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Most approaches to discourse markers tend to rely on observation on the behavior of monolingual classes of markers. In this paper, we offer a detailed analysis of the behavior and function of a single Spanish discourse marker, namely bueno , in bilingual discourse as opposed to its bilingual counterpart well. In particular, we compare pragmatic factors, and namely fine-grained differences between Spanish bueno and English well , with interactional factors such as the position of the marker in monological vs. dialogical sequences. Finally, we also take into account the impact of individual linguistic choices by comparing the behavior of different speakers when using the scrutinized discourse marker. Thus, we do not only contribute to and expand on previous literature on the behavior of discourse markers, but we also offer a new perspective to further study discourse markers in situations of language contact. • The paper explains the behavior of a single Spanish DM and its English counterpart in bilingual discourse. • A methodology based on online focus groups is used to explore the functionality of the discourse marker in interactions. • The paper finds a broad range of interpersonal functions that explain the use of bueno in bilingual discourse. • An underexplored community is proposed as a focal point in the study of contact and pragmatics. [ABSTRACT FROM AUTHOR]

This paper explores the procedural meaning of the Spanish adverb apenas , proposing that it carries the procedural meaning of right-hand APPROACHING. This procedural meaning effectively accounts for various interpretations and argumentative orientations of apenas in different contexts. The analysis demonstrates that apenas consistently implies a closeness or minimality, whether in quantitative or temporal domain. The procedural meaning also explains the negative argumentative orientation of apenas. Therefore, the different meanings of apenas can be analyzed in a holistic way. Through this analysis, the study aims to contribute to a deeper understanding of adverbial usage in Spanish and potentially guide analogous investigations in other languages. • The Spanish adverb apenas carries a procedural meaning. • The procedural meaning can offer a holistic analysis of this adverb. • The procedural meaning also explains the negative argumentative orientation of apenas. [ABSTRACT FROM AUTHOR]

• Si -future exclamatives in Spanish shed new light into the notion of insubordination. • Mirative future emerges as a result of successive emancipations. • Mirative future is compatible with the 'distance-forward' deictic template. • Mirative future represents a further step into the process of grammaticalization. • Mirative future exemplifies the range of mirative meaning conveyed in Spanish. This paper examines si -future exclamatives in Spanish, both synchronically and diachronically, with the aim not only of identifying their possible contexts of use but also of distinguishing their various semantic interpretations. In addition to permitting the redefinition of the space of insubordination and assessing the role of analogy in the continuing independence of the marker si , this proposal provides an explanation of Spanish mirative future as emerging from the emancipation of a previous structure, albeit that it retains the deictic value of morphological future –which becomes a functional feature in its new discursive meaning. From this perspective, the grammaticalization of morphological future in Spanish is not contemplated as a closed cycle, but rather as a still ongoing process. More broadly speaking, this paper helps outline the semantic array of mirative meanings through providing evidence about the type of mirativity that can be conveyed in Spanish. [ABSTRACT FROM AUTHOR]

People formulate places for different interactional goals (e.g., arranging meeting up with one another, giving directions). Although most research agrees that using names or numbers for streets is common, there are cultural realities that imply using other resources accessible to participants. This paper examines place formulation when there are not street numbers available. Data come from audio-recorded telephone calls to 911 Costa Rica. The study uses the method of Conversation Analysis combined with ethnography. Findings show that participants use three formulations: geographical, landmarks and "other signs". This paper shows that such formulations correspond to levels of granularity, and that there is cultural diversity when formulating place. • Participants use three interactional practices when formulating place. • Geographical formulations use the country's division: province, county, district. • Landmark formulations are comprised of the landmark, distance and direction. • "Other signs" formulations describe details or physical characteristics of places. • These formulations correspond to different levels of description used by callers. [ABSTRACT FROM AUTHOR]

