Different types of well-being are likely to be associated with different kinds of behaviors. The first objective of this study was, from a subjective well-being perspective, to examine whether harmony in life and satisfaction with life are related differently to cooperative behaviors depending on individuals’ social value orientation. The second objective was, from a methodological perspective, to examine whether language-based assessments calledcomputational language assessments(CLA), which enable respondents to answer with words that are analyzed using natural (...) class='Hi'>language processing, demonstrate stronger correlations with cooperation than traditional rating scales. Participants reported their harmony in life, satisfaction with life, and social value orientation before taking part in an online cooperative task. The results show that the CLA of overall harmony in life correlated with cooperation (all participants:r= 0.18,p 0.05). No significant correlations (measured by the CLA or traditional rating scales) were found between satisfaction with life and cooperation. In conclusion, our study reveals an important behavioral difference between different types of subjective well-being. To our knowledge, this is the first study supporting the validity of self-reported CLA over traditional rating scales in relation to actual behaviors. (shrink)

Objective: The establishment of patient-centered measures capable of empirically determining meaningful cognitive change after surgery can significantly improve the medical care of epilepsy patients. Thus, this study aimed to develop reliable change indices (RCIs) and standardized regression-based (SRB) change norms for a comprehensive neuropsychological test battery in the German language. Methods: Forty-seven consecutive patients with temporal lobe epilepsy underwent neuropsychological assessments, both before and 12 months after surgery. Practice-effect-adjusted RCIs and SRB change norms for each test score were (...) computed. To assess their usefulness, the presented methods were applied to a clinical sample, and binary logistic regression analyses were conducted to model the odds of achieving improvement in quality of life (QOL) after surgery. Results: The determined RCIs at 90% confidence intervals, and the SRB equations for each test score included in the test battery are provided. Cohen’s kappa analyses revealed a moderate mean agreement between the two measures, varying from slight to almost perfect agreement across test scores. Using these measures, a negative association between improvement in QOL and decline in verbal memory functions after surgery was detected. Significance: To the best of our knowledge, this study is the first to provide RCIs and SRB change norms necessary for the objective determination of neuropsychological change in a comprehensive test battery in the German language, facilitating the individual monitoring of improvement and decline in each patients’ cognitive functioning and psychosocial situations after epilepsy surgery. The application of the described measures revealed a strong negative association between improvement in QOL and decline in verbal memory functions after surgery. (shrink)

Previous studies of the lexical psycholinguistic properties in second language production have assessed the degree of an LPP dimension of an L2 corpus by computing the mean ratings of unique content words in the corpus for that dimension, without considering the possibility that learners at different proficiency levels may perceive the degree of that dimension of the same words differently. This study extended a dynamic semantic similarity algorithm to estimate the degree of five different LPP dimensions of several sub-corpora (...) of the Education First-Cambridge Open Language Database representing L2 English learners at different proficiency levels. Our findings provide initial evidence for the validity of the algorithm for assessing the LPPs in L2 production and contribute useful insights into between-proficiency relationships and cross-proficiency differences in the LPPs in L2 production as well as the relationships among different LPP dimensions. (shrink)

The present paper intends to draw the conception of language implied in the technique of word embeddings that supported the recent development of deep neural network models in computational linguistics. After a preliminary presentation of the basic functioning of elementary artificial neural networks, we introduce the motivations and capabilities of word embeddings through one of its pioneering models, word2vec. To assess the remarkable results of the latter, we inspect the nature of its underlying mechanisms, which have been characterized (...) as the implicit factorization of a word-context matrix. We then discuss the ordinary association of the “distributional hypothesis” with a “use theory of meaning,” often justifying the theoretical basis of word embeddings, and contrast them to the theory of meaning stemming from those mechanisms through the lens of matrix models (such as vector space models and distributional semantic models). Finally, we trace back the principles of their possible consistency through Harris’s original distributionalism up to the structuralist conception of language of Saussure and Hjelmslev. Other than giving access to the technical literature and state of the art in the field of natural language processing to non-specialist readers, the paper seeks to reveal the conceptual and philosophical stakes involved in the recent application of new neural network techniques to the computational treatment of language. (shrink)

We report a quantitative analysis of the cross-utterance coordination observed in child-directed language, where successive utterances often overlap in a manner that makes their constituent structure more prominent, and describe the application of a recently published unsupervised algorithm for grammar induction to the largest available corpus of such language, producing a grammar capable of accepting and generating novel wellformed sentences. We also introduce a new corpus-based method for assessing the precision and recall of an automatically acquired generative grammar (...) without recourse to human judgment. The present work sets the stage for the eventual development of more powerful unsupervised algorithms for language acquisition, which would make use of the coordination structures present in natural child-directed speech. (shrink)

In trying to control various aspects concerning utterance production in multi-party human–computer dialogue, argumentative considerations play an important part, particularly in choosing appropriate lexical units so that we fine-tune the degree of persuasion that each utterance has. A preliminary step in this endeavor is the ability to place an ordering relation between semantic forms (that are due to be realized as utterances, by the machine), concerning their persuasion strength, with respect to certain (explicit or implicit) conclusions. Thus, in this article, (...) we propose a mechanism for assessing utterances, in terms of their argumentative force. The framework designed conflates insights from Asher and Lascarides’ SDRT (“Segmented Discourse Representation Theory”), and from Anscombre and Ducrot’s AT (“Argumentation Theory”). These mechanisms are included in a language generation component of a multi-party dialogue system for book reservation applications (i.e., a “virtual librarian”), and thus evaluated via typical human–machine conversations. (shrink)

