Search Results (75)

Filled pauses are thought to be reflections of linguistic processes (e.g., lexical retrieval, speech planning and execution). Uh may be a self-directed cue for when a speaker needs more time to retrieve lexical–semantic representations, whereas um serves as a listener-directed, pragmatic cue. The use of filled pauses has not been examined in children who are hard of hearing (CHH). Participants included 68 CHH and 33 children with typical hearing (CTH). Participants engaged in conversations, expository discourse, and fable retells. We analyzed filled pauses as a function of hearing status and discourse contexts and evaluated the relationship between filled pauses and language ability. CHH produced uh across discourse contexts more often than their hearing peers. CHH did not differ in their use of um relative to CTH. Both um and uh were used more often in conversational samples compared to other types of discourse. Spearman’s correlations did not show any significant associations between the rate of filled pauses and standardized language scores. These results indicate that CHH produces uh more often than CTH, suggesting that they may have difficulty retrieving lexical–semantic items during ongoing speech. This information may be useful for interventionists who are collecting language samples during assessment. Full article

Effective language processing relies on pattern detection. Spanish monolinguals predict verb tense through stress–suffix associations: a stressed first syllable signals present tense, while an unstressed first syllable signals past tense. Low-proficiency second language (L2) Spanish learners struggle to detect these associations, and we investigated whether they benefit from game-based training. We examined the effects of four variables on their ability to detect stress–suffix associations: three linguistic variables—verbs’ lexical stress (oxytones/paroxytones), first-syllable structure (consonant–vowel, CV/consonant–vowel–consonant, CVC), and phonotactic probability—and one learner variable—working memory (WM) span. Beginner English learners of Spanish played a digital game focused on stress–suffix associations for 10 days and completed a Spanish proficiency test (Lextale-Esp), a Spanish background and use questionnaire, and a Corsi WM task. The results revealed moderate gains in the acquisition of stress–suffix associations. Accuracy gains were observed for CV verbs and oxytones, and overall reaction times (RTs) decreased with gameplay. Higher-WM learners were more accurate and slower than lower-WM learners in all verb-type conditions. Our findings suggest that prosody influences word activation and that digital gaming can help learners attend to L2 inflectional morphology. Full article

Readability formulas are mathematical functions that assess the ‘difficulty’ level of a given text. They play a crucial role in aligning educational texts with student reading abilities; however, existing models are often not tailored to specific linguistic or regional contexts. This study aims to develop and evaluate two novel readability formulas specifically designed for the Mexican Spanish language, targeting elementary education levels. The formulas were trained on a corpus of 540 texts drawn from official elementary-level textbooks issued by the Mexican public education system. The first formula was constructed using multiple linear regression, emulating the structure of traditional readability models. The second was derived through genetic programming (GP), a machine learning technique that evolves symbolic expressions based on training data. Both approaches prioritize interpretability and use standard textual features, such as sentence length, word length, and lexical and syntactic complexity. Experimental results show that the proposed formulas outperform several well-established Spanish and non-Spanish readability formulas in distinguishing between grade levels, particularly for early and intermediate stages of elementary education. The GP-based formula achieved the highest alignment with target grade levels while maintaining a clear analytical form. These findings underscore the potential of combining machine learning with interpretable modeling techniques and highlight the importance of linguistic and curricular adaptation in readability assessment tools. Full article

In this cohort study, we evaluated the cognitive and learning difficulties of school-age children perinatally infected with Chikungunya virus (CHIKV) on Reunion Island using the Evaluation of Cognitive Functions and Learning in Children (EDA) battery screening test compared to the healthy children cohort used for EDA development. Of the 19 infected children, 11 (57.9%) exhibited subnormal or abnormal scores, of whom 3 were classified as high risk, and 8 were classified as at risk for cognitive and learning difficulties. Children who had encephalopathy were at higher risk for displaying at least one difficulty than non-encephalopathic children (relative risk 2.13; 95% CI 1.05–4.33). The difficulties observed affected verbal functions, non-verbal functions, and learning abilities, such as phonology, lexical evocation and comprehension, graphism, selective visual attention, planning, visual–spatial reasoning, dictation and mathematics, as well as core executive functions, such as inhibitory control, shifting, and working memory. Neurocognitive dysfunctions could be linked to severe brain damage, as evidenced by severe white matter reduction mainly in the frontal lobes and corpus callosum and potentially in all functional networks involved in difficulties. These results should motivate further investigation of intellectual and adaptive functioning to diagnose intellectual deficiency and severe maladaptive behaviour in children perinatally infected with Chikungunya virus. Full article

