Linguistic Complexity Research Articles

Using Spontaneous Speech Recognition as a Biomarker to Distinguish Dementia Patients

AbstractBackgroundDigital biomarkers such as individual speech recordings, are a cost‐effective tool for assessing cognitive status using linguistic and acoustic content. The purpose of this study is to investigate whether Natural Language Processing (NLP) methods and audio feature extraction can distinguish spontaneous speech outputs in dementia patients from a healthy population.Method240 audio samples and transcripts of clinician‐participant dialogues involving the Cookie‐Theft visual description were acquired from the DementiaBank Pitt corpus (Dementia group (DG) n = 169; healthy controls (CG) n = 71). Lexical variety, syntactic complexity, salience of information, disfluency patterns, and sentiment analysis were evaluated. Sound synthesis and an acoustic R analysis package were used to filter and examine acoustic properties of recorded audio such as silence and speech segmentation, pitch tracking, and frequency modulation of vibrato or jitter. DG and CG were compared using non‐parametric Kruskal‐Wallis tests, Dunn’s multiple comparison, and Mann‐Whitney U‐test in the statistical analysis. In comparison to CG, we hypothesized that DG would differ in levels of lexical diversity, grammatical complexity, and overall salience.ResultOverall, text analysis showed no variations in disfluencies between groups, but there were significant differences in lexical diversity, syntactic complexity and reference rate to reality (p<0.0001). Additionally, there were no appreciable differences in the frequency of salient information between the two groups, however the frequency of non‐salient information and disfluencies was considerably higher in the DG (p<0.05). Analysis of acoustic features revealed that DG had longer average speech duration and speech segment durations compared to CG (p<0.001).. On the other hand, the rate of change of acoustic characteristics including pitch, mean entropy, and harmonics‐to‐noise ratios did not significantly differ between DG and CG.ConclusionIn conclusion, this paradigm reveals that, in comparison to healthy controls, dementia patients exhibited increased lexical diversity yet lower linguistic complexity, and a shift towards characterizing non‐salient objects in given stimuli, as well as longer segments of speech. Further examination of the rhythmic and acoustic characteristics of speech may provide a comprehensive framework towards defining speech as a potential digital biomarker for dementia risk, and provide applications to regions experiencing increasing socioeconomic disparities.

The Processing of English caused-motion construction by EFL learners

This article investigates the processing of English caused-motion constructions by Brazilian EFL learners. Drawing on corpus data on the production of such constructions by Brazilian learners, this study experimentally tests the four following constructional domains of caused motions discussed in Rosa (2020): (1) literal caused motions with instantiating verbs (e.g., put the toys into the box); (2) figurative caused motions with instantiating verbs (e.g., get yourself in trouble); (3) literal caused motions with modifying verbs (e.g., they laughed him out of the office); and (4) figurative caused motions with modifying verbs (e.g., she talked me into stupor). An acceptability judgment task with 120 EFL Brazilian learners at two levels of proficiency (B2 and C1) was devised so as to investigate the development of caused motions by testing two aspects and their effect on the comprehension of the structure: (1) level of proficiency, and (2) the degree of linguistic complexity of the structures in question. The results of the experimental study showed that learners’ proficiency level does affect their comprehension of the structures. However, the linguistic complexity of the structures seems to play an even greater role in that learners exhibit a descending level of comprehension of caused motions that is proportional with the ascending level of semantic and syntactic complexity of the structures.

Effects of speaker types and L1 backgrounds on the linguistic complexity of learners’ writing

AbstractThis study investigated the differences in linguistic complexity between different types of English users, including native speakers (NS), English as a foreign language (EFL) learners, and English as a second language (ESL) learners in terms of Kolmogorov complexity. Furthermore, we explored how first language backgrounds affect linguistic complexity. Our dataset contains 2272 argumentative essays produced by English NSs and upper‐intermediate learners from four ESL and six EFL countries/regions. Results showed that significant differences existed between the writings of NS, EFL, and ESL regarding overall and syntactic complexity. Specifically, the rank of overall complexity (NS > ESL > EFL) indicates that learners from countries/regions with higher exposure to English tend to produce overall more complex writings. Concerning syntactic complexity, EFL learners produce the most complex writings, while NS produces the least complex, indicating that essays written by EFL learners contain the most fixed word order patterns. In contrast, no significant difference was detected in morphological complexity among the NS, ESL, and EFL groups, suggesting that native and upper‐intermediate non‐NSs exhibit a similar range of morphological forms in their writings. Additionally, our results showed a larger effect of first language backgrounds over English speaker types on linguistic complexity, thus informing teachers to implement targeted writing instructions for learners from different countries.

