scholarly journals Dissociable electrophysiological measures of natural language processing reveal differences in speech comprehension strategy in healthy ageing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael P. Broderick ◽  
Giovanni M. Di Liberto ◽  
Andrew J. Anderson ◽  
Adrià Rofes ◽  
Edmund C. Lalor
Keyword(s):  
Older Adults ◽  
Cognitive Processing ◽  
Language Processing ◽  
Semantic Representation ◽  
Healthy Ageing ◽  
Activation Mechanism ◽  
Speech Comprehension ◽  
Semantic Features ◽  
Semantic Level ◽  
Older Subjects

AbstractHealthy ageing leads to changes in the brain that impact upon sensory and cognitive processing. It is not fully clear how these changes affect the processing of everyday spoken language. Prediction is thought to play an important role in language comprehension, where information about upcoming words is pre-activated across multiple representational levels. However, evidence from electrophysiology suggests differences in how older and younger adults use context-based predictions, particularly at the level of semantic representation. We investigate these differences during natural speech comprehension by presenting older and younger subjects with continuous, narrative speech while recording their electroencephalogram. We use time-lagged linear regression to test how distinct computational measures of (1) semantic dissimilarity and (2) lexical surprisal are processed in the brains of both groups. Our results reveal dissociable neural correlates of these two measures that suggest differences in how younger and older adults successfully comprehend speech. Specifically, our results suggest that, while younger and older subjects both employ context-based lexical predictions, older subjects are significantly less likely to pre-activate the semantic features relating to upcoming words. Furthermore, across our group of older adults, we show that the weaker the neural signature of this semantic pre-activation mechanism, the lower a subject’s semantic verbal fluency score. We interpret these findings as prediction playing a generally reduced role at a semantic level in the brains of older listeners during speech comprehension and that these changes may be part of an overall strategy to successfully comprehend speech with reduced cognitive resources.

scholarly journals Dissociable electrophysiological measures of natural language processing reveal differences in speech comprehension strategy in healthy ageing

2020 ◽  
Author(s):  
Michael P. Broderick ◽  
Giovanni M. Di Liberto ◽  
Andrew J. Anderson ◽  
Adrià Rofes ◽  
Edmund C. Lalor
Keyword(s):  
Older Adults ◽  
Cognitive Processing ◽  
Language Processing ◽  
Semantic Representation ◽  
Healthy Ageing ◽  
Activation Mechanism ◽  
Speech Comprehension ◽  
Semantic Features ◽  
Semantic Level ◽  
Older Subjects

AbstractHealthy ageing leads to changes in the brain that impact upon sensory and cognitive processing. It is not fully clear how these changes affect the processing of everyday spoken language. Prediction is thought to play an important role in language comprehension, where information about upcoming words is pre-activated across multiple representational levels. However, evidence from electrophysiology suggests differences in how older and younger adults use context-based predictions, particularly at the level of semantic representation. We investigate these differences during natural speech comprehension by presenting older and younger subjects with continuous, narrative speech while recording their electroencephalogram. We use linear regression to test how distinct computational measures of 1) semantic dissimilarity and 2) lexical surprisal are processed in the brains of both groups. Our results reveal dissociable neural correlates of these two measures that suggest differences in how younger and older adults successfully comprehend speech. Specifically, our results suggest that, while younger and older subjects both employ context-based lexical predictions, older subjects are significantly less likely to pre-activate the semantic features relating to upcoming words. Furthermore, across our group of older adults, we show that the weaker the neural signature of this semantic pre-activation mechanism, the lower a subject’s semantic verbal fluency score. We interpret these findings as prediction playing a generally reduced role at a semantic level in the brains of older listeners during speech comprehension and that these changes may be part of an overall strategy to successfully comprehend speech with reduced cognitive resources.

scholarly journals Mishearing as a Side Effect of Rational Language Comprehension in Noise

