Word List Research Articles

Word-level reading skills of Brazilian children with developmental language disorder

ABSTRACT Children with Developmental Language Disorder (DLD) show a wide range of impairments, including poor pre-reading skills and decoding difficulties due to phonological deficits and such difficulties have significant repercussions on the acquisition of written language. However, evidence about reading processes and development is mainly available for English-speaking children with DLD, limiting our understanding of this process in a cross-linguistic manner. The orthographic characteristics of languages significantly influence the learning process of written code. Unlike English, Brazilian Portuguese has a transparent decoding system and its orthography presents a set of consistent, univocal grapheme-phoneme relations. The present study investigated whether the challenges reported in decoding for children with DLD in opaque languages hold for children with DLD who are speakers of Brazilian Portuguese and whether the length and type of stimuli influence the decoding skills of children with DLD differently than when compared to children with typical language development (TLD). Sixteen children with DLD between seven and ten years of age who are monolingual speakers of Brazilian Portuguese and 64 controls with TLD matched by gender, age, and socioeconomic status, with the children with DLD in a 4:1 ratio; participated in the study. All children performed a computerized task where they were asked to decode a linguistically balanced list of words and nonwords designed according to Brazilian Portuguese decoding rules. The present study provides substantial evidence that children with DLD who are speakers of Brazilian Portuguese have deficits in the acquisition of decoding and that the decoding profile of children with DLD is subject to multiple influences, not only with relation to the length and type of stimuli but also characteristics of the languages these children are being literate in, highlighting the multifactorial nature involved in the development of decoding.

A - 21 Sex Differences in Cortical Thickness and Cognition in Individuals with Autosomal Dominant Alzheimer's Disease.

Cortical thinning is a marker of neurodegeneration. Individuals with autosomal dominant Alzheimer's disease (ADAD) develop early-onset dementia with virtually 100% certainty. Cortical thickness fluctuates across the ADAD lifespan, from early-life increased thickness to atrophy proximal to clinical onset. Females have higher cortical thickness and better cognition than males as they age. We examined sex differences in cortical thickness and cognitive performance in adults with ADAD. We assessed 85 Presenilin-1 E280A mutation carriers (74 cognitively-unimpaired, 11 mildly-impaired) from the Colombia-Boston Biomarker Study of ADAD. Mean age was 35.7 (SD = 10), education 10.2 (SD = 9), and 55 were female. Global cognition was measured using Mini-Mental State Examination (MMSE), and memory using CERAD Word List Delayed Recall. Participants underwent structural brain MRI. T-tests assessed between-group differences. Pearson correlations examined associations between cortical thickness and cognition. There were no sex differences in cortical thickness or cognitive performance (all ps > =0.05). For carriers, greater cortical thickness was associated with higher MMSE (r = 0.40, p < 0.001) and memory recall scores (r = 0.43, p < 0.01). Female carriers drove this effect, where greater cortical thickness was associated with higher MMSE (r = 0.46, p < 0.001) and memory recall scores (r = 0.47, p < 0.001); these associations were non-significant in male carriers alone. In cognitively-unimpaired female carriers, increased cortical thickness was associated with worse MMSE (r = -0.44, p < 0.001). We found sex differences in the relation between cortical thickness and cognition in ADAD carriers, which may be relevant to the differential vulnerability and progression of ad in females and males. Future work should investigate potential underlying mechanisms contributing to this sex difference.

Lexical Demands of Academic Written English: From Students’ Assignments to Scholarly Publications

The article presents a lexical study that investigates the lexical demands of academic written texts at different levels of writing. By employing the British National Corpus/ Corpus of Contemporary American English (BNC/COCA) word list and the Academic Word List (AWL), the present study analyzed data from the British Academic Written English (BAWE) corpus, which contained 2,761 student assignments, and the Public Library of Science One (PLOS ONE) corpus which included 4,000 scholarly articles. Results from the analyses demonstrated significant differences in lexical difficulty between students’ assignments and scholarly publications. The proportion of academic vocabulary in written texts was also found to increase as the writers’ levels went up. Cross-discipline comparisons highlighted the difference in lexical difficulties between scientific disciplines.