Background: Primary progressive aphasia (PPA) is a neurodegenerative disorder that worsens over time without appropriate treatment. Although referral to a speech and language pathologist is essential for diagnosing language deficits and developing effective treatment plans, there is no scientific consensus regarding the most effective treatment. Thus, our study aims to assess the efficacy and safety of various therapeutic interventions for PPA. Methods: Google Scholar, PubMed, Web of Science, and the Cochrane Library databases were systematically searched to identify articles assessing different therapeutic interventions for PPA. To ensure comprehensive coverage, the search strategy employed specific medical subject headings. The primary outcome measure was language gain; the secondary outcome assessed overall therapeutic effects. Data on study characteristics, patient demographics, PPA subtypes, therapeutic modalities, and treatment patterns were collected. Results: Fifty-seven studies with 655 patients were included. For naming and word finding, errorless learning therapy, lexical retrieval cascade (LRC), semantic feature training, smartphone-based cognitive therapy, picture-naming therapy, and repetitive transcranial magnetic stimulation (rTMS) maintained effects for up to six months. Repetitive rTMS, video-implemented script training for aphasia (VISTA), and structured oral reading therapy improved speech fluency. Sole transcranial treatments enhanced auditory verbal comprehension, whereas transcranial direct current stimulation (tDCS) combined with language or cognitive therapy improved repetition abilities. Phonological and orthographic treatments improved reading accuracy across PPA subtypes. tDCS combined with speech therapy enhanced mini-mental state examination (MMSE) scores and cognitive function. Several therapies, including smartphone-based cognitive therapy and VISTA therapy, demonstrated sustained language improvements over six months. Conclusions: Various therapeutic interventions offer potential benefits for individuals with PPA. However, due to the heterogeneity in study designs, administration methods, small sample sizes, and lack of standardized measurement methods, drawing a firm conclusion is difficult. Further studies are warranted to establish evidence-based treatment protocols. Full article

The present study aimed to enhance the understanding of the spelling processes used by young German-speaking learners of English as a foreign language (EFL). Specifically, we sought to (1) compare the children’s accuracy in spelling English real words versus pseudowords to elucidate the role of lexical and sublexical knowledge, and (2) determine which cognitive (phonological awareness, phonological short-term memory, working memory, nonverbal intelligence) and linguistic skills (English receptive grammar and vocabulary) underlie learners’ spelling abilities and misspellings (phonological and orthographic). We followed participants (N = 101) for two years, from the beginning of grade 3 to the end of grade 4. Cognitive skills and linguistic abilities were determined using standardized assessment procedures. Our results indicate that the learners in our study demonstrated greater accuracy in spelling English real words compared to pseudowords. English grammar knowledge significantly predicted real word and pseudoword spelling accuracy, as well as the number of phonological errors, which was the predominant error category. English vocabulary knowledge was a predictor for real word spelling, while nonverbal intelligence predicted pseudoword spelling accuracy. Phonological short-term memory positively predicted the number of orthographic errors (phonologically plausible misspellings but lacking orthographic conventions). Full article

In linguistically diverse and multilingual South African communities, it is common to use non-standard language varieties (NSLVs), often called mixed languages, as lingua franca. These NSLVs are primarily spoken in black townships throughout South Africa. Previous studies show that the discursive production of oral narratives impacts the development and use of higher-order language processing, as they require the knowledge, language skills and abilities to produce coherent discourse. The main focus of the existing literature in oral narrative is mostly on standard languages. In this study, we explore how speakers of Sepitori, a non-standard language variety (NSLV), produce an oral narrative compared to Sesotho, a standard language. The current study investigates the oral narrative production of a total number of 20 participants who are adult speakers of Sesotho and Sepitori (ten from each language). The Sesotho speakers were bilingual speakers of English and Sesotho. The Sepitori speakers were multilingual speakers of English, Sesotho, Zulu and other languages spoken in the Mamelodi township. This study used a mixed methodology of quantitative and qualitative analysis. Narratives were annotated for language complexity in the macro- and microstructure elements: the length and type of clause, pragmatic acts, referential lexical choices and code-switched words. Sepitori speakers produced narratives characterised by interactive clauses unrelated to the narrative level and with a greater range of lexical referents, showcasing more individual linguistic variation. Sesotho speakers produced a more sequential oral narrative in line with story schema with fewer interjections to the researcher. In an increasingly linguistically heterogeneous South Africa, more research is required to gain insights into how multilingual individuals develop and refine their narrative skills, emphasising the much-needed focus on NSLV from a psycholinguistic perspective, which may ultimately inform tools of assessment for multilingual children and adults in social, clinical and academic contexts. Full article