Information Quality and Readability: ChatGPT's Responses to the Most Common Questions About Spinal Cord Injury

This study aimed to assess the quality, readability, and comprehension of texts generated by ChatGPT in response to commonly asked questions about spinal cord injury (SCI). The study utilized Google Trends to identify the most frequently searched keywords related to SCI. The identified keywords were sequentially inputted into ChatGPT, and the resulting responses were assessed for quality using the Ensuring Quality Information for Patients (EQIP) tool. The readability of the texts was analyzed using the Flesch-Kincaid grade level and the Flesch-Kincaid reading ease parameters. The mean EQIP score of the texts was determined to be 43.02±6.37, the Flesch-Kincaid reading ease score to be 26.24±13.81, and the Flesch-Kincaid grade level was determined to be 14.84±1.79. The analysis revealed significant concerns regarding the quality of texts generated by ChatGPT, indicating serious problems with readability and comprehension. The mean EQIP score was low, suggesting a need for improvement in the accuracy and reliability of the information provided. The Flesch-Kincaid grade level indicated a high linguistic complexity, requiring a level of education equivalent to approximately 14 to 15years of formal education for comprehension. The results of this study show heightened complexity in ChatGPT-generated SCI texts, surpassing optimal health communication readability. ChatGPT currently cannot substitute comprehensive medical consultations. Enhancing text quality could be attainable through dependence on credible sources, the establishment of a scientific board, and collaboration with expert teams. Addressing these concerns could improve text accessibility, empowering patients and facilitating informed decision-making in SCI.

Detecting Financial Statement Fraud through Multidimensional Analysis of Text Readability

ABSTRACT This study uses Coh-Metrix to analyze multiple dimensions of readability of the MD&A section of the SEC Form 10-K. We incorporate the five main Coh-Metrix components of text easability (word concreteness, syntactic simplicity, referential cohesion, deep cohesion, and narrativity) into a logistic model to test their predictive power for financial misreporting. We find that compared to the MD&As of nonfraud firms, the MD&As of fraud firms connect clauses and sentences less coherently, use more story-like language, and show a higher number of vague and abstract words. Thus, referential cohesion, narrativity, and word concreteness significantly enhance predictive ability in fraud detection. The Coh-Metrix readability measures enhance the linguistic complexity assessment beyond traditional readability measures, such as the Fog Index and the Flesch Indexes. Financial analysts and investors can utilize the Coh-Metrix readability measures to supplement traditional readability measures and common financial statement variables in predicting financial misreporting. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G32; K42; M41; M48.

Language Proficiency and the Relation to Word–Problem Performance in Emergent Bilingual Students with Mathematics Difficulties

As students enter the upper elementary grades, word problems become a main component of mathematics instruction, increasing in complexity as students advance through the curriculum. For students identified as emergent bilinguals with mathematics difficulty (MD), the linguistic complexity inherent in word problems may serve as a barrier to word–problem proficiency. The current study investigated the potential relation between academic English proficiency and word–problem outcomes for emergent bilinguals with MD. After analyzing data from 241 third–grade students, results indicated students who participated in an evidence–based word–problem intervention outperformed students who did not receive the intervention. Moreover, students’ academic English–language proficiency scores in the domains of reading and writing positively correlated with higher scores on a measure of word–problem solving.

Identifying the Challenges Encountered by Teachers While Using Intermediate English Textbooks - Sindh Board

The present study investigates the challenges encountered by teachers in utilizing English language textbooks of the intermediate level, specifically within the context of the Sindh Board education system. English language textbooks play a pivotal role in language instruction, offering structured content, exercises, and pedagogical support to enhance students' language proficiency. Despite their significance, there exists a dearth of research exploring the problems experienced by teachers while employing these textbooks in the classroom. The research design follows a mixed-methods approach, combining qualitative and quantitative data collection techniques. The qualitative phase encompasses semi-structured interviews with a purposive sample of intermediate-level English language teachers from various schools and colleges under the Sindh Board. These interviews will delve into the teachers' perspectives, experiences, and insights regarding the challenges faced during textbook utilization. On the other hand, the quantitative phase employs surveys distributed among a representative sample of teachers to gather statistical data on the most prevalent difficulties encountered. The study aims to identify and analyze the various issues that hinder effective textbook implementation in the Sindh Board's English language classrooms. These issues may encompass concerns related to content appropriateness, linguistic complexity, cultural relevance, alignment with curriculum objectives, and overall teacher preparedness. Additionally, factors influencing teachers' attitudes towards textbooks, such as training and support, will be explored. The findings of this research will contribute to the existing literature on language education and curriculum development, particularly in the context of the Sindh Board's English language program. The results will aid educational policymakers and curriculum designers in recognizing the areas that require improvement and in formulating more effective strategies to enhance teacher proficiency and student learning outcomes. Ultimately, this study explores the suggestion which may improve the use of textbooks and it aspires to promote the optimal use of English language textbooks, fostering a more conducive learning environment for intermediate-level students in the Sindh Board education system.

