Spoken Language Comprehension Research Articles

The structure and statistics of language jointly shape cross-frequency neural dynamics during spoken language comprehension

Humans excel at extracting structurally-determined meaning from speech despite inherent physical variability. This study explores the brain’s ability to predict and understand spoken language robustly. It investigates the relationship between structural and statistical language knowledge in brain dynamics, focusing on phase and amplitude modulation. Using syntactic features from constituent hierarchies and surface statistics from a transformer model as predictors of forward encoding models, we reconstructed cross-frequency neural dynamics from MEG data during audiobook listening. Our findings challenge a strict separation of linguistic structure and statistics in the brain, with both aiding neural signal reconstruction. Syntactic features have a more temporally spread impact, and both word entropy and the number of closing syntactic constituents are linked to the phase-amplitude coupling of neural dynamics, implying a role in temporal prediction and cortical oscillation alignment during speech processing. Our results indicate that structured and statistical information jointly shape neural dynamics during spoken language comprehension and suggest an integration process via a cross-frequency coupling mechanism.

Facilitative Processing of Grammatical Gender in Heritage Speakers with Two Gender Systems

Abstract This study investigates facilitative processing of grammatical gender in heritage Spanish speakers whose dominant language is German, using eye-tracking in the Visual World Paradigm. Bilinguals with two gender systems are known to have an integrated mental lexicon with shared gender features that are co-activated during language processing and can result in interference. The present study shows that, despite observed effects of gender congruency with German, heritage speakers were able to use gender information on prenominal articles in Spanish to facilitate lexical retrieval of the target noun. This suggests that processing of gender agreement in the heritage language is resilient to competition from gender in the dominant language during real-time spoken-language comprehension. Moreover, direct comparison with previous results from heritage Spanish speakers in the USA does not show evidence that overall speed of facilitative processing in the heritage language is modulated by the presence or absence of gender in the majority language.

Students' Strategies for Improving Their Listening Comprehension

In order to navigate many of the circumstances that arise in everyday life, one must practice active listening. People listen to audio for a variety of reasons, including amusement, learning in scholarly fields, or gathering important information. Students with a wide variety of hearing problems often show symptoms when they try to comprehend the content delivered in English. Children often find it difficult to absorb spoken information since schools place a strong focus on language, reading, and writing. Most course guides and lecturers tend to downplay the importance of listening. The challenges with auditory perception, particularly those pertaining to hearing, actively processing, and comprehending spoken information, are the main focus of this research. Teachers who are aware of the difficulties that their pupils encounter in the classroom may assist their students more successfully in order to help them improve their comprehension of spoken language and acquire excellent listening skills. This is a result of the teachers' improved ability to relate to and comprehend the emotions and experiences of their students. The significance of helping students develop efficient study habits and improve their English listening abilities is emphasized in this article review. Students who are struggling in other courses could get help from teachers who specialize in teaching English as a second language. In the conclusion, the researcher made suggestions for instructional exercises that both professors and pupils need to partake in.

Delta-band Activity Underlies Referential Meaning Representation during Pronoun Resolution.

Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities or concepts that have been encoded in memory from previous linguistic context. Models of language processing propose that internally stored linguistic concepts, accessed via exogenous cues such as phonological input of a word, are represented as (a)synchronous activities across a population of neurons active at specific frequency bands. Converging evidence suggests that delta band activity (1-3 Hz) is involved in temporal and representational integration during sentence processing. Moreover, recent advances in the neurobiology of memory suggest that recollection engages neural dynamics similar to those which occurred during memory encoding. Integrating from these two research lines, we here tested the hypothesis that neural dynamic patterns, especially in delta frequency range, underlying referential meaning representation, would be reinstated during pronoun resolution. By leveraging neural decoding techniques (i.e., representational similarity analysis) on a magnetoencephalogram data set acquired during a naturalistic story-listening task, we provide evidence that delta-band activity underlies referential meaning representation. Our findings suggest that, during spoken language comprehension, endogenous linguistic representations such as referential concepts may be proactively retrieved and represented via activation of their underlying dynamic neural patterns.