Using educational robots to integrate computational thinking with cross-disciplinary content has gone beyond Science, Technology, Engineering, and Mathematics, to include foreign-language learning and further cross-context target-language acquisition. Such integration must not solely emphasise CT problem-solving skills. Rather, it must provide students with interactive learning to support their target-language interaction while reducing potential TL anxiety. This study aimed to validate the effects of the proposed method of pair programming along with question-and-response interaction in a board-game activity on (...) young learners’ CT skills and TL learning across contexts. Two Grade 6 classes, one with 16 students who were studying Chinese as a Second Language and the other with 16 students who were studying English as a Foreign Language, participated in the activity. A series of instruments on achievement assessment, questionnaires on CT skills and TL anxiety, and sequential learning behaviour analysis were used to critically examine the results. The main conclusion is that the EFL group showed better social skills of cooperation on CT and lower TL learning anxiety, while the CSL group demonstrated better problem-solving skills in CT, but presented more behaviours of trial-and-error loops. Results not only contribute suggestions for cross-disciplinary learning but also provide support for cross-context instruction beyond educational coursework. (shrink)

Sleep quality, personality, and cognitive load potentially increase second language writing anxiety and subsequently affect SLW achievement. This study investigates the predictions of sleep quality, personality, and cognitive load toward SLW anxiety and achievement in a computer-based test. Participants included 172 voluntary undergraduates majoring in English as foreign language. SLW anxiety in a computer-based test, sleep disturbance, personality and cognitive load was assessed with the SLW Anxiety Inventory, Pittsburg Sleep Quality Index, Type-D Personality, and cognitive load questionnaires. A (...) structural equation modeling approach was applied to examine the interdependence among the observed variables. An adequate-fit SLW anxiety model was built. The structural model showed that sleep disturbance, social inhibition personality, and computer-induced cognitive load were significant predictors of SLW anxiety in a computer-based test. Subsequently, SLW anxiety in a computer-based test and computer-induced cognitive load were significant negative predictors of computer-based SLW achievement. (shrink)

Since its conception nearly 20 years ago, Logic Programming - the idea of using logic as a programming language - has been developed to the point where it now plays an important role in areas such as database theory, artificial intelligence and software engineering. However, there are still many challenging research issues to be addressed and the UK branch of the Association for Logic Programming was set up to provide a forum where the flourishing research community could discuss important (...) issues of Logic Programming which were often by-passed at the large international conferences. This volume contains the twelve papers which were presented at the ALPUK's 3rd conference which was held in Edinburgh, 10-12 April 1991. The aim of the conference was to give a broad but detailed technical insight into the work currently being done in this field, both in the UK and by researchers as far afield as Canada and Bulgaria. The breadth of interest in this area of Computer Science is reflected in the range of the papers which cover - amongst other areas - massively parallel implementation, constraint logic programming, circuit modelling, algebraic proof of program properties, deductive databases, specialised editors and standardisation. The resulting volume gives a good overview of the current progress being made in the field and will be of interest to researchers and students of any aspects of logic programming, parallel computing or database techniques and management. (shrink)

This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important and innovative changes in theories and concepts. Gathering revised contributions presented at the international conference on Model-Based Reasoning, held on October 24–26 2018 in Seville, Spain, the book is divided into three main parts. The first focuses on models, reasoning, and representation. It highlights key theoretical concepts from an applied perspective, and addresses issues concerning information visualization, experimental (...) methods, and design. The second part goes a step further, examining abduction, problem solving, and reasoning. The respective papers assess different types of reasoning, and discuss various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies, this part is intended to foster new discussions and stimulate new ideas. All in all, the book provides researchers and graduate students in the fields of applied philosophy, epistemology, cognitive science, and artificial intelligence alike with an authoritative snapshot of the latest theories and applications of model-based reasoning. (shrink)

The present study assessed the language teachers' pedagogical beliefs and orientations in integrating technology in the online classroom and its effect on students' motivation and engagement. It utilized a cross-sectional correlational research survey. The study respondents were the randomly sampled 205 language teachers (μ= 437, n= 205) and 317 language students (μ= 1800, n= 317) of select higher educational institutions in the Philippines. The study results revealed that respondents hold positive pedagogical beliefs and orientations using technology-based teaching (...) in their language classroom. Test of difference showed that female teachers manifested a firmer belief in student-centered online language teaching than their male counterparts. However, the utilization and attitude towards technology in the language classroom is favorably associated with the male teachers. As to students' level of language learning motivation and engagement, it was found out that male and female students have high level of language learning engagement. Further, the test of relationship showed that the higher the teachers' belief in utilizing student-centered teaching to integrate technology in the language classroom, the higher the students are motivated and engaged in learning. In like manner, it was also revealed that teacher-centered belief is negatively correlated to student’s motivation and engagement in online language learning. In this regard, the pedagogical assumptions that hold EFL teachers positively to integrate technology in the language classroom. This study generally offers implications for enhancing language teacher's digital literacy to promote motivating, fruitful, and engaging language lessons for 21ts century learning. (shrink)