The Informativeness of Sentiment Types in Risk Factor Disclosures: Evidence from Firms with Cybersecurity Breaches

ABSTRACT This study examines the degree to which Loughran and McDonald (LM) word lists are informative at the item level of SEC filings, such as risk factors (RF) and management’s discussion and analysis (MDA) disclosures in 10-X reports. In this context, we explore if sentiment types are informative when associated with other material events, namely cybersecurity breaches. Our results support the assertion that sentiment types, beyond positive and negative, are informative at the individual disclosure item level, as tested in the RF and MDA sections. We also find that investors respond to different types of sentiment between RF and MDA. We find an economically significant estimated average economic impact of $469 million/firm. We further contribute to the literature by applying novel statistical methods that advance empirical accounting literature. Data Availability: Data are available from the public sources cited in the text.

The lexical representation of coda /t/ by 14-month-olds

We evaluated 14-month-olds’ lexical representation of coda /t/. Pronunciation variation of /t/, one of the most frequent segments in English, is well documented. Crucially, in American English infant-directed speech, /t/s are most often produced as glottal stops. This is particularly the case in word-final position, where words like cat and night are produced as [kæʔ] and [naiʔ] around 42% of the time, but produced with word-final canonical stop consonants (e.g., [kæt] or [nait]) only 25% of the time. In Experiment 1, we found that infants preferred to listen to familiar monosyllabic words ending in glottal stops (like [kæʔ]) when compared to nonce words ([kɪp]). This suggests that infants encode the most frequently occurring variant in their lexical entries. We are now testing whether the preference for familiar words produced with a glottal stop in Experiment 1 is the result of coda underspecification or encoding of glottal stop. If codas are underspecified in infant’s lexical representations, we expect no preference between lists of familiar words with glottal stops ([kæʔ]), compared to minimal pairs with coda mispronunciations ([kæk]). We will discuss implications of these findings for infants’ developing lexical representations and knowledge of allophony, focusing on the contribution of input frequency.

Gestural timing in naïve listener imitation of Cantonese vowels

Studies of nonnative vowel production have analyzed sounds predominantly in terms of acoustics, while the underlying articulatory gestures, as well as their timing, remain understudied. This study examines nonnative production of backness and rounding contrasts in the Cantonese vowel sets /i y u/ and /ɛ œ ɔ/. 15 native Cantonese speakers and 15 native English speakers participated. Native English speakers read a list of English words containing the vowels [i u ɪ ʊ e o ɛ ɔ], and then imitated Cantonese words containing [i y u ɪ ʊ ɛœ ɵ ɔ], presented auditorily. L1 Cantonese speakers produced the same set of Cantonese words, presented orthographically. Dynamic acoustic, ultrasound, and lip video data were collected and analyzed using GAMMs. In L1 Cantonese, target tongue and lip positions are achieved at vowel onset and maintained throughout the vowel duration, yielding acoustically monophthongal vowels. In contrast, L1 English [u, o] exhibit peak rounding during the vowel offglide, while magnitude of tongue and F2 displacement vary according to consonantal context. Lip gestures show similar late timing in non-native imitations of Cantonese [y, u], yielding English-like F2 trajectories, although the two vowels differed in tongue position. These results suggest that acoustically non-native-like vowel productions may result in part from transfer of L1 gestural timing. [Work supported by Hong Kong RGC, No. 27614421.]