2021 ◽  
Vol 12 ◽  
Author(s):  
Marjolein Van Os ◽  
Jutta Kray ◽  
Vera Demberg
Keyword(s):  
Older Adults ◽  
Language Processing ◽  
Language Comprehension ◽  
Speech Signal ◽  
Speech Comprehension ◽  
Noisy Signal ◽  
Simple Consequence ◽  
Top Down ◽  
Rational Language ◽  
Listening Experiment

Language comprehension in noise can sometimes lead to mishearing, due to the noise disrupting the speech signal. Some of the difficulties in dealing with the noisy signal can be alleviated by drawing on the context – indeed, top-down predictability has shown to facilitate speech comprehension in noise. Previous studies have furthermore shown that strong reliance on the top-down predictions can lead to increased rates of mishearing, especially in older adults, which are attributed to general deficits in cognitive control in older adults. We here propose that the observed mishearing may be a simple consequence of rational language processing in noise. It should not be related to failure on the side of the older comprehenders, but instead would be predicted by rational processing accounts. To test this hypothesis, we extend earlier studies by running an online listening experiment with younger and older adults, carefully controlling the target and direct competitor in our stimuli. We show that mishearing is directly related to the perceptibility of the signal. We furthermore add an analysis of wrong responses, which shows that results are at odds with the idea that participants overly strongly rely on context in this task, as most false answers are indeed close to the speech signal, and not to the semantics of the context.

scholarly journals Healthy Ageing and Sentence Production: Disrupted Lexical Access in the Context of Intact Syntactic Planning

2018 ◽  
Author(s):  
Sophie M. Hardy ◽  
Katrien Segaert ◽  
Linda Wheeldon
Keyword(s):  
Older Adults ◽  
Language Processing ◽  
Age Groups ◽  
Healthy Ageing ◽  
Sentence Production ◽  
Lexical Retrieval ◽  
Age Related ◽  
Multiple Processes ◽  
Priming Paradigm ◽  
Successful Execution

AbstractHealthy ageing does not affect all features of language processing equally. In this study, we investigated the effects of ageing on different processes involved in fluent sentence production, a complex task that requires the successful execution and coordination of multiple processes. In Experiment 1, we investigated age-related effects on the speed of syntax selection using a syntactic priming paradigm. Both young and older adults produced target sentences quicker following syntactically related primes compared to unrelated primes, indicating that syntactic facilitation effects are preserved with age. In Experiment 2, we investigated age-related effects in syntactic planning and lexical retrieval using a planning scope paradigm: participants described moving picture displays designed to elicit sentences with either initial coordinate or simple noun phrases and, on half of the trials, the second picture was previewed. Without preview, both age groups were slower to initiate sentences with larger coordinate phrases, suggesting a similar phrasal planning scope. However, age-related differences did emerge relating to the preview manipulation: while young adults displayed speed benefits of preview in both phrase conditions, older adults only displayed speed preview benefits within the initial phrase (coordinate condition). Moreover, preview outside the initial phrase (simple condition) caused older adults to become significantly more error-prone. Thus, while syntactic planning scope appears unaffected by ageing, older adults do appear to encounter problems with managing the activation and integration of lexical items into syntactic structures. Taken together, our findings indicate that healthy ageing disrupts the lexical, but not the syntactic, processes involved in sentence production.

Low-Resource Language Discrimination toward Chinese Dialects with Transfer Learning and Data Augmentation

2022 ◽  
Vol 21 (2) ◽  
pp. 1-21
Author(s):  
Fan Xu ◽  
Yangjie Dan ◽  
Keyu Yan ◽  
Yong Ma ◽  
Mingwen Wang
Keyword(s):  
Transfer Learning ◽  
Language Processing ◽  
Data Augmentation ◽  
Semantic Representation ◽  
Semantic Features ◽  
Language Discrimination ◽  
Low Resource ◽  
Chinese Dialects ◽  
Fine Tune ◽  
Target Side

Chinese dialects discrimination is a challenging natural language processing task due to scarce annotation resource. In this article, we develop a novel Chinese dialects discrimination framework with transfer learning and data augmentation (CDDTLDA) in order to overcome the shortage of resources. To be more specific, we first use a relatively larger Chinese dialects corpus to train a source-side automatic speech recognition (ASR) model. Then, we adopt a simple but effective data augmentation method (i.e., speed, pitch, and noise disturbance) to augment the target-side low-resource Chinese dialects, and fine-tune another target ASR model based on the previous source-side ASR model. Meanwhile, the potential common semantic features between source-side and target-side ASR models can be captured by using self-attention mechanism. Finally, we extract the hidden semantic representation in the target ASR model to conduct Chinese dialects discrimination. Our extensive experimental results demonstrate that our model significantly outperforms state-of-the-art methods on two benchmark Chinese dialects corpora.