Recent discussions in the philosophy of psychology have examined the use and legitimacy of such notions as ‘representation’, ‘content’, ‘computation’, and ‘inference’ within a scientific psychology. While the resulting assessments have varied widely, ranging from outright rejection of some or all of these notions to full vindication of their use, there has been notable agreement on the considerations deemed relevant for making an assessment. The answer to the question of whether the notion of, say, representational content may be admitted (...) into a scientific psychology has often been made to hinge upon whether the notion can be squared with our ‘ordinary’ or ‘folk’ style of psychological explanation, with its alleged commitment to the idiom of beliefs and desires. The emphasis on ‘folk psychology’ in arguments concerning the status of various concepts within scientific psychology is unfortunate, because it runs afoul of the ideal that the philosophy of psychology, by analogy with the philosophy of biology and the philosophy of physics, should have at its core the discussion of ongoing psychological theories. For while it may be admitted that the status of appeals to ‘folk psychology’ in order to justify a role for the belief-desire idiom within psychology proper is a matter that is of interest in its own right, it is not at all clear that mainstream experimental psychology has adopted either the language or the conceptions of ‘belief-desire’ psychology. (shrink)

The papers collected in this volume exemplify some of the trends in current approaches to logic, language and computation. Written by authors with varied academic backgrounds, the contributions are intended for an interdisciplinary audience. The first part of this volume addresses issues relevant for multi-agent systems: reasoning with incomplete information, reasoning about knowledge and beliefs, and reasoning about games. Proofs as formal objects form the subject of Part II. Topics covered include: contributions on logical frameworks, linear logic, and different (...) approaches to formalized reasoning. Part III focuses on representations and formal methods in linguistic theory, addressing the areas of comparative and temporal expressions, modal subordination, and compositionality. (shrink)

To assess—from a qualitative perspective—the perceptions and attitudes of Spanish rehabilitation professionals (e.g. rehabilitation doctors, speech therapists, physical therapists) about Brain–Computer Interface (BCI) technology. A qualitative, exploratory and descriptive study was carried out by means of interviews and analysis of textual content with mixed generation of categories and segmentation into frequency of topics. We present the results of three in-depth interviews that were conducted with Spanish speaking individuals who had previously completed a survey as part of a larger, 3-country/language, (...) survey on BCI perceptions. 11 out of 15 of these Spanish respondents (survey) either strongly or somewhat accept the use of BCI in rehabilitation therapy. However, the results of our three in-depth interviews show how, due to a strong inertia of attitudes and perceptions about BCI technology, most professionals feel reluctant to use BCI technology in their daily practice (interview). (shrink)

Empirical insights into language processing have a philosophical relevance that extends well beyond philosophical questions about language. This chapter will discuss this wider relevance: We will consider how experimental philosophers can examine language processing in order to address questions in several different areas of philosophy. To do so, we will present the emerging research program of experimental argument analysis (EAA) that examines how automatic language processing shapes verbal reasoning – including philosophical arguments. The evidential strand of (...) experimental philosophy uses mainly questionnaire-based methods to assess the evidentiary value of intuitive judgments that are adduced as evidence for philosophical theories and as premises for philosophical arguments. Extending this prominent strand of experimental philosophy, EAA underpins such assessments, extends the scope of the assessments, and expands the range of the empirical methods employed: EAA examines how automatic inferences that are continually made in language comprehension and production shape verbal reasoning, and draws on findings about comprehension biases that affect the contextualisation of such default inferences, in order to explain and expose fallacies. It deploys findings to assess premises and inferences from premises to conclusions, in philosophical arguments. To do so, it adapts methods from psycholinguistics and recruits methods from computational linguistics. (shrink)

Computational models of affect (CMAS), in their most common form, cannot take into account the qualitative (phenomenal) dimension of affect itself. Their expressivity can be extended, thus promoting the much sought-after standardization in the most theory-neutral way, using OWL (Web Ontology Language) and machine learning techniques. OWL is an expressive formal language, as well as an established open standard, and can be used to describe the models, possibly including qualitative entities at the fundamental level. The supervised machine (...) learning techniques allow the direct learning and application of models described as OWL ontologies. Thanks to human supervision (e.g. using datasets labeled by a human user), they can take into account the qualitative dimension of affect when the models warrant it. To further promote the aforementioned standardization, the task of classifying texts according to their affective content (known in computer science as "sentiment analysis") can be recommended as a way to assess the performance of the models. It is a multifaceted task, in which usually divergent fields as philosophy, psychology and computer science meet. Moreover, since it is a very current task in computer science, there are many resources available to facilitate the development of a standard benchmark for CMAS. (shrink)

This paper explores aspects of GPT-3 that have been discussed as harbingers of artificial general intelligence and, in particular, linguistic intelligence. After introducing key features of GPT-3 and assessing its performance in the light of the conversational standards set by Alan Turing in his seminal paper from 1950, the paper elucidates the difference between clever automation and genuine linguistic intelligence. A central theme of this discussion on genuine conversational intelligence is that members of a linguistic community never merely respond “algorithmically” (...) to queries through a selective kind of pattern recognition, because they must also jointly attend and act with other speakers in order to count as genuinely intelligent and trustworthy. This presents a challenge for systems like GPT-3, because representing the world in a way that makes conversational common ground salient is an essentially collective task that we can only achieve jointly with other speakers. Thus, the main difficulty for any artificially intelligent model of conversation is to account for the communicational intentions and motivations of a speaker through joint attention. These joint motivations and intentions seem to be completely absent from the standard way in which systems like GPT-3 and other artificial intelligent systems work. This is not merely a theoretical issue. Since GPT-3 and future iterations of similar systems will likely be available for commercial use through application programming interfaces, caution is needed regarding the risks created by these systems, which pass for “intelligent” but have no genuine communicational intentions, and can thereby produce fake and unreliable linguistic exchanges. (shrink)