Similarities between South Korea and Tamil Nadu: The Unknown Link

Tamil is one of the ancient languages which has an oldest extant literature. It is one of the longest surviving Dravidian languages dated from 300 BC. Korean is the native language for about 80 million people all over the world. Modern Korean was developed by King Sejong the Great in the 15th century. While analyzing the Tamil and Korean scripts, there was a certain amount of similarity in both text and grammar of these two languages. Despite the geographical separation of these two peninsulas, they share a considerable extent of literature and cultural resemblance. Hence, this proposed work provides a proof for the similarity with the help of a theoretical research study. This work portrays a list of words taken from Korean and Tamil Literature as samples and classifies them as complete or partial based on their similarity. It also lists verbs which after conjugation have a lexical similarity.

Reduced vowel space in video conferences via Zoom: Evidence from read speecha).

This exploratory study compared vowel space area (VSA) in face-to-face situations and video conference situations using the software Zoom. Twenty native German participants read word lists recorded before and after spontaneous conversation. The overall VSA in Zoom was reduced significantly by 11.9%, with a more reduced VSA before and less reduction after the spontaneous conversation. Of nine peripheral vowels in German, /aː iː yː/ showed a significantly reduced Euclidean distance to the centroid of the vowel space. The observed hypoarticulation is discussed in light of the experimental setup, situational differences, and less involvement in Zoom than in face-to-face situations.

Comorbid cerebral amyloid angiopathy in dementia and prodromal stages-Prevalence and effects on cognition.

To determine the contribution of cerebral amyloid angiopathy to cognitive impairment in MCI and dementia. Patients with subjective memory impairment (SMI), amnestic and non-amnestic mild cognitive impairment ((n)aMCI), Alzheimer's disease (AD), mixed and vascular dementia (MD/VD) from our memory clinic were included in this retrospective analysis. Patients underwent neuropsychological testing and cranial magnetic resonance imaging (MRI). Magnetic resonance imaging data sets were analyzed regarding the presence of CAA-related MRI biomarkers to determine CAA prevalence. ANOVAs were used to investigate the contribution of CAA to cognitive impairment within diagnostic groups and to determine whether differences in cognitive test performance between the diagnostic groups are mediated by total CAA burden. 475 patients (222 male, 253 female) with SMI (n=47), naMCI (n=41), aMCI (n=189), early AD (n=9), AD (n=114), MD (n=71) and VD (n=4) were included. Mean age was 73.2 (9.9) years. CAA prevalence was 14.9% in SMI, 14.6% in naMCI, 24.3% in aMCI, 22.2% in early onset AD, 18.4% in late onset AD, 46.5% in MD and 25% in VD. Patients with possible and probable CAA were older than patients without CAA. In particular, diagnosis of aMCI, early onset AD, MD and VD showed high CAA prevalence. In AD but not in aMCI, CAA diagnosis significantly influenced test performance in the CERAD word list recall (F (1,78)=4505; p=0.037; partial eta-square=0.055). Differences in cognitive test performance between the diagnostic groups of naMCI, aMCI, AD and MD were mediated by total CAA burden within AAT simply nouns subtest (F (2,39)=4059; p=0.025; partial eta-square=0.172) and in CERAD verbal fluency test (F (3,129)=3533; p=0.017; partial eta-square=0.076). This retrospective analysis demonstrates high prevalence rates of CAA in cognitive diagnoses. Our data suggest that comorbid CAA independently impacts cognitive test performance in the course of AD with presumably stage-dependent effects. Especially in patients with AD comorbid CAA additionally impairs memory function. Total CAA small vessel disease burden further modulates psychometric differences in cognitive test performance between diagnostic groups regarding word finding and word fluency capabilities.