Cognitive Processing of Miscommunication in Interactive Listening: An Evaluation of Listener Indecision and Cognitive Effort

2021 ◽  
pp. 1-17
Author(s):  
Jennifer M. Roche ◽  
Arkady Zgonnikov ◽  
Laura M. Morett
Keyword(s):  
Decision Making ◽  
Cognitive Processing ◽  
Language Processing ◽  
Cognitive Effort ◽  
Mouse Tracking ◽  
Computer Mouse ◽  
Decision Making Processes ◽  
Computer Mouse Tracking ◽  
Listening Task ◽  
Processing Effort

Purpose The purpose of the current study was to evaluate the social and cognitive underpinnings of miscommunication during an interactive listening task. Method An eye and computer mouse–tracking visual-world paradigm was used to investigate how a listener's cognitive effort (local and global) and decision-making processes were affected by a speaker's use of ambiguity that led to a miscommunication. Results Experiments 1 and 2 found that an environmental cue that made a miscommunication more or less salient impacted listener language processing effort (eye-tracking). Experiment 2 also indicated that listeners may develop different processing heuristics dependent upon the speaker's use of ambiguity that led to a miscommunication, exerting a significant impact on cognition and decision making. We also found that perspective-taking effort and decision-making complexity metrics (computer mouse tracking) predict language processing effort, indicating that instances of miscommunication produced cognitive consequences of indecision, thinking, and cognitive pull. Conclusion Together, these results indicate that listeners behave both reciprocally and adaptively when miscommunications occur, but the way they respond is largely dependent upon the type of ambiguity and how often it is produced by the speaker.

Age-Related Differences in Processing Dynamic Information to Identify Vowel Quality

1992 ◽  
Vol 35 (4) ◽  
pp. 892-902 ◽  
Author(s):  
Robert Allen Fox ◽  
Lida G. Wall ◽  
Jeanne Gokcen
Keyword(s):  
Older Adults ◽  
Vowel Quality ◽  
Perceptual Cues ◽  
Dynamic Information ◽  
Process Dynamic ◽  
Center Condition ◽  
Age Related ◽  
Control Version ◽  
Older Subjects ◽  
Whole Word

This study examined age-related differences in the use of dynamic acoustic information (in the form of formant transitions) to identify vowel quality in CVCs. Two versions of 61 naturally produced, commonly occurring, monosyllabic English words were created: a control version (the unmodified whole word) and a silent-center version (in which approximately 62% of the medial vowel was replaced by silence). A group of normal-hearing young adults (19–25 years old) and older adults (61–75 years old) identified these tokens. The older subjects were found to be significantly worse than the younger subjects at identifying the medial vowel and the initial and final consonants in the silent-center condition. These results support the hypothesis of an age-related decrement in the ability to process dynamic perceptual cues in the perception of vowel quality.

The Opposition of Surprisal and Semantic Similarity in the Prediction of Language Processing: Evidence from Eye-tracking Data

2020 ◽  
Author(s):  
Kun Sun
Keyword(s):  
Eye Tracking ◽  
Semantic Similarity ◽  
Cognitive Processing ◽  
Language Processing ◽  
Language Comprehension ◽  
Word Processing ◽  
Reading Time ◽  
Computational Models ◽  
Tracking Data ◽  
Dynamic Approach