Correlation of Cognitive and Linguistic Factors with Spoken Language Comprehension in Early Elementary Students

Correlation of Cognitive and Linguistic Factors with Spoken Language Comprehension in Early Elementary Students

Integration of semantic and coarticulation cues during spoken language comprehension in adults

Recent work examining cue integration across levels of linguistic representation has found that listeners can dynamically integrate some of the lower-level and higher-level cues during spoken language comprehension. However, it is still not well understood how the mechanism of cue integration works. This study investigated how adults (n = 52) process preceding higher-level semantic cues and later low-level coarticulation cues during spoken language comprehension using an eye-tracking paradigm. Participants were tested on sentences that contained a prime (semantically related or semantically unrelated to the target) and a target which had varying coarticulation cues (matching versus mismatching splicing cues). Participants were presented with two pictures (target and competitor) on a screen. Analyses looked at the proportion of looking to the target during the prime and target time windows. Results demonstrate that adults flexibly use both the preceding semantic cues and later coarticulatory cues once they are available. Our findings also indicate that adults flexibly weighed both the preceding higher-level and later lower-level cues, such that the processing of low-level coarticulatory cue varied depending on the semantic context. We have added an unstudied level of cue (semantic context) to the set of cues that our cognitive system can integrate during language comprehension.

The Cerebellum Is Sensitive to the Lexical Properties of Words During Spoken Language Comprehension.

Over the past few decades, research into the function of the cerebellum has expanded far beyond the motor domain. A growing number of studies are probing the role of specific cerebellar subregions, such as Crus I and Crus II, in higher-order cognitive functions including receptive language processing. In the current fMRI study, we show evidence for the cerebellum's sensitivity to variation in two well-studied psycholinguistic properties of words-lexical frequency and phonological neighborhood density-during passive, continuous listening of a podcast. To determine whether, and how, activity in the cerebellum correlates with these lexical properties, we modeled each word separately using an amplitude-modulated regressor, time-locked to the onset of each word. At the group level, significant effects of both lexical properties landed in expected cerebellar subregions: Crus I and Crus II. The BOLD signal correlated with variation in each lexical property, consistent with both language-specific and domain-general mechanisms. Activation patterns at the individual level also showed that effects of phonological neighborhood and lexical frequency landed in Crus I and Crus II as the most probable sites, though there was activation seen in other lobules (especially for frequency). Although the exact cerebellar mechanisms used during speech and language processing are not yet evident, these findings highlight the cerebellum's role in word-level processing during continuous listening.

Difficulty Student Understand English Speech in the Second Semester of the English Study Program

Listening is a crucial skill that needs to be mastered in English language acquisition. However, several obstacles hinder the mastery of listening, such as difficulties in comprehending spoken language. In this scenario, there are a significant number of students who cannot comprehend the English language. The objective of this study is to identify the factors that contribute to students' difficulty in comprehending spoken English. The participants of this study consisted of English major students enrolled in the second semester at STAIN Gajah Putih Takengon. The focus of this research was to investigate the challenges that these students encounter when comprehending spoken language in the listening domain. The research methodology employed is qualitative. Regarding the internal instruments, this study employs observation, tests, and interviews. Research findings indicate that there are multiple factors that contribute to students' inability to comprehend English speech. The primary factors that influence students' listening skills are lack of concentration, speaking speed, and originality. The conclusion that can be inferred from this study is that the speed of speech delivery and a lack of concentration in listening are contributing factors to difficulty in understanding speech.