Developing and validating a mid-frequency word list for chemistry: a corpus-based approach using big data

Given the importance of specialized vocabulary in scientific communication and academic discourse, there is a growing need to create wordlists to address the vocabulary-learning needs of university students and researchers in different subject areas. The current study analyzed a corpus of chemistry research articles (with 278 million running words) to establish a mid-frequency vocabulary list for this field. Using frequency, range, and dispersion criteria, the study identified 560 lemmas in the fourth to the ninth British National Corpus/Corpus of Contemporary American English (BNC/COCA) lists that provided 6.4% coverage of all words in the corpus. The list was validated using specialized and general corpora, and the results confirmed the value and relevance of the items for chemistry. Moreover, for using the list for pedagogical goals, the vocabulary items were divided into five bands based on their coverage and importance. The 100 words in the first band were the most important mid-frequent vocabulary in chemistry, as they provided 3.05% coverage. The study highlights the significant contribution of mid-frequency words in research articles and the findings have implications for using large corpora as a big data source in identifying specialized and field-specific vocabulary.

Cross-linguistic realization of lateral ejective affricates in connected versus isolated speech

Typological research on ejectives has focused on the realization of stops in isolated speech (Kingston 1985, Lindau 1984). However, there has been little research on the realization of ejectives, and in particular affricates, in connected versus isolated speech. Given that lateral affricates can be produced with variable realization, this study compares the acoustics of [tɬ’] in isolated and connected speech for speakers of three languages: Lushootseed (Coast Salish), Hul’q’umi’num’ (Coast Salish), and Dene Kədə́ (Dene/Athabaskan). Duration, spectral moment, and voice quality measurements were examined from corpus data of word lists and connected speech. Results indicated that there was greater voice onset time (VOT), longer closure duration, and a smaller frication duration to VOT ratio in isolated speech than connected speech, supporting Lindblom’s (1990) and Farnetani &amp; Recasens’ (2013) view that words are produced more hyperarticulated in isolated speech. Cross-linguistic differences were found in the duration of frication, center of gravity, and the rise to peak amplitude of the following vowel. Dene Kədə́ had greater frication duration and a shallower intensity slope than the Salish languages, indicators of differences in place of articulation and degree of affrication. This suggests different realizations of [tɬ’] across languages.

Introducing MultilingProfiler: An adaptable tool for analysing the vocabulary in French, German, and Spanish texts

Vocabulary profiling with computational tools and word lists is an established step in the development of pedagogical materials for learners of English. However, existing tools and word lists lack sensitivity to the orthographical, morphological, and grammatical systems of highly-inflected and declined languages. This limits the degree to which lexical profiling can be usefully implemented in the creation of materials intended for use with beginner/low-intermediate learners of such languages who have only partial knowledge of these systems.In this article, we present MultilingProfiler, a vocabulary profiling tool designed to support nuanced profiling of texts in French, German, and Spanish. We introduce the concept of ‘bespoke’ word families tailored to the needs of learners at various stages of development, and outline key features of the tool that operationalise this concept (the functionality to select which inflected, derived, and multiword forms of headwords are included in the profile; sensitivity to orthographical systems; embedded word lists aligning with specific programs of study; and cumulative word lists that grow with learner knowledge). We present two case studies that find MultilingProfiler's features to be effective in highlighting potential mismatches between the lexical demands of texts and the expected knowledge of learners, and consider applications of the tool in research methods.

한·중 대등합성어 대조 연구

The purpose of this study is to examine the corresponding types of Korean-Chinese equivalent compound words based on a list of Korean equivalent compound words derived from the literature research method. To this end, a total of 34 Korean equivalent compound words that are educationally meaningful for Chinese learners were selected based on the Korean learning vocabulary list of the National Language Institute in Korea. Next, the list of Korean equivalent compound words was categorized into three types: 8 complementary compound words, 16 contiguous compound words, and 10 overlapping compound words. Finally, the corresponding types of Korean-Chinese equivalent compound words were presented in nine different cases. This study is significant in that it compiled a list of Korean equivalent compound words that differ from Chinese equivalent compound words based on the semantic relationships of the components, and further analyzed the corresponding types of KoreanChinese equivalent compound words in nine detailed cases.