The Sentence in Language and Cognition is about the significant role of the sentence in linguistic cognition and in the practical domains of human existence. Dr. Tista Bagchi has written a comprehensive assessment of the structure and cognitive function of the sentence and the clause in the context of real-world discourse and activities.The notions of sentencehood and clausehood with special reference to the semantic histories of the terms sentence and clause, including their ethical, legal, and administrative uses, are assessed. (...) This is followed by a concise historical survey of the treatment of the sentence in a few of the ancient linguistic traditions, notably the Greek, Roman(-Alexandrian), Arab, and Sanskrit scholastic traditions. A wide variety of sentence types, from a cross-section of languages spoken in Asia, Europe, and the Americas, are presented by way of factual evidence for sentences and clauses as linguistic units. Formally defined notions of the sentence and the clause as syntactic constituents in major theoretical frameworks are examined and assessed for their essential properties and points of convergence. The Sentence in Language and Cognition is an essential book for advanced students and researchers of linguistics. (shrink)

Large Language Models (LLMs) could be a useful tool for lawyers. However, empirical research on their effectiveness in conducting legal tasks is scant. We study securities cases involving cryptocurrencies as one of numerous contexts where AI could support the legal process, studying GPT-3.5’s legal reasoning and ChatGPT’s legal drafting capabilities. We examine whether a) GPT-3.5 can accurately determine which laws are potentially being violated from a fact pattern, and b) whether there is a difference in juror decision-making based on (...) complaints written by a lawyer compared to ChatGPT. We feed fact patterns from real-life cases to GPT-3.5 and evaluate its ability to determine correct potential violations from the scenario and exclude spurious violations. Second, we had mock jurors assess complaints written by ChatGPT and lawyers. GPT-3.5’s legal reasoning skills proved weak, though we expect improvement in future models, particularly given the violations it suggested tended to be correct (it merely missed additional, correct violations). ChatGPT performed better at legal drafting, and jurors’ decisions were not statistically significantly associated with the author of the document upon which they based their decisions. Because GPT-3.5 cannot satisfactorily conduct legal reasoning tasks, it would be unlikely to be able to help lawyers in a meaningful way at this stage. However, ChatGPT’s drafting skills (though, perhaps, still inferior to lawyers) could assist lawyers in providing legal services. Our research is the first to systematically study an LLM’s legal drafting and reasoning capabilities in litigation, as well as in securities law and cryptocurrency-related misconduct. (shrink)

Biases and misunderstanding stemming from pre-training in Generative Pre-Trained Transformers are more likely for users of underrepresented English varieties, since the training dataset favors dominant Englishes (e.g., American English). We investigate (potential) bias in GPT-4 when it interacts with Trinidadian English Creole (TEC), a non-hegemonic English variety that partially overlaps with standardized English (SE) but still contains distinctive characteristics. (1) Comparable responses: we asked GPT-4 18 questions in TEC and SE and compared the content and detail of the responses. (2) (...) Accurate translation: we assessed how accurate and authentic 29 TEC and 34 SE translations were. (3) Language knowledge and attitudes: we asked what language the prompts were written in and categorized the responses and examined any language attitudes that were exhibited. Content and detail in prompts were comparable. The model was proficient at translating TEC pronouns and many grammatical categories. It was weaker at processing spelling and vocabulary items. In addition, it produced several inauthentic features. Only 39% of TEC-generated sentences were fully grammatical. While GPT-4 was perfect at identifying SE, it was 21% accurate at identifying TEC, which it sometimes classified as English with “errors” and “corrected”. GPT-4’s scope of use is limited for non-hegemonic English users. It is problematic that some of its analyses perpetuate bias against underrepresented Englishes. Increased research on lesser-documented Englishes is necessary and we anticipate that this problem affects dialects of other languages. We intend to partner with Trinidadian stakeholders to train GPT-4 in the future. (shrink)

This paper aims at comparing and relating belief revision and argumentation as approaches to model reasoning processes. Referring to some prominent literature references in both fields, we will discuss their (implicit or explicit) assumptions on the modeled processes and hence commonalities and differences in the forms of reasoning they are suitable to deal with. The intended contribution is on one hand assessing the (not fully explored yet) relationships between two lively research fields in the broad area of defeasible reasoning and (...) on the other hand pointing out open issues and potential directions for future research. (shrink)

This study examined the effects of computer-assisted cognitive rehabilitation in a group of 16 brain-damaged patients. Therapeutic effectiveness was assessed by improvement on computer tasks, the results of neuropsychological tests and quality of life ratings. Participants suffered from mild to moderate attention and memory problems or aphasia. The procedure involved baseline assessment, a 15-week course of therapy conducted twice a week and posttest. Neuropsychological tests assessing attention, memory and language problems and quality of life ratings were administered twice: in (...) pre- and posttests. Twelve healthy controls were also examined twice using the same battery of neuropsychological tests. The RehaCom program and the Polish computer therapy program for aphasics called Afa-System were used for rehabilitation. The computer-assisted rehabilitation tasks were selected individually for each patient. The results showed significant improvement on computer-assisted tasks in all braindamaged subjects. However, none or very little improvement was observed on neuropsychological tests and quality of life ratings. The results of the study confirm the importance of using different types of measures to estimate the effectiveness of computer-assisted neuropsychological rehabilitation as well as the necessity of applying various kinds of therapy to improve cognitive, emotional and social functioning in brain-damaged patients. (shrink)