Acoustic and language-specific sources for phonemic abstraction from speech

Spoken language comprehension requires abstraction of linguistic information from speech, but the interaction between auditory and linguistic processing of speech remains poorly understood. Here, we investigate the nature of this abstraction using neural responses recorded intracranially while participants listened to conversational English speech. Capitalizing on multiple, language-specific patterns where phonological and acoustic information diverge, we demonstrate the causal efficacy of the phoneme as a unit of analysis and dissociate the unique contributions of phonemic and spectrographic information to neural responses. Quantitive higher-order response models also reveal that unique contributions of phonological information are carried in the covariance structure of the stimulus-response relationship. This suggests that linguistic abstraction is shaped by neurobiological mechanisms that involve integration across multiple spectro-temporal features and prior phonological information. These results link speech acoustics to phonology and morphosyntax, substantiating predictions about abstractness in linguistic theory and providing evidence for the acoustic features that support that abstraction.

The volume and the distribution of premorbid white matter hyperintensities: Impact on post-stroke aphasia.

White matter hyperintensities (WMH) are a radiological manifestation of progressive white matter integrity loss. The total volume and distribution of WMH within the corpus callosum have been associated with pathological cognitive ageing processes but have not been considered in relation to post-stroke aphasia outcomes. We investigated the contribution of both the total volume of WMH, and the extent of WMH lesion load in the corpus callosum to the recovery of language after first-ever stroke. Behavioural and neuroimaging data from individuals (N = 37) with a left-hemisphere stroke were included at the early subacute stage of recovery. Spoken language comprehension and production abilities were assessed using word and sentence-level tasks. Neuroimaging data was used to derive stroke lesion variables (volume and lesion load to language critical regions) and WMH variables (WMH volume and lesion load to three callosal segments). WMH volume did not predict variance in language measures, when considered together with stroke lesion and demographic variables. However, WMH lesion load in the forceps minor segment of the corpus callosum explained variance in early subacute comprehension abilities (t = -2.59, p = .01) together with corrected stroke lesion volume and socio-demographic variables. Premorbid WMH lesions in the forceps minor were negatively associated with early subacute language comprehension after aphasic stroke. This negative impact of callosal WMH on language is consistent with converging evidence from pathological ageing suggesting that callosal WMH disrupt the neural networks supporting a range of cognitive functions.

Comprehending Turkish sentences using word order, thematic roles, and case

A core aspect of sentence comprehension is assigning thematic roles such as agents and patients to nouns. Turkish, a flexible word order language with accusative case-marking, allows us to compare the relative effect of word order, case-marking, and thematic reversibility in sentence comprehension. We conducted two spoken language comprehension experiments to investigate the relationships among these factors. Native Turkish-speaking adults were faster and more accurate in comprehending sentences with default word order than those with scrambled word order; case-marked sentences than non-casemarked sentences; and sentences with thematically irreversible nouns than those with reversible nouns. The effect of word order depended on the reversibility of the nouns, and case-marking had little-to-no effect on comprehension when the nouns were thematically irreversible. Our results suggest that while Turkish speakers use multiple cues to map thematic roles onto nouns, there are diminishing returns of facilitation with each additional source of information. These results give support to race-based models of sentence comprehension.

Hierarchical and Bidirectional Joint Multi-Task Classifiers for Natural Language Understanding

The MASSIVE dataset is a spoken-language comprehension resource package for slot filling, intent classification, and virtual assistant evaluation tasks. It contains multi-language utterances from human beings communicating with a virtual assistant. In this paper, we exploited the relationship between intent classification and slot filling to improve the exact match accuracy by proposing five models with hierarchical and bidirectional architectures. There are two variants for hierarchical architectures and three variants for bidirectional architectures. These are the hierarchical concatenation model, the hierarchical attention-based model, the bidirectional max-pooling model, the bidirectional LSTM model, and the bidirectional attention-based model. The results of our models showed a significant improvement in the averaged exact match accuracy. The hierarchical attention-based model improved the accuracy by 1.01 points for the full training dataset. As for the zero-shot setup, we observed that the exact match accuracy increased from 53.43 to 53.91. In this study, we observed that, for multi-task problems, utilizing the relevance between different tasks can help in improving the model’s overall performance.