Situation types can be viewed as the foundation of representation of sentence meaning. Noting that situation types cannot be determined by verbs alone, recent studies often focus on situation type prediction in terms of the combination of different linguistic constituents at the sentence level instead of lexically marked situation types. However, in languages with a fully marked aspectual system, such as Mandarin Chinese, such an approach may miss the opportunity of leveraging lexical aspects as well as other distribution-based lexical cues of event types. Currently, there is a lack of resources and methods for the identification and validation of the lexical aspect, and this issue is particularly severe for Chinese. From a computational linguistics perspective, the main reason for this shortage stems from the absence of a verified lexical aspect classification system, and consequently, a gold-standard dataset annotated according to this classification system. Additionally, owing to the lack of such a high-quality dataset, it remains unclear whether semantic models, including large general-purpose language models, can actually capture this important yet complex semantic information. As a result, the true realization of lexical aspect analysis cannot be achieved. To address these two problems, this paper sets out two objectives. First, we aim to construct a high-quality lexical aspect dataset. Since the classification of the lexical aspect depends on how it interacts with aspectual markers, we establish a scientific classification and data construction process through the selection of vocabulary items, the compilation of co-occurrence frequency matrices, and hierarchical clustering. Second, based on the constructed dataset, we separately evaluate the ability of linguistic features and large language model word embeddings to identify lexical aspect categories in order to (1) verify the capacity of semantic models to infer complex semantics and (2) achieve high-accuracy prediction of lexical aspects. Our final classification accuracy is 72.05%, representing the best result reported thus far. Full article

Sociophonetic competence—a component of sociolinguistic and, thus, communicative competence—has been explored in both learner production and perception. Still, little is known about the relationship between learners’ ability to account for sociophonetic variability in the input and their likelihood to produce such variation in output. The present study explores 21 learners’ preference for a specific sociophonetic variant on an aural preference task and the same learners’ patterns of production of the variant in semi-spontaneous speech. The sociolinguistic variable considered is Spanish intervocalic /d/, variably realized as approximant [ð] or deleted based on numerous (extra)linguistic factors, including the speaker’s gender, the vowel that precedes /d/, and the grammatical category and lexical frequency of the word containing /d/. Results reveal that preference for and production of a deleted variant increased with learner proficiency. Moreover, regardless of proficiency, learners generally selected deleted /d/ more than they produced it, suggesting that sociophonetic awareness precedes reliable production. Learners’ production of a deleted variant was influenced by the preceding vowel, the grammatical category of the word containing /d/, and the word’s lexical frequency, and sensitivity to these predictors was especially observed as proficiency increased. Learners produced the deleted variant more after /o/, in adjectives and nouns, and in frequent words. Full article

In recent years, advancements in artificial intelligence, speech, and natural language processing technology have enhanced spoken dialogue systems (SDSs), enabling natural, voice-based human–computer interaction. However, discrete, token-based LLMs in emotionally adaptive SDSs focus on lexical content while overlooking essential paralinguistic cues for emotion expression. Existing methods use external emotion predictors to compensate for this but introduce computational overhead and fail to fully integrate paralinguistic features with linguistic context. Moreover, the lack of high-quality emotional speech datasets limits models’ ability to learn expressive emotional cues. To address these challenges, we propose EmoSDS, a unified SDS framework that integrates speech and emotion recognition by leveraging self-supervised learning (SSL) features. Our three-stage training pipeline enables the LLM to learn both discrete linguistic content and continuous paralinguistic features, improving emotional expressiveness and response naturalness. Additionally, we construct EmoSC, a dataset combining GPT-generated dialogues with emotional voice conversion data, ensuring greater emotional diversity and a balanced sample distribution across emotion categories. The experimental results show that EmoSDS outperforms existing models in emotional alignment and response generation, achieving a minimum 2.9% increase in text generation metrics, enhancing the LLM’s ability to interpret emotional and textual cues for more expressive and contextually appropriate responses. Full article

Background/Objectives: In a tonal language like Chinese, phonologically contrasting tones signify word meanings at the syllable level. Although the development of lexical tone perception ability has been examined in many behavioral studies, its developmental trajectory from childhood to adulthood at the neural level remains unclear. This cross-sectional study aimed to examine the issue by measuring the mismatch negativity (MMN) response to a Chinese lexical tonal contrast in three groups. Methods: The MMN response to a flat-falling tonal contrast (Tone1 versus Tone4) were recorded from children (25 participants aged 6–8), adolescents (26 participants aged 12–14), and young adults (20 participants aged 18–24). Nonsense speech stimuli were also used by superimposing Tone1 and Tone4 on an English syllable. Results: All three groups demonstrated typical early MMN responses in both the meaningful and nonsense syllable conditions. However, the MMN amplitudes varied significantly across groups, with the child group showing smaller responses compared to the adolescent and adult groups, while the latter two groups had similar MMN amplitudes. Conclusions: Neural sensitivity to tonal contrasts is not fully mature in children and reaches a more adult-like level during adolescence, with no significant difference in sensitivity to meaningful versus nonsense syllables. These results provide new insights into the neural development of lexical tone perception in a tonal language, highlighting its maturation during adolescence in this process. Full article