A substantial amount of recent work in natural language generation has focused on the generation of ‘‘one‐shot’’ referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It turns out (...) that the success of the IA depends substantially on the ‘‘preference order’’ (PO) employed by the IA, particularly in complex domains. While some POs cause the IA to produce referring expressions that are very similar to expressions produced by human subjects, others cause the IA to perform worse than its main competitors; moreover, it turns out to be difficult to predict the success of a PO on the basis of existing psycholinguistic findings or frequencies in corpora. We also examine the computational complexity of the algorithms in question and argue that there are no compelling reasons for preferring the IA over some of its main competitors on these grounds. We conclude that future research on the generation of referring expressions should explore alternatives to the IA, focusing on algorithms, inspired by the Greedy Algorithm, which do not work with a fixed PO. (shrink)

Although formal thought disorder (FTD) has been for long a clinical label in the assessment of some psychiatric disorders, in particular of schizophrenia, it remains a source of controversy, mostly because it is hard to say what exactly the “formal” in FTD refers to. We see anomalous processing of terminological knowledge, a core construct of human knowledge in general, behind FTD symptoms and we approach this anomaly from a strictly formal perspective. More specifically, we present here a symbolic computational (...) model of storage in, and activation of, a human semantic network, or semantic memory, whose core element is logical form; this is normalized by description logic (DL), namely by CL, a DL-based language – Conception Language – designed to formalize conceptualization from the viewpoint of individual cognitive agency. In this model, disruptions in the rule-based implementation of the logical form account for the apparently semantic anomalies symptomatic of FTD, which are detected by means of a CL-based algorithmic assessment. (shrink)

The article explores the use of the “ChatGPT” artificial intelligence language model in the Human Sciences field. ChatGPT uses natural language processing techniques to imitate human language and engage in artificial conversations. While the platform has gained attention from the scientific community, opinions on its usage are divided. The article presents some conversations with ChatGPT to examine ethical, relational and linguistic issues related to human-computer interaction (HCI) and assess its potential for Human Sciences research. The interaction with (...) the platform recalls the “uncanny valley” phenomenon still known to Social Robotics. While ChatGPT can be beneficial, it requires proper supervision and verification of its results. Furthermore, new research methods must be developed for qualitative, quantitative, and mixed methods. (shrink)

This paper asks why information should ever be expressed vaguely, re-assessing some previously proposed answers to this question and suggesting some new ones. Particular attention is paid to the benefits that vague expressions can have in situations where agreement over the meaning of an expression cannot be taken for granted. A distinction between two different versions of the above-mentioned question is advocated. The first asks why human languages contain vague expressions, the second question asks when and why a speaker should (...) choose a vague expression when communicating with a hearer. While the former question is purely theoretical, the latter has practical implications for the computational generation of utterances in Natural Language Generation (NLG). (shrink)

Intellectual humility can be broadly construed as being conscious of the limits of one’s existing knowledge and capable of acquiring more knowledge, which makes it a key virtue of the information age. However, the claim “I am humble” seems paradoxical in that someone who has the disposition in question would not typically volunteer it. Therefore, measuring intellectual humility via self-report may be methodologically unsound. As a consequence, we suggest analyzing intellectual humility semantically, using a psycholexical approach that focuses on both (...) synonyms and antonyms of ‘intellectual humility’. We present a thesaurus-based methodology to map the semantic space of intellectual humility and the vices it opposes as a heuristic to support analysis and diagnosis of this disposition. We performed the mapping both in English and German in order to test for possible cultural differences in the understanding of intellectual humility. In both languages, we find basically the same three semantic dimensions of intellectual humility as well as three dimensions of its related vices. The resulting semantic clusters were validated in an empirical study with English and German participants. We find medium-to-high correlations between thesaurus similarity and perceived similarity, and we can validate the three dimensions identified in the study. But we also find limitations of the thesaurus methodology in terms of cluster plausibility. We conclude by discussing the importance of these findings for constructing psychometric measures of intellectual humility via self-report vs. computer models. (shrink)

This paper asks why information should ever be expressed vaguely, re-assessing some previously proposed answers to this question and suggesting some new ones. Particular attention is paid to the benefits that vague expressions can have in situations where agreement over the meaning of an expression cannot be taken for granted. A distinction between two different versions of the above-mentioned question is advocated. The first asks why human languages contain vague expressions, the second question asks when and why a speaker should (...) choose a vague expression when communicating with a hearer. While the former question is purely theoretical, the latter has practical implications for the computational generation of utterances in Natural Language Generation (NLG). (shrink)

Analyzing and evaluating legal case reports are labor-intensive tasks for judges and lawyers, who usually base their decisions on report abstracts, legal principles, and commonsense reasoning. Thus, summarizing legal documents is time-consuming and requires excellent human expertise. Moreover, public legal corpora of specific languages are almost unavailable. This paper proposes a transfer learning approach with extractive and abstractive techniques to cope with the lack of labeled legal summarization datasets, namely a low-resource scenario. In particular, we conducted extensive multi- and cross- (...) class='Hi'>language experiments. The proposed work outperforms the state-of-the-art results of extractive summarization on the Australian Legal Case Reports dataset and sets a new baseline for abstractive summarization. Finally, syntactic and semantic metrics assessments have been carried out to evaluate the accuracy and the factual consistency of the machine-generated legal summaries. (shrink)