USING SONGS AND MUSICS TO IMPROVE STUDENTS’ LISTENING SKILLS IN SENIOR HIGH SCHOOL

Listening is the most critical aspect of language acquisition, without which one cannot comprehend spoken language, nor can they produce any spoken language. However, EFL learners and teachers find listening is difficult to learn and to teach. Teachers can play a critical role in helping students overcome these challenges by providing opportunities for students to practice active listening, engaging them in discussions that are relevant to their interests and backgrounds, and using a variety of teaching methods, media, and resources to enhance their listening skills, one of which is using songs. Listening to English songs and music can be effective ways to improve students’ listening skills. Songs can provide a fun and engaging way for students to practice their listening comprehension as well as help them become more familiar with the language and its pronunciation. Furthermore, music can help motivate students to expand their vocabulary and pronunciation skills..

Enhanced Dual Convolutional Neural Network Model Using Explainable Artificial Intelligence of Fault Prioritization for Industrial 4.0.

Artificial intelligence (AI) systems are increasingly used in corporate security measures to predict the status of assets and suggest appropriate procedures. These programs are also designed to reduce repair time. One way to create an efficient system is to integrate physical repair agents with a computerized management system to develop an intelligent system. To address this, there is a need for a new technique to assist operators in interacting with a predictive system using natural language. The system also uses double neural network convolutional models to analyze device data. For fault prioritization, a technique utilizing fuzzy logic is presented. This strategy ranks the flaws based on the harm or expense they produce. However, the method's success relies on ongoing improvement in spoken language comprehension through language modification and query processing. To carry out this technique, a conversation-driven design is necessary. This type of learning relies on actual experiences with the assistants to provide efficient learning data for language and interaction models. These models can be trained to have more natural conversations. To improve accuracy, academics should construct and maintain publicly usable training sets to update word vectors. We proposed the model dataset (DS) with the Adam (AD) optimizer, Ridge Regression (RR) and Feature Mapping (FP). Our proposed algorithm has been coined with an appropriate acronym DSADRRFP. The same proposed approach aims to leverage each component's benefits to enhance the predictive model's overall performance and precision. This ensures the model is up-to-date and accurate. In conclusion, an AI system integrated with physical repair agents is a useful tool in corporate security measures. However, it needs to be refined to extract data from the operating system and to interact with users in a natural language. The system also needs to be constantly updated to improve accuracy.

A tradeoff between acoustic and linguistic feature encoding in spoken language comprehension.

When we comprehend language from speech, the phase of the neural response aligns with particular features of the speech input, resulting in a phenomenon referred to as neural tracking. In recent years, a large body of work has demonstrated the tracking of the acoustic envelope and abstract linguistic units at the phoneme and word levels, and beyond. However, the degree to which speech tracking is driven by acoustic edges of the signal, or by internally-generated linguistic units, or by the interplay of both, remains contentious. In this study, we used naturalistic story-listening to investigate (1) whether phoneme-level features are tracked over and above acoustic edges, (2) whether word entropy, which can reflect sentence- and discourse-level constraints, impacted the encoding of acoustic and phoneme-level features, and (3) whether the tracking of acoustic edges was enhanced or suppressed during comprehension of a first language (Dutch) compared to a statistically familiar but uncomprehended language (French). We first show that encoding models with phoneme-level linguistic features, in addition to acoustic features, uncovered an increased neural tracking response; this signal was further amplified in a comprehended language, putatively reflecting the transformation of acoustic features into internally generated phoneme-level representations. Phonemes were tracked more strongly in a comprehended language, suggesting that language comprehension functions as a neural filter over acoustic edges of the speech signal as it transforms sensory signals into abstract linguistic units. We then show that word entropy enhances neural tracking of both acoustic and phonemic features when sentence- and discourse-context are less constraining. When language was not comprehended, acoustic features, but not phonemic ones, were more strongly modulated, but in contrast, when a native language is comprehended, phoneme features are more strongly modulated. Taken together, our findings highlight the flexible modulation of acoustic, and phonemic features by sentence and discourse-level constraint in language comprehension, and document the neural transformation from speech perception to language comprehension, consistent with an account of language processing as a neural filter from sensory to abstract representations.