Intelligent Analysis Methods and Methodology of Banking Regulation Rules - Real Issues and Improvements in the Implementation by Commercial Banks

Banking regulation rules serve as the institutional basis for promoting commercial banks’ healthy and sustainable development. The linguistic complexity within the regulation discourse system leads to challenges in overall comprehension and execution, as well as disparities in interpretation and enforcement. By introducing intelligent analysis methods, the author conducts comparative analysis and historical research on regulation rules from both cross- sectional and historical development perspectives. This approach maximizes the exploration of regulation essence and the identification of laws of change, thus enhancing the effective implementation of regulation rules in the design of commercial banking systems.

An Interactive Framework of Cross-Lingual NLU for In-Vehicle Dialogue.

As globalization accelerates, the linguistic diversity and semantic complexity of in-vehicle communication is increasing. In order to meet the needs of different language speakers, this paper proposes an interactive attention-based contrastive learning framework (IABCL) for the field of in-vehicle dialogue, aiming to effectively enhance cross-lingual natural language understanding (NLU). The proposed framework aims to address the challenges of cross-lingual interaction in in-vehicle dialogue systems and provide an effective solution. IABCL is based on a contrastive learning and attention mechanism. First, contrastive learning is applied in the encoder stage. Positive and negative samples are used to allow the model to learn different linguistic expressions of similar meanings. Its main role is to improve the cross-lingual learning ability of the model. Second, the attention mechanism is applied in the decoder stage. By articulating slots and intents with each other, it allows the model to learn the relationship between the two, thus improving the ability of natural language understanding in languages of the same language family. In addition, this paper constructed a multilingual in-vehicle dialogue (MIvD) dataset for experimental evaluation to demonstrate the effectiveness and accuracy of the IABCL framework in cross-lingual dialogue. With the framework studied in this paper, IABCL improves by 2.42% in intent, 1.43% in slot, and 2.67% in overall when compared with the latest model.

How May I Interrupt? Linguistic-Driven Design Guidelines for Proactive in-Car Voice Assistants

Voice assistants (VAs) are predicted to develop from merely reactive to increasingly proactive agents in the future. While proactivity allows a leap towards more intelligent conversations with VAs, designing proactive agents is not straightforward, as benefit and acceptance of proactive behavior is dependent on a plethora of factors. For instance, proactive agents run the risk of disrupting users who are already engaged in ongoing primary tasks. While a large body of research is therefore concerned with when to proactively interrupt users, how to interrupt them has received less attention. To close this gap, a driving simulator study was conducted to find linguistic best practices for designing proactive prompts in German. Low linguistic complexity as well as suggestive rather than imposing language were found to influence study participants’ preferences for proactive prompts. These findings underline that the existing framework for designing proactive interactions needs to be enhanced by nuanced linguistic considerations.

Staging Joyce’s Prose – Zenon Fajfer and Katarzyna Bazarnik’s Finnegans Make

The purpose of the paper is to examine Finnegans Make, Zenkasi Theatre Company’s adaptation of Joyce’s prose devised and directed by Zenon Fajfer and Katarzyna Bazarnik, staged in the 1990s. It aims to demonstrate how by employing avant-garde compositional ideas and language games, they translate the structural and linguistic complexity characteristic of the Irish author to the idiom of the stage. demonstrate the thematic coherence of Joyce’s work, accompanied by compositional and. It analyses in detail the play’s circular structure that draws on excerpts from Dubliners, A Portrait of the Artist, Ulysses and Finnegans Wake. It also discusses how Fajfer and Bazarnik engage the audience and explore the theatre space. Finally, it examines how they use the space of the book and typographical devices to translate the live performance into a spatialised score of the play.