A substantial amount of recent work in natural language generation has focused on the generation of ‘‘one-shot’’ referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It turns out (...) that the success of the IA depends substantially on the ‘‘preference order’’ (PO) employed by the IA, particularly in complex domains. While some POs cause the IA to produce referring expressions that are very similar to expressions produced by human subjects, others cause the IA to perform worse than its main competitors; moreover, it turns out to be difficult to predict the success of a PO on the basis of existing psycholinguistic findings or frequencies in corpora. We also examine the computational complexity of the algorithms in question and argue that there are no compelling reasons for preferring the IA over some of its main competitors on these grounds. We conclude that future research on the generation of referring expressions should explore alternatives to the IA, focusing on algorithms, inspired by the Greedy Algorithm, which do not work with a fixed PO. (shrink)

Intellectual humility can be broadly construed as being conscious of the limits of one’s existing knowledge and capable of acquiring more knowledge, which makes it a key virtue of the information age. However, the claim “I am humble” seems paradoxical in that someone who has the disposition in question would not typically volunteer it. Therefore, measuring intellectual humility via self-report may be methodologically unsound. As a consequence, we suggest analyzing intellectual humility semantically, using a psycholexical approach that focuses on both (...) synonyms and antonyms of ‘intellectual humility’. We present a thesaurus-based methodology to map the semantic space of intellectual humility and the vices it opposes as a heuristic to support analysis and diagnosis of this disposition. We performed the mapping both in English and German in order to test for possible cultural differences in the understanding of intellectual humility. In both languages, we find basically the same three semantic dimensions of intellectual humility as well as three dimensions of its related vices. The resulting semantic clusters were validated in an empirical study with English and German participants. We find medium-to-high correlations between thesaurus similarity and perceived similarity, and we can validate the three dimensions identified in the study. But we also find limitations of the thesaurus methodology in terms of cluster plausibility. We conclude by discussing the importance of these findings for constructing psychometric measures of intellectual humility via self-report vs. computer models. (shrink)

We trained a computational model (the Chunk-Based Learner; CBL) on a longitudinal corpus of child–caregiver interactions in English to test whether one proposed statistical learning mechanism—backward transitional probability—is able to predict children's speech productions with stable accuracy throughout the first few years of development. We predicted that the model less accurately reconstructs children's speech productions as they grow older because children gradually begin to generate speech using abstracted forms rather than specific “chunks” from their speech environment. To test this (...) idea, we trained the model on both recently encountered and cumulative speech input from a longitudinal child language corpus. We then assessed whether the model could accurately reconstruct children's speech. Controlling for utterance length and the presence of duplicate chunks, we found no evidence that the CBL becomes less accurate in its ability to reconstruct children's speech with age. (shrink)

The discrepancy between syntax and semantics is a painstaking issue that hinders a better comprehension of the underlying neuronal processes in the human brain. In order to tackle the issue, we at first describe a striking correlation between Wittgenstein's Tractatus, that assesses the syntactic relationships between language and world, and Perlovsky's joint language-cognitive computational model, that assesses the semantic relationships between emotions and “knowledge instinct”. Once established a correlation between a purely logical approach to the language (...) and computable psychological activities, we aim to find the neural correlates of syntax and semantics in the human brain. Starting from topological arguments, we suggest that the semantic properties of a proposition are processed in higher brain's functional dimensions than the syntactic ones. In a fully reversible process, the syntactic elements embedded in Broca's area project into multiple scattered semantic cortical zones. The presence of higher functional dimensions gives rise to the increase in informational content that takes place in semantic expressions. Therefore, diverse features of human language and cognitive world can be assessed in terms of both the logic armor described by the Tractatus, and the neurocomputational techniques at hand. One of our motivations is to build a neuro-computational framework able to provide a feasible explanation for brain's semantic processing, in preparation for novel computers with nodes built into higher dimensions. (shrink)

Roger Schank's research in AI takes seriously the ideas that understanding natural language involves mapping its expressions into an internal representation scheme and that these internal representations have a syntax appropriate for computational operations. It therefore falls within the computational approach to the study of mind. This paper discusses certain aspects of Schank's approach in order to assess its potential adequacy as a (partial) model of cognition. This version of the Language of Thought hypothesis encounters some (...) of the same difficulties that arise for Fodor's account. (shrink)

ABSTRACTComputers are now able to automatically generate metaphors, but some automatically generated metaphors are more well received than others. In this article, we showed participants a series of “A is B” type metaphors that were either generated by humans or taken from the Twitter account “MetaphorIsMyBusiness”, which is linked to a fully automated metaphor generator. We used these metaphors to assess linguistic factors that drive metaphor appreciation and understanding, including the role of novelty, word frequency, concreteness, and emotional valence of (...) the topic and vehicle terms. We additionally assessed how these metaphors were understood in three languages, including English, Spanish, and Mandarin Chinese, and whether participants thought they had been generated by a human or a computer. We found that meaningfulness, appreciation, speed in finding meaning, and humanness ratings were reliably correlated with each other in all three languages, which we interpret to indicate a mor... (shrink)