Developmental trajectories of spoken language comprehension and functional communication in children with cerebral palsy: A prospective cohort study.

To investigate spoken language comprehension (SLC), single-word comprehension (SWC), functional communication development, and their determinants, in children with cerebral palsy. This was a prospective cohort study in the Netherlands spanning 2 years 6 months. The main outcomes were SLC and SWC, assessed by the Computer-Based instrument for Low motor Language Testing (C-BiLLT) and the Peabody Picture Vocabulary Test-III-NL (PPVT-III-NL) respectively; and functional communication, measured by a subscale of the Focus on the Outcomes of Communication Under Six-34 (FOCUS-34). Linear mixed models were used to determine developmental trajectories, which were compared with norm and reference data. Potential determinants, for example intellectual functions, speech production, functional communication level (classified with the Communication Function Classification System, CFCS), and functional mobility, were added to assess their effects. Children with cerebral palsy (n = 188; mean age 59 months, range 17-110) were monitored for 2 years 6 months. Developmental trajectories for SLC (C-BiLLT) and SWC (PPVT-III-NL) were nonlinear; those for functional communication (FOCUS-34) were linear. Compared with norm and reference groups, significantly delayed SLC, SWC, and functional communication development were found. Determinants for SLC and SWC were intellectual functions and functional communication level (CFCS); and for functional communication development (FOCUS-34), speech production and arm-hand functioning. Children with cerebral palsy showed delayed SLC, SWC, and functional communication development compared with norm and reference groups. Remarkably, functional mobility was not associated with the development of SLC, SWC, or functional communication. Children with cerebral palsy have delayed spoken language comprehension (SLC), single-word comprehension (SWC), and functional communication development, compared to norm and reference data. Determinants for SLC and SWC development are intellectual functions and functional communication level. Determinants for functional communication development are speech production and arm-hand functioning. Functional mobility is not associated with SLC, SWC, or functional communication.

Unknown treatment effects of donepezil in Alzheimer’s disease: Network analysis of three double‐blind randomized, placebo‐controlled, clinical trials

AbstractBackgroundPsychometric network analysis is an alternative theoretically‐driven analytic approach that has the potential to conceptualize cognitive impairment in Alzheimer’s disease differently than was previously assumed and consequently detect unknown treatment effects.MethodBased on individual participant data, extracted from three double‐blind, randomized placebo‐controlled clinical trials, psychometric networks were computed on observed Alzheimer’s Disease Assessment Scale Cognitive Subscale scores at baseline (N = 1,554) and on predicted change scores at 24 weeks of follow‐up for participants who received donepezil (N = 797) or placebo (N = 484).ResultA novel conceptualization of cognitive impairment in Alzheimer’s disease was displayed through the baseline network, that had 90% (n = 27) positive statistically significant (p<0.05) associations, and a most central aspect of ideational praxis. Following 24 weeks, treatment effects emerged via the differences between the change networks. The donepezil change network had more statistically significant (p<0.05) positive associations and a higher global strength (n = 15; S = 1.22; p = 0.03), than the placebo network (n = 8; S = 0.57), suggesting that for those who were treated with donepezil cognition is a more unified construct. Less for those given placebo. The main aspects of change in cognitive impairment were comprehension of spoken language for the donepezil network and spoken language ability for the placebo network, suggesting that comprehension of spoken language is most sensitive to pharmaceutical interventions.ConclusionOverall, psychometric network analysis presents a new conceptualization of cognitive impairment in Alzheimer’s disease, points to previously unknown treatment effects and highlights well‐defined aspects that may translate into future treatment targets.

The Influence of Caregiver Language on the Association Between Child Temperament and Spoken Language in Children Who Are Deaf or Hard of Hearing.