Expectations or predictions about upcoming content play an important role during language comprehension and processing. One important aspect of recent studies of language comprehension and processing concerns the estimation of the upcoming words in a sentence or discourse. Many studies have used eye-tracking data to explore computational and cognitive models for contextual word predictions and word processing. Eye-tracking data has previously been widely explored with a view to investigating the factors that influence word prediction. However, these studies are problematic on several levels, including the stimuli, corpora, statistical tools they applied. Although various computational models have been proposed for simulating contextual word predictions, past studies usually preferred to use a single computational model. The disadvantage of this is that it often cannot give an adequate account of cognitive processing in language comprehension. To avoid these problems, this study draws upon a massive natural and coherent discourse as stimuli in collecting the data on reading time. This study trains two state-of-art computational models (surprisal and semantic (dis)similarity from word vectors by linear discriminative learning (LDL)), measuring knowledge of both the syntagmatic and paradigmatic structure of language. We develop a `dynamic approach' to compute semantic (dis)similarity. It is the first time that these two computational models have been merged. Models are evaluated using advanced statistical methods. Meanwhile, in order to test the efficiency of our approach, one recently developed cosine method of computing semantic (dis)similarity based on word vectors data adopted is used to compare with our `dynamic' approach. The two computational and fixed-effect statistical models can be used to cross-verify the findings, thus ensuring that the result is reliable. All results support that surprisal and semantic similarity are opposed in the prediction of the reading time of words although both can make good predictions. Additionally, our `dynamic' approach performs better than the popular cosine method. The findings of this study are therefore of significance with regard to acquiring a better understanding how humans process words in a real-world context and how they make predictions in language cognition and processing.

NESTORE Ontology: a Multi-Domain Semantic Tool for the Characterization of Older Adults Status and Behaviour to Promote Healthy Ageing by IoT Systems (Preprint)

2020 ◽  
Author(s):  
Alfonso Mastropietro ◽  
Filippo Palumbo ◽  
Silvia Orte ◽  
Michele Girolami ◽  
Francesco Furfari ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Mental Status ◽  
Scientific Knowledge ◽  
Social Behaviour ◽  
Physical Activity Behaviour ◽  
Healthy Ageing ◽  
Physiological Status ◽  
Ageing Population ◽  
Activity Behaviour

BACKGROUND The constant progression in number and share of the ageing population will likely have deep effects in most of the industrialized countries. The Internet of Things (IoT) paradigm can play a key role in facilitating independent living of the ageing population thus trying to reduce the burden on the society. Considering that ageing is a multi-factorial physiological process, the development of novel IoT systems, tools and devices, specifically targeted to older people, must be based on a holistic framework built on robust scientific knowledge in different scientific domains. OBJECTIVE A novel semantic formalization was developed, based on a multidomain healthy ageing model, to support structuring and standardizing heterogeneous scientific knowledge about ageing. The main aim of the paper is to present the new NESTORE ontology, with the purpose thus extending the available ontologies provided by universAAL-IoT (uAAL-IoT). METHODS Well-assessed scientific knowledge, specifically selected to target older adults aged between 65 and 75, was formalized into a holistic model using a multi-domain approach including three main different dimensions related to well-being: (i) Physiological Status and Physical Activity Behaviour, (ii) Nutrition, and (iii) Cognitive and Mental Status and Social Behaviour. Based on this model, within the NESTORE H2020 project, a new ontology was developed in the uAAL-IoT framework, which provides modelling tools and a set of core ontologies. RESULTS The NESTORE ontologies cover all the needed concepts to represent 5 significant domains of ageing. In total, 12 sub-ontologies were modelled with more than 60 classes and sub-classes referenced among them by using more than 100 relations and around 20 enumerations. NESTORE increases the uAAL ontologies collection by 40% and expand the uAAL domain usage for Physiological Status and Physical Activity Behaviour (8 ontologies), Nutrition (3 ontologies) and Cognitive and Mental Status and Social Behaviour (4 ontologies). CONCLUSIONS NESTORE ontology provides innovation both in terms of semantic content and technological approach. The thoroughly use of this ontology can support the development of a decision support system, to promote healthy ageing, with the capacity to do dynamic multi-scale modelling of user-specific data based on the semantic annotations of users’ profile.

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