Infant language learners are faced with the difficult inductive problem of determining how new words map to novel or known objects in their environment. Bayesian inference models have been successful at using the sparse information available in natural child-directed speech to build candidate lexicons and infer speakers’ referential intentions. We begin by asking how a Bayesian model optimized for monolingual input generalizes to new monolingual or bilingual corpora and find that, especially in the case of the bilingual input, the (...) model shows a significant decrease in performance. In the next experiment, we propose the ME Model, a modified Bayesian model, which approximates infants’ mutual exclusivity bias to support the differential demands of monolingual and bilingual learning situations. The extended model is assessed using the same corpora of real child-directed speech, showing that its performance is more robust against varying input and less dependent than the Intentional Model on optimization of its parsimony parameter. We argue that both monolingual and bilingual demands on word learning are important considerations for a computational model, as they can yield significantly different results than when only one such context is considered. (shrink)

Over the last decade, iterated learning studies have provided compelling evidence for the claim that linguistic structure can emerge from non‐structured input, through the process of transmission. However, it is unclear whether individuals differ in their tendency to add structure, an issue with implications for understanding who are the agents of change. Here, we identify and test two contrasting predictions: The first sees learning as a pre‐requisite for structure addition, and predicts a positive correlation between learning accuracy and structure addition, (...) whereas the second maintains that it is those learners who struggle with learning and reproducing their input who add structure to it. This prediction is hard to test in standard iterated learning paradigms since each learner is exposed to a different input, and since structure and accuracy are computed using the same test items. Here, we test these contrasting predictions in two experiments using a one‐generation artificial language learning paradigm designed to provide independent measures of learning accuracy and structure addition. Adults (N = 48 in each study) were exposed to a semi‐regular language (with probabilistic structure) and had to learn it: Learning was assessed using seen items, whereas structure addition was calculated over unseen items. In both studies, we find a strong positive correlation between individuals' ability to learn the language and their tendency to add structure to it: Better learners also produced more structured languages. These findings suggest a strong link between learning and generalization. We discuss the implications of these findings for iterated language models and theories of language change more generally. (shrink)

Lexical ambiguity is pervasive in language, and the nature of the representations of an ambiguous word's multiple meanings is yet to be fully understood. With a special focus on Chinese characters, the present study first established that native speaker's perception about a character's number of meanings was heavily influenced by the availability of its distinct word formations, while whether these meanings would be perceived to be closely related was driven by further conceptual analysis. These notions were operationalized as two (...) computed metrics, which assessed the degree of dispersion across individual word formations and the degree of propinquity across clusters of word formations, respectively, in a distributional semantic space. The observed correlations between the computed and the perceived metrics indicated that the utility of word formations to tap into meaning representations of Chinese characters was indeed cognitively plausible. The results have demonstrated the extent to which distributional semantics could inform about meaning representations of Chinese characters, which has theoretical implications for the representation of ambiguous words more generally. (shrink)

Melody prediction is an important aspect of music listening. The success of prediction, i.e., whether the next note played in a song is the same as the one predicted by the listener, depends on various factors. In the paper, we present two studies, where we assess how music familiarity and music expertise influence melody prediction in human listeners, and, expressed in appropriate data/algorithmic ways, computational models. To gather data on human listeners, we designed a melody prediction user study, where (...) familiarity was controlled by two different music collections, while expertise was assessed by adapting the Music Sophistication Index instrument to Slovenian language. In the second study, we evaluated the melody prediction accuracy of computational melody prediction models. We evaluated two models, the SymCHM and the Implication-Realization model, which differ substantially in how they approach melody prediction. Our results show that both music familiarity and expertise affect the prediction accuracy of human listeners, as well as of computational models. (shrink)

This article contributes to the debate around the abilities of large language models such as GPT-3, dealing with: firstly, evaluating how well GPT does in the Turing Test, secondly the limits of such models, especially their tendency to generate falsehoods, and thirdly the social consequences of the problems these models have with truth-telling. We start by formalising the recently proposed notion of reversible questions, which Floridi & Chiriatti propose allow one to ‘identify the nature of the source of their (...) answers’, as a probabilistic measure based on Item Response Theory from psychometrics. Following a critical assessment of the methodology which led previous scholars to dismiss GPT’s abilities, we argue against claims that GPT-3 completely lacks semantic ability. Using ideas of compression, priming, distributional semantics and semantic webs we offer our own theory of the limits of large language models like GPT-3, and argue that GPT can competently engage in various semantic tasks. The real reason GPT’s answers seem senseless being that truth-telling is not amongst them. We claim that these kinds of models cannot be forced into producing only true continuation, but rather to maximise their objective function they strategize to be plausible instead of truthful. This, we moreover claim, can hijack our intuitive capacity to evaluate the accuracy of its outputs. Finally, we show how this analysis predicts that a widespread adoption of language generators as tools for writing could result in permanent pollution of our informational ecosystem with massive amounts of very plausible but often untrue texts. (shrink)

Employability is an important indicator of the competency of the employees. Employability model is a useful analytical framework for studying the ever-changing relationship between higher education and the job market. At present, the demand for business English graduates is increasing, however, there is a skill gap between their educational readiness and the recruitment requirements. In order to solve this problem, this study adopted mixed methods research and carried out the research design according to the exploratory sequence design to construct an (...) employability model for business English graduates. A 46-item scale was developed to measure the employability of business English graduates’ employability. After assessment, it was found that the employability of business English graduates was multi-dimensional, with three dimensions—professional knowledge, generic competencies, and career management and 10 sub-dimensions—English language skills, foreign trade competencies, computer and internet application skills, social skills, learning and development, personal traits, thinking ability, work ethics, career identity and planning, and service awareness. This study verified that the employability of business English graduates reached the standard of talent training and met the requirements of employers. There were employability differences in gender, places of origin and educational institutions. From this study, it could be inferred that cultivation of business English majors should be multi-dimensional. (shrink)

