Third, compensatory EF strategies would be more strongly associated with performance on high-variability sentence recognition tasks for CI users than NH peers. Two groups of children, adolescents, and young adults aged 9 to 29 years participated in this cross-sectional study: 49 long-term CI users (≥7 years) and 56 NH controls. All participants were tested on measures of rapid phonological coding (Children's Test of Nonword Repetition), conventional sentence recognition (Harvard Sentence Recognition Test), and two novel high-variability sentence recognition tests that varied the indexical attributes of speech (Perceptually Robust English Sentence Test Open-set test and Perceptually Robust English Sentence Test Open-set test-Foreign Accented English test). Measures of EF included verbal working memory (WM), spatial WM, controlled cognitive fluency, and inhibition concentration. CI users scored lower than NH peers on both tests of high-variability sentence recognition even after conventional sentence recognition skills were statistically controlled. Correlations between rapid phonological coding and high-variability sentence recognition scores were stronger for the CI sample than for the NH sample even after basic sentence perception skills were statistically controlled. Scatterplots revealed different ranges and slopes for the relationship between rapid phonological coding skills and high-variability sentence recognition performance in CI users and NH peers. Although no statistically significant correlations between EF strategies and sentence recognition were found in the CI or NH sample after use of a conservative Bonferroni-type correction, medium to high effect sizes for correlations between verbal WM and sentence recognition in the CI sample suggest that further investigation of this relationship is needed. These findings provide converging support for neurocognitive models that propose two channels for speech-language processing: a fast-automatic channel that predominates whenever possible and a compensatory slow-effortful processing channel that is activated during perceptually-challenging speech processing tasks that are not fully managed by the fast-automatic channel (ease of language understanding, framework for understanding effortful listening, and auditory neurocognitive model). CI users showed significantly poorer performance on measures of high-variability sentence recognition than NH peers, even after simple sentence recognition was controlled. Nonword repetition scores showed almost no overlap between CI and NH samples, and correlations between nonword repetition scores and high-variability sentence recognition were consistent with greater reliance on engagement of fast-automatic phonological coding for high-variability sentence recognition in the CI sample than in the NH sample. Further investigation of the verbal WM-sentence recognition relationship in CI users is recommended. Assessment of fast-automatic phonological processing and slow-effortful EF skills may provide a better understanding of speech perception outcomes in CI users in the clinical setting.

Children's Speech Perception in Noise: Evidence for Dissociation From Language and Working Memory

We examined the association between speech perception in noise (SPIN), language abilities, and working memory (WM) capacity in school-age children. Existing studies supporting the Ease of Language Understanding (ELU) model suggest that WM capacity plays a significant role in adverse listening situations. Eighty-three children between the ages of 7 to 11 years participated. The sample represented a continuum of individual differences in attention, memory, and language abilities. All children had normal-range hearing and normal-range nonverbal IQ. Children completed the Bamford-Kowal-Bench Speech-in-Noise Test (BKB-SIN; Etymotic Research, 2005), a selective auditory attention task, and multiple measures of language and WM. Partial correlations (controlling for age) showed significant positive associations among attention, memory, and language measures. However, BKB-SIN did not correlate significantly with any of the other measures. Principal component analysis revealed a distinct WM factor and a distinct language factor. BKB-SIN loaded robustly as a distinct 3rd factor with minimal secondary loading from sentence recall and short-term memory. Nonverbal IQ loaded as a 4th factor. Results did not support an association between SPIN and WM capacity in children. However, in this study, a single SPIN measure was used. Future studies using multiple SPIN measures are warranted. Evidence from the current study supports the use of BKB-SIN as clinical measure of speech perception ability because it was not influenced by variation in children's language and memory abilities. More large-scale studies in school-age children are needed to replicate the proposed role played by WM in adverse listening situations.

Hearing impairment, cognition and speech understanding: exploratory factor analyses of a comprehensive test battery for a group of hearing aid users, the n200 study

Objective: The aims of the current n200 study were to assess the structural relations between three classes of test variables (i.e. HEARING, COGNITION and aided speech-in-noise OUTCOMES) and to describe the theoretical implications of these relations for the Ease of Language Understanding (ELU) model. Study sample: Participants were 200 hard-of-hearing hearing-aid users, with a mean age of 60.8 years. Forty-three percent were females and the mean hearing threshold in the better ear was 37.4 dB HL. Design: LEVEL1 factor analyses extracted one factor per test and/or cognitive function based on a priori conceptualizations. The more abstract LEVEL 2 factor analyses were performed separately for the three classes of test variables. Results: The HEARING test variables resulted in two LEVEL 2 factors, which we labelled SENSITIVITY and TEMPORAL FINE STRUCTURE; the COGNITIVE variables in one COGNITION factor only, and OUTCOMES in two factors, NO CONTEXT and CONTEXT. COGNITION predicted the NO CONTEXT factor to a stronger extent than the CONTEXT outcome factor. TEMPORAL FINE STRUCTURE and SENSITIVITY were associated with COGNITION and all three contributed significantly and independently to especially the NO CONTEXT outcome scores (R2 = 0.40). Conclusions: All LEVEL 2 factors are important theoretically as well as for clinical assessment.