Corpus-Based Approach to Sociolinguistic Study of Offensive Words: Gender, Time and Register Differences

The unpleasant expressions (offensiveness) always emotionally affect to the human psyches, and exists in all languages in less or strong degrees and directly or indirectly. Therefore, this study aimed to investigate over the changes of them by corporally-derived data and their registers, times and genders were the pilot targets. BNC and COCA Corpora were put for data collections while the list of previous insulting words was selected to reuse, especially the ones with highest frequencies. The results suggested 4 words damn, shit, fuck and dick had the highest degrees of uses but those from BNC were comparatively fewer than the rest. Moreover, the top four were emerged up to the different periods of times and contexts while men used them considerably more often than the women did.

Оценка достовернности данных о возрасте усвоения слов, получаемых путем опроса взрослых респондентов

Given the difficulty to establish an objective measure of age of acquisition (AoA), this study focuses on the subjective measures of this parameter, i.e., adult ratings, or judgment of word learning age. The question under study is the validity of subjective adult estimates of AoA as a standard norming tool for this characteristic in Russia. AoA estimates were gathered for 7,500 words by presentation to eight hundred participants. The latter were given 25 lists of words with the instruction to specify supposed age of their acquisition. A total of 179,100 estimates collected from 597 participants were included in the analysis (from 20 to 30 protocols on each list). The middle age of the participants was 20.50±3.84 years, with 96% of them being at the age of 17–25 years old. Objective estimates were received through the examination of school children from the 2nd, 4th, 6th and 8th grade by means of the dictionary-type tests. The words for each test were selected so that their subjective AoAs were nearest to the actual age of students. Total number of generated tasks amounted to 720. The subset of test items for each grade was divided into two subtests equated on complexity. The subtest length varied from 80 (for the 2nd grade) to 150 (the 6th and 8th grades) tasks. Reliability of subtest scores varied in a range of 0.85–0.95. The comparison of subjective and objective estimates was carried out in several ways, first of all, by calculating the correlation coefficients between subjective AoA of test words and accuracy of their identification. After appropriate correction on direct range restriction of subjective AoA variation, corrected correlations in a range of 0.6–0.9 (0.79 on average) were received. This figure (along with the additional data) allows to draw a conclusion on a reasonable validity of subjective estimates of AoA as a norming tool for this characteristic. The article outlines the prospects for further research of factors influencing accuracy of adult estimates of word learning age in Russia.

A study of the inclusion of Chinese characters in the HNK word list

A study of the inclusion of Chinese characters in the HNK word list

The 10-Word Auditory Verbal Learning Test and Vocabulary Performance in 4- and 5-Year-Old Children.

Understanding the different factors that determine vocabulary development in young children is essential for the diagnosis and rehabilitation of language disorders in children. Language development is closely related to other cognitive processes such as auditory verbal learning and memory. This research focuses on the development of a novel auditory verbal learning test (AVLT) for 4- and 5-year-old children within the Dutch population. This new test is an adaptation of the common AVLT for both older children and adults, usually including a list of 15 words. Considering the lower attention span and limited executive functioning in young children, the word list of this new instrument is reduced to 10 words. Besides, a second recognition form has been developed to improve the ability to distinguish between possible underlying learning and memory deficits. Ninety-five preschool children (ages 4;0-5;12 [years;months]) were tested with this new AVLT 10-word test for kids (10WT-K), yielding different measures of verbal auditory memory. Forty-eight of 95 children received a recognition task with semantically unrelated items, and 47 of 95 received a recognition task with semantically related items. Three additional language skills were assessed to establish test validation: receptive and expressive vocabulary performance and nonword repetition. Outcome of the 10WT-K was related to scores on the language measures. Positive correlations were found between the total score of the 10WT-K and all three aforementioned language skills. We found no correlations between frequency of error types (intrusions and repetitions) and language measures. Furthermore, children who were administered the recognition list with semantically related items showed fewer correct answers and more false-positive and false-negative responses than children who received a recognition list with semantically unrelated items. The 10WT-K for young children can be used to (a) measure different aspects of auditory verbal learning and memory, (b) clarify the nature of possible verbal learning difficulties, and (c) identify a possible nature of language disorders. The word recognition task tested with semantically related items provides a more accurate measurement of individual differences, namely, in distinguishing retrieval and storage abilities. The significant relation found between auditory verbal short-term memory capacity and vocabulary performance in preschool children is a first step toward establishing test validity.