To examine the interaction between child temperament and caregiver linguistic input (i.e., syntactic complexity and lexical diversity) on receptive language in children who are deaf or hard of hearing (DHH). Families of 59 DHH children ( Mage = 5.66 years) using spoken language for communication participated in this cross-sectional study. Caregivers completed the Child Behavior Questionnaire-Short Form, which measured child temperament across three established factors (i.e., effortful control, negative affectivity, surgency-extraversion) and participated with their child in a semi-structured, dyadic play interaction that occurred during a home visit. Caregivers' language during the play interaction was quantified based on lexical diversity and syntactic complexity. Children also completed norm-referenced receptive language measures (i.e., Comprehensive Assessment of Spoken Language-2, age-appropriate Clinical Evaluation of Language Fundamentals) during the home visit that were combined into a composite measure of child receptive language. When caregivers used lower to moderate levels of lexical diversity, child effortful control was positively related to child receptive language. However, when caregivers used higher levels of lexical diversity, child effortful control and child receptive language were not related to each other. Family environments rich in caregiver lexical input to children might provide a protective influence on DHH child language outcomes by helping to ensure DHH children with varying self-regulatory abilities achieve better spoken language comprehension. These findings highlight the importance of encouraging caregivers to provide rich and stimulating language-learning environments for DHH children.

The impact of dialect differences on spoken language comprehension

AbstractResearch has suggested that children who speak African American English (AAE) have difficulty using features produced in Mainstream American English (MAE) but not AAE, to comprehend sentences in MAE. However, past studies mainly examined dialect features, such as verbal -s, that are produced as final consonants with shorter durations when produced in conversation which impacts their phonetic saliency. Therefore, it is unclear if previous results are due to the phonetic saliency of the feature or how AAE speakers process MAE dialect features more generally. This study evaluated if there were group differences in how AAE- and MAE-speaking children used the auxiliary verbs was and were, a dialect feature with increased phonetic saliency but produced differently between the dialects, to interpret sentences in MAE. Participants aged 6, 5–10, and 0 years, who spoke MAE or AAE, completed the DELV-ST, a vocabulary measure (PVT), and a sentence comprehension task. In the sentence comprehension task, participants heard sentences in MAE that had either unambiguous or ambiguous subjects. Sentences with ambiguous subjects were used to evaluate group differences in sentence comprehension. AAE-speaking children were less likely than MAE-speaking children to use the auxiliary verbs was and were to interpret sentences in MAE. Furthermore, dialect density was predictive of Black participant’s sensitivity to the auxiliary verb. This finding is consistent with how the auxiliary verb is produced between the two dialects: was is used to mark both singular and plural subjects in AAE, while MAE uses was for singular and were for plural subjects. This study demonstrated that even when the dialect feature is more phonetically salient, differences between how verb morphology is produced in AAE and MAE impact how AAE-speaking children comprehend MAE sentences.

Between alpha and gamma oscillations: Neural signatures of linguistic predictions and listener's attention to speaker's communication intention

When listeners hear a message produced by their interlocutor, they can predict upcoming words thanks to the sentential context and their attention can be focused on the speaker's communication intention. In two electroencephalographical (EEG) studies, we investigated the oscillatory correlates of prediction in spoken-language comprehension and how they are modulated by the listener’s attention. Sentential contexts which were strongly predictive of a particular word were ended by a possessive adjective either matching the gender of the predicted word or not. Alpha, beta and gamma oscillations were studied as they were considered to play a crucial role in the predictive process. While evidence of word prediction was related to alpha fluctuations when listeners focused their attention on sentence meaning, changes in high-gamma oscillations were triggered by word prediction when listeners focused their attention on the speaker's communication intention. Independently of the endogenous attention to a level of linguistic information, the oscillatory correlates of word predictions in language comprehension were sensitive to the prosodic emphasis produced by the speaker at a late stage. These findings thus bear major implications for understanding the neural mechanisms that support predictive processing in spoken-language comprehension.