Imitation, Sign Language Skill and the Developmental Ease of Language Understanding (D-ELU) Model.

Imitation and language processing are closely connected. According to the Ease of Language Understanding (ELU) model (Rönnberg et al., 2013) pre-existing mental representation of lexical items facilitates language understanding. Thus, imitation of manual gestures is likely to be enhanced by experience of sign language. We tested this by eliciting imitation of manual gestures from deaf and hard-of-hearing (DHH) signing and hearing non-signing children at a similar level of language and cognitive development. We predicted that the DHH signing children would be better at imitating gestures lexicalized in their own sign language (Swedish Sign Language, SSL) than unfamiliar British Sign Language (BSL) signs, and that both groups would be better at imitating lexical signs (SSL and BSL) than non-signs. We also predicted that the hearing non-signing children would perform worse than DHH signing children with all types of gestures the first time (T1) we elicited imitation, but that the performance gap between groups would be reduced when imitation was elicited a second time (T2). Finally, we predicted that imitation performance on both occasions would be associated with linguistic skills, especially in the manual modality. A split-plot repeated measures ANOVA demonstrated that DHH signers imitated manual gestures with greater precision than non-signing children when imitation was elicited the second but not the first time. Manual gestures were easier to imitate for both groups when they were lexicalized than when they were not; but there was no difference in performance between familiar and unfamiliar gestures. For both groups, language skills at T1 predicted imitation at T2. Specifically, for DHH children, word reading skills, comprehension and phonological awareness of sign language predicted imitation at T2. For the hearing participants, language comprehension predicted imitation at T2, even after the effects of working memory capacity and motor skills were taken into account. These results demonstrate that experience of sign language enhances the ability to imitate manual gestures once representations have been established, and suggest that the inherent motor patterns of lexical manual gestures are better suited for representation than those of non-signs. This set of findings prompts a developmental version of the ELU model, D-ELU.

Cognitive aging and hearing acuity: modeling spoken language comprehension.

The comprehension of spoken language has been characterized by a number of “local” theories that have focused on specific aspects of the task: models of word recognition, models of selective attention, accounts of thematic role assignment at the sentence level, and so forth. The ease of language understanding (ELU) model (Rönnberg et al., 2013) stands as one of the few attempts to offer a fully encompassing framework for language understanding. In this paper we discuss interactions between perceptual, linguistic, and cognitive factors in spoken language understanding. Central to our presentation is an examination of aspects of the ELU model that apply especially to spoken language comprehension in adult aging, where speed of processing, working memory capacity, and hearing acuity are often compromised. We discuss, in relation to the ELU model, conceptions of working memory and its capacity limitations, the use of linguistic context to aid in speech recognition and the importance of inhibitory control, and language comprehension at the sentence level. Throughout this paper we offer a constructive look at the ELU model; where it is strong and where there are gaps to be filled.

The effects of hearing loss on neural processing and plasticity.

The effects of hearing loss on neural processing and plasticity.

The Ease of Language Understanding (ELU) model: theoretical, empirical, and clinical advances

Working memory is important for online language processing during conversation. We use it to maintain relevant information, to inhibit or ignore irrelevant information, and to attend to conversation selectively. Working memory helps us to keep track of and actively participate in conversation, including taking turns and following the gist. This paper examines the Ease of Language Understanding model (i.e., the ELU model, Rönnberg, 2003; Rönnberg et al., 2008) in light of new behavioral and neural findings concerning the role of working memory capacity (WMC) in uni-modal and bimodal language processing. The new ELU model is a meaning prediction system that depends on phonological and semantic interactions in rapid implicit and slower explicit processing mechanisms that both depend on WMC albeit in different ways. It is based on findings that address the relationship between WMC and (a) early attention processes in listening to speech, (b) signal processing in hearing aids and its effects on short-term memory, (c) inhibition of speech maskers and its effect on episodic long-term memory, (d) the effects of hearing impairment on episodic and semantic long-term memory, and finally, (e) listening effort. New predictions and clinical implications are outlined. Comparisons with other WMC and speech perception models are made.