The influence of temporal (a)synchrony and linguistic complexity on audiovisual speech perception

Audiovisual (AV) cues often lead to improved speech understanding, especially when the auditory input is impoverished (e.g., in background noise, for people with hearing loss). This AV improvement occurs when both the auditory and visual information can be integrated together effectively (e.g., through temporal synchrony). However, whether the complexity of speech signals influences this integrated percept and how this contributes to speech understanding is still unknown. This study investigates whether individual differences in perception of temporal synchrony of the auditory and visual speech signal explain individual variability in AV speech recognition, and whether this differs across different levels of linguistic processing. By implementing five different levels of linguistic complexity (i.e., varying phoneme-viseme connections, vocabulary knowledge and/or linguistic context) and introducing temporal asynchrony in a remote task with English speaking adults we ask the following questions: (1) Is temporal synchrony needed to observe AV speech perception benefits? (2) Does this vary by linguistic level? (3) Does linguistic complexity influence synchrony perception? (4) And does synchrony perception explain individual variability in AV speech perception? These findings add value in deciding how AV synchronization should be balanced in hearing aid designs as well as in augmented / virtual reality devices.

Insights from lexical and syntactic analyses of a French for academic purposes assessment

With the objective of improving writing assessment of language instruction, we examine the lexical and syntactic features in two corpora of high and low scoring French texts of the Test du Certificat de Compétence en Langue Seconde (Second Language Certification Test; TCCLS) at the University of Ottawa (uOttawa). We first situate the test in its local context, demonstrating how our research objectives are born from specific needs to improve student outcomes. We then describe our creation of two corpora of high and low performing test takers, followed by lexical bundle (LB) analyses (Phase 1) and further linguistic complexity analyses with a French-language tool (Phase 2). Results indicate that high level writers used more LBs and borrowed more text from the prompt than low level writers. In addition, specific elements of linguistic complexity were identified, suggesting high level writers produced texts that were lexically richer and more syntactically advanced. We discuss the importance of these findings in improving our writing instruction, as well as the challenges of adapting tools and approaches traditionally associated with English to French.

Accounting Reporting Complexity and Non-GAAP Earnings Disclosure

ABSTRACT We examine whether the complexity of mandatory accounting disclosures prompts managers to voluntarily disclose adjusted measures of actual earnings performance, and whether this practice reflects attempts to obfuscate or mitigate the informational opacity accounting complexity creates for investors. Using the metadata in XBRL filings, we construct measures of accounting complexity that map directly to the mandated standards applied in financial statement filings. We find a positive and economically significant association between accounting complexity and managers’ propensity to disclose non-GAAP earnings information. This relation is robust and incremental to common measures of business and linguistic complexity, and the transitory nature of firms’ economic activities. We also find that the quality and informativeness of adjusted earnings information increases with accounting complexity, consistent with motives to better inform investors when accounting disclosures are complex. Overall, our results suggest that managers use non-GAAP earnings disclosure to mitigate the adverse informational effects of accounting complexity. Data Availability: All data are available from sources identified in the paper. JEL Classifications: M41; M43.

Response planning during question-answering: does deciding what to say involve deciding how to say it?

To answer a question, speakers must determine their response and formulate it in words. But do they decide on a response before formulation, or do they formulate different potential answers before selecting one? We addressed this issue in a verbal question-answering experiment. Participants answered questions more quickly when they had one potential answer (e.g., Which tourist attraction in Paris is very tall?) than when they had multiple potential answers (e.g., What is the name of a Shakespeare play?). Participants also answered more quickly when the set of potential answers were on average short rather than long, regardless of whether there was only one or multiple potential answers. Thus, participants were not affected by the linguistic complexity of unselected but plausible answers. These findings suggest that participants select a single answer before formulation.

The effect of collaborative prewriting on L2 collaborative writing production and individual L2 writing development

Abstract This study investigates the effect of collaborative prewriting on L2 collaborative writing production and individual L2 writing development. The participants were 51 university EFL students from two English composition classes. One class (n = 26) was the collaborative prewriting (CP) group, and the other was the non-collaborative prewriting (NCP) group (n = 25). Both groups participated in individual pre- and post-test writing and two collaborative expository essay writing tasks via Google Docs. The CP group engaged in collaborative prewriting before the collaborative writing tasks, whereas the NCP group did not. Learners’ pre- and post-test writing was evaluated for content quality, organization, linguistic complexity, and accuracy. Learner collaboration was analyzed for reflective versus non-reflective content-, organization-, and language-related episodes (CREs, OREs, LREs). LREs were further analyzed for resolution. The results showed that the learners who were engaged in collaborative prewriting produced collaborative expository essays with better content quality and organization, and made greater improvement in the content quality and organization of individual L2 writing. The findings were discussed in relation to the CREs, OREs, and LREs produced during collaborative prewriting and writing processes.