Background/Objectives: Narration is a sensitive tool for the assessment of language in children with high-functioning autism spectrum disorder (HF-ASD) since mild language deficits beyond the sentential level are not always noticeable through the administration of standardized language tests targeting the lexical or sentential level. This study investigated the narrative ability of monolingual Greek-speaking HF-ASD children in comparison to that of their typically developing (TD) peers and explored the associations between narrative variables, ADHD symptomatology, and memory skills in the participants on the autistic spectrum. Methods: The participants were 39 children aged 7 to 12 years, 19 with HF-ASD and 20 age-matched, vocabulary-matched, and cognitively matched TD peers. Results: The two groups were similar in most microstructural and macrostructural variables but differed significantly in syntactic complexity (p = 0.024; d = 0.754) and subordination (p < 0.001; d = −1.576) indices, implying that the HF-ASD group presented syntactic delay in comparison to their TD peers. The HF-ASD participants showed significantly higher heterogeneity in the amount of information generated for the story’s main character (p = 0.004; d = −0.093) in comparison to their TD peers. Significant associations were observed between verbal and visual memory, complex syntactic structures, and Theory of Mind-related internal state terms. ADHD symptomatology was negatively correlated with the generation of simple and coordinated clauses. Finally, complex syntax and delayed vSTM were correlated with retelling total scores, indicating that language ability and verbal memory compensate for narrative competence in HF-ASD children. Conclusions: The findings highlight the impact that language skills, memory ability, and ADHD symptomatology have on narrative competence in children with HF-ASD, as well as the importance of narrative use for assessing the language skills in populations with mild language impairment. Full article

Standardized assessment tools are essential for informed, data-driven decision-making. Reading speedily is a crucial early skill that all students should have the opportunity to develop in inclusive classrooms. To facilitate classroom-based reading diagnostics in this area of reading, we developed a flash reading test that reliably measures the performance of students with and without learning disabilities and intellectual disabilities. This test can be administered in the classroom and completed independently by students, taking only a few minutes, without requiring them to read aloud. The test is designed to provide an accurate assessment of the speed of lexical recall for all students. To evaluate the difficulty-generating-item characteristics of the new instrument, 400 primary and special school students participated in the test. The results indicate that students with low abilities and disabilities are particularly differentiated by the combination of a short display duration and short words. We provide information for test developers interested in designing similar assessments and teachers who can use this instrument to make informed decisions in the classroom. Full article

Background/Objectives: The present study examines the role of morphemic units in the initial word recognition stage among beginning readers. We assess whether and to what extent sublexical units, such as morphemes, are used in processing French words and how their use varies with reading proficiency. Methods: Two experiments were conducted to investigate the perceptual and morphological effects on the recognition of words presented in central vision, using a variable-viewing-position technique. To explore changes during elementary school years, we tested children from the second and fourth grades, as well as adult readers. Results: The percentage of correct word identification was highest near the center of the word, indicating an optimal viewing position for all three participant groups. Viewing position effects were modulated by age and the properties of the stimuli (length and morphological structure). Experiment 1 demonstrated that lexical decisions are influenced by morphological structure to a decreasing extent as reading skill develops. Experiment 2 revealed that morphological processing in children primarily relies on the orthographic information provided by morphemes (surface morphology), whereas proficient readers process morphological information at a more abstract level, exhibiting a genuine morphological-facilitation effect. Conclusions: Overall, our study strongly indicates that morphemic units play a crucial role in the initial stage of word identification in early reading development. This conclusion aligns with the “word and affix” model, which posits that morphological representations become increasingly independent of orthography as reading ability and word exposure improve. Full article

To cope with the challenges posed by the complex linguistic structure and lexical polysemy in ancient texts, this study proposes a two-stage translation model. First, we combine GujiBERT, GCN, and LSTM to categorize ancient texts into historical and non-historical categories. This categorization lays the foundation for the subsequent translation task. To improve the efficiency of word vector generation and reduce the limitations of the traditional Word2Vec model, we integrated the entropy weight method in the hopping lattice training process and spliced the word vectors with GujiBERT. This improved method improves the efficiency of word vector generation and enhances the model’s ability to accurately represent lexical polysemy and grammatical structure in ancient documents through dependency weighting. In training the translation model, we used a different dataset for each text category, significantly improving the translation accuracy. Experimental results show that our categorization model improves the accuracy by 5% compared to GujiBERT. In contrast, the Entropy-SkipBERT improves the BLEU scores by 0.7 and 0.4 on historical and non-historical datasets. Ultimately, the proposed two-stage model improves the BLEU scores by 2.7 over the baseline model. Full article