Working memory compensates for hearing related phonological processing deficit

Acquired hearing impairment is associated with gradually declining phonological representations. According to the Ease of Language Understanding (ELU) model, poorly defined representations lead to mismatch in phonologically challenging tasks. To resolve the mismatch, reliance on working memory capacity (WMC) increases. This study investigated whether WMC modulated performance in a phonological task in individuals with hearing impairment. A visual rhyme judgment task with congruous or incongruous orthography, followed by an incidental episodic recognition memory task, was used. In participants with hearing impairment, WMC modulated both rhyme judgment performance and recognition memory in the orthographically similar non-rhyming condition; those with high WMC performed exceptionally well in the judgment task, but later recognized few of the words. For participants with hearing impairment and low WMC the pattern was reversed; they performed poorly in the judgment task but later recognized a surprisingly large proportion of the words. Results indicate that good WMC can compensate for the negative impact of auditory deprivation on phonological processing abilities by allowing for efficient use of phonological processing skills. They also suggest that individuals with hearing impairment and low WMC may use a non-phonological approach to written words, which can have the beneficial side effect of improving memory encoding.Learning outcomes: Readers will be able to: (1) describe cognitive processes involved in rhyme judgment, (2) explain how acquired hearing impairment affects phonological processing and (3) discuss how reading strategies at encoding impact memory performance.

Speech in noise and ease of language understanding: when and how working memory capacity plays a role

A working memory based model for Ease of Language Understanding (ELU) has been developed (Rönnberg, 2003; Rönnberg et al., 2008; Rönnberg et al., 2011). It predicts that speech understanding in adverse, mismatching noise conditions is dependent on explicit processing resources such as working memory capacity (WMC). This presentation will examine the details of this prediction by addressing some recent data on (1) how brainstem responses are modulated by working memory load and WMC, (2) how cortical correlates of speech understanding in noise are modulated by WMC, and (3) how WMC determines episodic long-term memory for spoken discourse masked by speech.

Cognitive Hearing Science

Stuart Gatehouse was one of the pioneers of cognitive hearing science. The ease of language understanding (ELU) model (Rönnberg) is one example of a cognitive hearing science model where the interplay between memory systems and signal processing is emphasized. The mismatch notion is central to ELU and concerns how phonological information derived from the signal, matches/mismatches phonological representations in lexical and semantic long-term memory (LTM). When signals match, processing is rapid, automatic and implicit, and lexical activation proceeds smoothly. Given a mismatch, lexical activation fails, and working or short-term memory (WM/STM) is assumed to be invoked to engage in explicit repair strategies to disambiguate what was said in the conversation. In a recent study, negative long-term consequences of mismatch were found by means of relating hearing loss to episodic LTM in a sample of old hearing-aid wearers. STM was intact (Rönnberg et al.). Beneficial short-term consequences of a binary masking noise reduction scheme on STM was obtained in 4-talker babble for individuals with high WM capacity, but not in stationary noise backgrounds (Ng et al.). This suggests that individuals high on WM capacity inhibit semantic auditory distraction in 4-talker babble while exploiting the phonological benefits in terms of speech quality provided by binary masking (Wang). Both long-term and short-term mismatch effects, apparent in data sets including behavioral as well as subjective (Rudner et al.) data, need to be taken into account in the design of future hearing instruments.

Editorial

Editorial

Cognition and aided speech recognition in noise: Specific role for cognitive factors following nine‐week experience with adjusted compression settings in hearing aids

The working memory model for Ease of Language Understanding (ELU) proposes that language understanding under taxing conditions is related to explicit cognitive capacity. We refer to this as the mismatch hypothesis, since phonological representations based on the processing of speech under established conditions may not be accessed so readily when input conditions change and a match becomes problematic. Then, cognitive capacity requirements may differ from those used for processing speech hitherto. In the present study, we tested this hypothesis by investigating the relationship between aided speech recognition in noise and cognitive capacity in experienced hearing aid users when there was either a match or mismatch between processed speech input and established phonological representations. The settings in the existing digital hearing aids of the participants were adjusted to one of two different compression settings which processed the speech signal in qualitatively different ways ("fast" or "slow"). Testing took place after a 9-week period of experience with the new setting. Speech recognition was tested under different noise conditions and with match or mismatch (i.e. alternative compression setting) manipulations of the input signal. Individual cognitive capacity was measured using a reading span test and a letter monitoring test. Reading span, a reliable measure of explicit cognitive capacity, predicted speech recognition performance under mismatch conditions when processed input was incongruent with recently established phonological representations, due to the specific hearing aid setting. Cognitive measures were not main predictors of performance under match conditions. These findings are in line with the ELU model.