• End-to-end lite-transformer for full pages handwritten text recognition. • The curriculum learning strategy allows the model to be trained using limited data. • The model can be easily adapted to other scripts by a simple transfer-learning process using only page-level labeled images. • Extensive comparative experiments are conducted on multiple languages: English, French, Spanish, and Arabic. The Transformer has quickly become the dominant architecture for various pattern recognition tasks due to its capacity for long-range representation. However, transformers are data-hungry models and need large datasets for training. In Handwritten Text Recognition (HTR), collecting a massive amount of labeled data is a complicated and expensive task. In this paper, we propose a lite transformer architecture for full-page multi-script handwriting recognition. The proposed model comes with three advantages: First, to solve the common problem of data scarcity, we propose a lite transformer model that can be trained on a reasonable amount of data, which is the case of most HTR public datasets, without the need for external data. Second, it can learn the reading order at page-level thanks to a curriculum learning strategy, allowing it to avoid line segmentation errors, exploit a larger context and reduce the need for costly segmentation annotations. Third, it can be easily adapted to other scripts by applying a simple transfer-learning process using only page-level labeled images. Extensive experiments on different datasets with different scripts (French, English, Spanish, and Arabic) show the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

This paper analyzes impoliteness-related language in response to a season's greeting posted by the Prime Ministers of Spain and the UK on December 2022 to wish Twitter users a Felices Fiestas/Merry Christmas. A corpus made up of the first 500 tweet events mentioning Sánchez and Johnson with the @ feature was analyzed through the combination of qualitative and quantitative tools and an impoliteness2 approach to compare the most commonly deployed impoliteness strategies in response to what is felt as an offense by respondents from the two cultures. Previous impoliteness taxonomies inform the analysis (Culpeper, 1996 , 2011). Findings reveal a preference for on-record strategies vs. off-record ones in both corpora. Whereas the English respondents oriented themselves towards attacking the negative face of the Prime Minister and that of other participants with sarcasm and implicated impoliteness, the Spanish group deployed impoliteness-related language to disparage the Prime Minister's positive face through insults and the rectification of his words. The hostile acts and explicit metalanguage about emotional states in the replies to the expressive speech act corroborate the perceived breach of some aspects of the moral order on the part of the Twitter users in the out-group, hence aiding the already observed polarization of political discussions. • Impoliteness is analyzed in replies to the season's greetings of Pedro Sánchez and Boris Johnson on Twitter. • Findings indicate that on-record impoliteness strategies are more frequent than off-record ones in both groups. • English respondents use negative-face attacking strategies, sarcasm, and implicated impoliteness in their replies. • Spanish respondents deploy insults and attacks on the positive public face of the Prime Minister as favored strategies. • Impoliteness-related discourse is multifunctional and aims to restore the moral order that is perceived as altered. [ABSTRACT FROM AUTHOR]

• Chinese should be categorized as a discourse-configurational language, namely a Category III language under Miyagawa's typology. • Several compelling empirical facts are presented to demonstrate that the δ-feature lowers to T in Chinese. • Chinese wh -adverbial zenme 'how come' is not base-generated in the CP periphery, but rather inserted in the TP. Assuming the Strong Uniformity Principle, Miyagawa recently proposed a typology of languages based on distinct patterns of Feature Inheritance at Phase C. In this typology, Chinese is identified as a Category II language (with the δ-feature on C and the φ-feature on T). That is, Chinese is regarded as a non-discourse-configurational language similar to English. This paper aims to review Miyagawa's discussion of Chinese and argue for its reclassification as a Category III language, that is, a discourse-configurational language like Spanish. I contend that Miyagawa's discussion of Chinese only pertains to Aboutness-shift topic, a type of topic base-generated in the CP domain across languages; as a result, his conclusions are unsustainable. On the other hand, I show that phenomena like Object Preposing, forced A-focalization, and the distribution of Familiar and Contrastive topics in non-assertive embedded clauses provide compelling evidence that the δ-feature has lowered to T in Chinese. Finally, I address a potential counterargument presented by the Chinese wh -adverbial zenme 'how come'. I argue that zenme is not base-generated in the CP periphery, but rather inserted in the TP layer. [ABSTRACT FROM AUTHOR]