Modeling effects of linguistic complexity on L2 processing effort: The case of eye movement in text reading

AbstractThis study examined how linguistic complexity features contribute to second language (L2) processing effort by analyzing the Dutch English-L2 learners’ eye movements from GECO and MECO, two eye-tracking corpora. Processing effort was operationalized as reading rate, mean fixation duration, regression rate, skipping rate, and mean saccade amplitude. In Study 1, the lexical, syntactic, and discoursal indices in 272 snippets of a novel in GECO were regressed against these eye-movement measures. The results showed that the one-component partial least square regression (PLS-R) models could explain 11%–37% of the variance in these eye-movement measures and outperformed eight readability formulas (six traditional and two recent cognitively inspired formulas based on the readers’ perception on text difficulty) in predicting L2 processing effort. In Study 2, the eye-tracking data from MECO were used to evaluate whether the findings from Study 1 could be applied more broadly. The results revealed that although the predictability of these PLS-R components decreased, they still performed better than the readability formulas. These findings suggest that the linguistic indices identified can be used to predict L2 text processing effort and provide useful implications for developing systems to assess text difficulty for L2 learners.

How loan descriptions affect the likelihood that borrowers obtain loans in P2P networks? -An empirical analysis based on the "Renrendai" platform.

Information asymmetry is widespread in the P2P online lending market, creating an imbalance in the position of lenders and borrowers. This paper aims to expand the process of information exchange between lenders and borrowers by analyzing the link between soft information such as borrowers' loan descriptions and lending outcomes. Based on the transaction data of the 'Renrendai' platform, this paper analyzed the linguistic features and extracted the content of loan descriptions using a latent Dirichlet allocation (LDA) theme model. To further explore the value of loan descriptions in predicting lending success, this paper conducts a prediction study based on a support vector machine model. It is found that: lenders focus on effective information in the loan descriptions, the linguistic complexity affects the transaction, with simple and direct statements being more favorable; the content for building a good personal image of the borrower will significantly contribute to the lending success. In the prediction study section, it is demonstrated that loan descriptions' language feature indicators can improve prediction accuracy. This paper uncovers the importance of loan descriptions in online lending transactions, which has implications in assisting lenders' investment judgments, as well as in platform information system improvements.

The Interplay of Task Characteristics, Linguistic Complexity, and Language Proficiency in High‐Stakes English as a Foreign Language Writing

AbstractThe linguistic characteristics of text productions depend on various factors, including individual language proficiency as well as the tasks used to elicit the production. To date, little attention has been paid to whether some writing tasks are more suitable than others to represent and differentiate students' proficiency levels. This issue is especially relevant in the context of high‐stakes language examinations. In this study, we investigated task effects in English as a foreign language (EFL) Abitur examinations, the high‐stakes test qualifying for higher education admission in Germany. Based on texts produced by 362 students, we examined (a) if and how student writings differ in their linguistic complexity and (b) if the EFL Abitur tasks are equally suited to differentiate the students' proficiency levels. We used a broad operationalization of linguistic complexity, including measures from various linguistic domains in the computational analysis of the texts. The results of our mixed‐effects models show that student texts differ in their linguistic complexity primarily by the functional needs of the task types employed (summary, analysis, and argumentation). Furthermore, writing tasks that demand high independence in language performance are best suited to differentiate between proficiency levels, which becomes especially evident in vocabulary choice and usage.

Behind the scenes: The role of writing guideline design in online charitable crowdfunding market

The online charitable crowdfunding platform has emerged as a powerful tool for raising funds from large crowds to support non-profit activities. Following a patronage model, fundraisers on the platform are forced to use compelling stories to capture the attention of individual donors. As such, conceptualizing a persuasive request narrative for projects posted on the platform becomes one of the most pressing issues. Project writing guidelines, as an important platform design, are widely adopted to help fundraisers. Unfortunately, their role in the market has not been well examined. To fill this research gap, we leverage a unique dataset from a leading donation-based crowdfunding platform in the United States and make full use of its policy change opportunity on writing guidelines to thoroughly investigate its impacts and the underlying mechanism on donors’ contributions. Our empirical results show that the more constraints the guidelines impose on writing, the more likely they are to weaken the persuasiveness of narratives. We specifically focus on three aspects of narrative complexity and find that writing guidelines have a negative impact on linguistic complexity, which in turn diminishes donors’ contribution behavior. Nevertheless, they have positive impacts on both content and structural complexity, with the difference being that increased content complexity weakens donors’ contributions, while higher structural complexity is more likely to attract donations. Moreover, we examine the heterogeneous effects of writing guidelines on fundraisers with varied involvements. These findings deepen our understanding of writing guidance design in online platforms and have implications for charitable crowdfunding platforms and fundraisers.