Defining Semantically Close Words of Kazakh Language with Distributed System Apache Spark

This work focuses on determining semantically close words and using semantic similarity in general in order to improve performance in information retrieval tasks. The semantic similarity of words is an important task with many applications from information retrieval to spell checking or even document clustering and classification. Although, in languages with rich linguistic resources, the methods and tools for this task are well established, some languages do not have such tools. The first step in our experiment is to represent the words in a collection in a vector form and then define the semantic similarity of the terms using a vector similarity method. In order to tame the complexity of the task, which relies on the number of word (and, consequently, of the vector) pairs that have to be combined in order to define the semantically closest word pairs, A distributed method that runs on Apache Spark is designed to reduce the calculation time by running comparison tasks in parallel. Three alternative implementations are proposed and tested using a list of target words and seeking the most semantically similar words from a lexicon for each one of them. In a second step, we employ pre-trained multilingual sentence transformers to capture the content semantics at a sentence level and a vector-based semantic index to accelerate the searches. The code is written in MapReduce, and the experiments and results show that the proposed methods can provide an interesting solution for finding similar words or texts in the Kazakh language.

Examining Letter Detector Tolerance through Offset Letter Halves: Evidence from Lexical Decision.

Neurobiological models of reading assume that the specialized detectors at the letter level (e.g., the arrays of detectors for the letter 'n') possess a certain degree of tolerance (e.g., Local Combination Detectors model, Dehaene et al. 2005). In this study, we designed two lexical decision experiments that examined the limits of tolerance of letter detectors by introducing a novel manipulation involving shifting letter halves (e.g., in Experiment 1; in Experiment 2) relative to intact items. This manipulation alters the transition between upper and lower parts of the letters, adding junctions that do not exist in the intact letter forms. We included high- and low-frequency words in the stimulus list to investigate whether letter distortion affects processing beyond the letter level, reasoning that interactive effects would signal top-down lexical feedback. In Experiment 1, which employed a subtle letter shift, we observed a minimal cost of letter distortion that did not interact with word frequency. Experiment 2, employing a larger letter shift, revealed an overall greater reading cost that affected differentially high- and low-frequency words. Overall, these findings offer insights into the limits of resilience in letter detectors to distortion during word recognition and introduce a novel manipulation of letter distortion.

Post-processing automatic transcriptions with machine learning for verbal fluency scoring

ObjectiveTo compare verbal fluency scores derived from manual transcriptions to those obtained using automatic speech recognition enhanced with machine learning classifiers. MethodsUsing Amazon Web Services, we automatically transcribed verbal fluency recordings from 1400 individuals who performed both animal and letter F verbal fluency tasks. We manually adjusted timings and contents of the automatic transcriptions to obtain “gold standard” transcriptions. To make automatic scoring possible, we trained machine learning classifiers to discern between valid and invalid utterances. We then calculated and compared verbal fluency scores from the manual and automatic transcriptions. ResultsFor both animal and letter fluency tasks, we achieved good separation of valid versus invalid utterances. Verbal fluency scores calculated based on automatic transcriptions showed high correlation with those calculated after manual correction. ConclusionMany techniques for scoring verbal fluency word lists require accurate transcriptions with word timings. We show that machine learning methods can be applied to improve off-the-shelf ASR for this purpose. These automatically derived scores may be satisfactory for some applications. Low correlations among some of the scores indicate the need for improvement in automatic speech recognition before a fully automatic approach can be reliably implemented.