Author profiling consists of extracting their demographic and psychographic information by examining their writings. This information can then be used to improve the reader experience and to detect bots or propagators of hoaxes and/or hate speech. Therefore, author profiling can be applied to build more robust and efficient Knowledge-Based Systems for tasks such as content moderation, user profiling, and information retrieval. Author profiling is typically performed automatically as a document classification task. Recently, language models based on transformers have also proven to be quite effective in this task. However, the size and heterogeneity of novel language models, makes it necessary to evaluate them in context. The contributions we make in this paper are four-fold: First, we evaluate which language models are best suited to perform author profiling in Spanish. These experiments include basic, distilled, and multilingual models. Second, we evaluate how feature integration can improve performance for this task. We evaluate two distinct strategies: knowledge integration and ensemble learning. Third, we evaluate the ability of linguistic features to improve the interpretability of the results. Fourth, we evaluate the performance of each language model in terms of memory, training, and inference times. Our results indicate that the use of lightweight models can indeed achieve similar performance to heavy models and that multilingual models are actually less effective than models trained with one language. Finally, we confirm that the best models and strategies for integrating features ultimately depend on the context of the task. • Study of large language models for conducting Author Profiling in Spanish. • Feature integration improves the performance of large language models. • Interpretability of profiles using linguistic features. • Hyperlinks and hashtag are strong features when discerning between bots and humans. • Stylometry is the linguistic category most relevant in Author Profiling. [ABSTRACT FROM AUTHOR]

This paper investigates the intersection between gender and foreign language education with specific reference to subject choice, motivation, and achievement. The study was carried out at a Ghanaian public university, amongst students of the following Bachelor of Arts foreign language programmes: Arabic, Chinese, French, Kiswahili, Russian and Spanish. Through a thematic analysis of transcribed focus group discussions and desk-research of relevant administrative documents, the authors inquire why a gender enrolment gap exists in the foreign language programmes and if indeed, certain languages are perceived as more masculine than others. The findings of the study confirm the existence of a gender gap in foreign language education. Participants also considered some languages such as Spanish and French as more feminine. Regarding their motivation, participants noted both integrative and instrumental factors that motivated them to study the foreign language. Additionally, the study found no statistical significance between the performance of females and males. However, males performed slightly better than females in Arabic, French, Kiswahili and Russian whereas females performed better in Spanish and Chinese. [ABSTRACT FROM AUTHOR]

The wide adoption of electronic health records (EHRs) offers immense potential as a source of support for clinical research. However, previous studies focused on extracting only a limited set of medical concepts to support information extraction in the cancer domain for the Spanish language. Building on the success of deep learning for processing natural language texts, this paper proposes a transformer-based approach to extract named entities from breast cancer clinical notes written in Spanish and compares several language models. To facilitate this approach, a schema for annotating clinical notes with breast cancer concepts is presented, and a corpus for breast cancer is developed. Results indicate that both BERT-based and RoBERTa-based language models demonstrate competitive performance in clinical Named Entity Recognition (NER). Specifically, BETO and multilingual BERT achieve F-scores of 93.71% and 94.63%, respectively. Additionally, RoBERTa Biomedical attains an F-score of 95.01%, while RoBERTa BNE achieves an F-score of 94.54%. The findings suggest that transformers can feasibly extract information in the clinical domain in the Spanish language, with the use of models trained on biomedical texts contributing to enhanced results. The proposed approach takes advantage of transfer learning techniques by fine-tuning language models to automatically represent text features and avoiding the time-consuming feature engineering process. • A deep learning-based approach for extracting breast cancer information from clinical narratives written in Spanish. • A comprehensive annotation scheme to represent medical concepts in the breast cancer domain. • A corpus manually annotated by clinicians for supporting clinical named entity recognition in the breast cancer domain. • Experiments on transformer-based language models to extract information using a breast cancer corpus. • A method to exploit transfer learning to perform cancer named entity recognition using language models that avoids feature engineering processes. [ABSTRACT FROM AUTHOR]

• The results show that the ChatGPT summary obtained the best marks in terms of content and style, with its respective marks being 3 and 2.5 points higher than those of the students. • These results are independent of the ages, levels of professional experience, and genders of the teachers who corrected the summary. • The emergence of generative AIs such as ChatGPT generates a number of ethical, methodological, and evaluative considerations that must be taken into account in the development of student training. This paper presents a research study that evaluated the score ChatGPT would get when summarizing a reading comprehension text from the PISA international tests with a prompt that made it simulate doing this as if it were a 15-year-old student. For this purpose, the text was camouflaged among 30 other summaries made by real 15-year-old students and was evaluated by 30 Spanish language teachers with different profiles in terms of age, professional experience, and gender who were unaware that one of the texts was made by artificial intelligence (AI). The evaluation of the summary, for which a homogeneous rubric is used, is based on two fundamental criteria: content and style. For the data analysis descriptive and inferential statistical techniques were used. The results show that the ChatGPT summary obtained the best marks in terms of content and style, with its respective marks being 3 and 2.5 points higher than those of the students. Therefore, we can deduce that the style and content of the ChatGPT summary greatly exceeded those presented by the students. These results are independent of the ages, levels of professional experience, and genders of the teachers who corrected the summary. The integration of AI tools such as ChatGPT must be based on solid methodological proposals that integrate their use from a creative and critical perspective that allows learning with the support of these tools and not using them as substitutes for the development of basic student competencies. [ABSTRACT FROM AUTHOR]