Evolutionary psychology often does not sufficiently document the innate constraint and domain specificity required for strong adaptationist argument. We develop these criteria within the domain of music. First, we advocate combining computational, developmental, cross-cultural, and neuroscience research to address the ways in which a domain is innately constrained. Candidate constraints in music include the importance of the octave and other simple pitch ratios, the categorization of the octave into tones, the importance of melodic contour, tonal hierarchies, and principles of (...) grouping and meter. Second, we advocate combining psychological, neuroscience, and genetic research across cognitive domains to address the domain specificity of such constraints. Currently available evidence suggests that the innate constraints in music are not specific to that domain, making it unclear which domain(s) provided the relevant selection pressures. (shrink)

Objective: Traditionally, asymmetric spatial processing has been assessed with paper-and-pencil tasks, but growing evidence indicates that computer-based methods are a more sensitive assessment modality. It is not known, however, whether simply converting well-established paper-and-pencil methods into a digital format is the best option. The aim of the present study was to compare sensitivity in detecting contralesional omissions of two different computer-based methods: a “digitally converted” cancellation task was compared with a computer-based Visual and Auditory dual-tasking approach, which has already proved (...) to be very sensitive.Methods: Participants included 40 patients with chronic unilateral stroke in either the right hemisphere or the left hemisphere and 20 age-matched healthy controls. The cancellation task was implemented on a very large format or in a smaller paper-and-pencil version. The computer-based dual-tasks were implemented on a 15′′ monitor and required the detection of unilateral and bilateral briefly presented lateralized targets.Results: Neither version of the cancellation task was able to show spatial bias in RH patients. In contrast, in the Visual dual-task RH patients missed significantly more left-sided targets than controls in both unilateral and bilateral trials. They also missed significantly more left-sided than right-sided targets only in the bilateral trials of the Auditory dual-task.Conclusion: The dual-task setting outperforms the cancellation task approach even when the latter is implemented on a screen. Attentionally demanding methods are useful for revealing mild forms of contralesional visuospatial deficits. (shrink)

Recent scholarship has helped to demythologise the life and work of Georg Philipp Friedrich von Hardenberg who, as the poet “Novalis”, had come to instantiate the nineteenth-century’s stereotype of the romantic poet. Among Hardenberg’s interests that seem to sit uneasily with this literary persona were his interests in science and mathematics, and especially in the idea, traceable back to Leibniz, of a mathematically based computational approach to language. Hardenberg’s approach to language, and his attempts to bring mathematics (...) to bear on poetry, is examined in relation to debates that developed late in the eighteenth century over the relation of language to thought—debates which share many features with contemporary ones in this area. (shrink)

Language assessment literacy is a significant component of language teachers’ expertise but is also a challenging task for most language teachers. To date, there have been relatively few studies examining the research on teachers’ LAL during these decades. To fill this void, this article reviews the conceptualizations of LAL and relevant empirical studies published from 1991 to 2021. It first analyzes various conceptualizations of LAL. Then in examining the empirical studies on teachers’ LAL, five major themes emerge: (...) teachers’ LAL levels; factors influencing LAL; language teachers’ assessment training needs; language assessment training courses; and LAL development through reflection. Finally, future research directions on teachers’ LAL are discussed. (shrink)

In this paper we investigate the problem of testing the coherence of an assessment of conditional probability following a purely logical setting. In particular we will prove that the coherence of an assessment of conditional probability χ can be characterized by means of the logical consistency of a suitable theory T χ defined on the modal-fuzzy logic FP k (RŁΔ) built up over the many-valued logic RŁΔ. Such modal-fuzzy logic was previously introduced in Flaminio (Lecture Notes in Computer Science, vol. (...) 3571, 2005) in order to treat conditional probability by means of a list of simple probabilities following the well known (smart) ideas exposed by Halpern (Proceedings of the eighth conference on theoretical aspects of rationality and knowledge, pp 17–30, 2001) and by Coletti and Scozzafava (Trends Logic 15, 2002). Roughly speaking, such logic is obtained by adding to the language of RŁΔ a list of k modalities for “probably” and axioms reflecting the properties of simple probability measures. Moreover we prove that the satisfiability problem for modal formulas of FP k (RŁΔ) is NP-complete. Finally, as main result of this paper, we prove FP k (RŁΔ) in order to prove that the problem of establishing the coherence of rational assessments of conditional probability is NP-complete. (shrink)

BackgroundSelf-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths, self-report multiple choice questionnaires have considerable limitations in nature. With the rise of machine learning and Natural language processing, researchers in the field of psychology are widely adopting NLP to assess psychological construct to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that of psychology due to small data sets (...) and unvalidated modeling practices.AimsThe current article introduces the study method and procedure of phase II which includes the interview questions for the five-factor model of personality developed in phase I. This study aims to develop the interview and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology, and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress. The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction.MethodsPhase I study was conducted to fifty-nine native Korean adults to acquire the personality-related text data from the interview and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 300 Korean adults will be recruited using a convenience sampling method via online survey. The text data collected from interviews will be analyzed using the natural language processing. The results of the online survey including demographic data, depression, anxiety, and personality inventories will be analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress. (shrink)