Detecting and normalizing temporal expressions is an essential step for many NLP tasks. While a variety of methods have been proposed for detection, best normalization approaches rely on hand-crafted rules. Furthermore, most of them have been designed only for English. In this paper we present a modular multilingual temporal processing system combining a fine-tuned Masked Language Model for detection, and a grammar-based normalizer. We experiment in Spanish and English and compare with HeidelTime, the state-of-the-art in multilingual temporal processing. We obtain best results in gold timex normalization, timex detection and type recognition, and competitive performance in the combined TempEval-3 relaxed value metric. A detailed error analysis shows that detecting only those timexes for which it is feasible to provide a normalization is highly beneficial in this last metric. This raises the question of which is the best strategy for timex processing, namely, leaving undetected those timexes for which is not easy to provide normalization rules or aiming for high coverage. [ABSTRACT FROM AUTHOR]

• Linguistic domains (vocabulary, phonetics, syntax) do not change independently in the development of languages. • Relationships among linguistic domains do not follow a uniform or universal pattern. • Linguistic distances between all of the modern languages predict traditional phylogenetic trees to a high degree. Languages differ along multiple dimensions (lexis, phonology, morphology, syntax). Related languages descend from a common ancestor language but have diverged over time. This paper asks whether languages diverge equally along all dimensions, and, to the extent that they do not, which dimension reflects the traditional language family tree best. We computed measures of (i) lexical distance (ii) phonetic distance, and (iii) syntactic distance. The measures were computed on all words and sentences extracted from a corpus of translations of four relatively short English texts into another four Germanic languages (Danish, Dutch, German, Swedish), five Romance languages (French, Italian, Portuguese, Romanian, Spanish) and six Slavic languages (Bulgarian, Croatian, Czech, Polish, Slovakian, Slovenian). We examined the correlation structure of the distances for all pairs of Germanic (10), Romance (10) and Slavic (15) languages (i.e., within-family comparisons only). The results indicate that the linguistic dimensions are generally correlated (weakly but significantly), and that the correlations are stronger for pairs within families than when all 35 pairs are examined together. Cladistic family trees correlate best with the lexical distance (0.851 < r < 0.887). This confirms that the genealogical language trees are predominantly based on lexical rather than phonetic or syntactic considerations. [ABSTRACT FROM AUTHOR]

• A tutor for learning the Spanish Sign Language basic hand configurations. • Hand landmark extraction from a sequence of images. • Similarities between configurations using Procrustes analysis. • Multidimensional scaling analysis of the clustering of the hand configurations. Communication between people from different communities can sometimes be hampered by the lack of knowledge of each other's language. A large number of people needs to learn a language in order to ensure a fluid communication or want to do it just out of intellectual curiosity. To assist language learners' needs tutor tools have been developed. In this paper we present a tutor for learning the basic 42 hand configurations of the Spanish Sign Language, as well as more than one hundred of common words. This tutor registers the user image from an off-the-shelf webcam and challenges her to perform the hand configuration she chooses to practice. The system looks for the configuration, out of the 42 in its database, closest to the configuration performed by the user, and shows it to her, to help her to improve through knowledge of her errors in real time. The similarities between configurations are computed using Procrustes analysis. A table with the most frequent mistakes is also recorded and available to the user. The user may advance to choose a word and practice the hand configurations needed for that word. Sign languages have been historically neglected and deaf people still face important challenges in their daily activities. This research is a first step in the development of a Spanish Sign Language tutor and the tool is available as open source. A multidimensional scaling analysis of the clustering of the 42 hand configurations induced by Procrustes similarity is also presented. [ABSTRACT FROM AUTHOR]

• Faculty members are key players in promoting the inclusion of students with disabilities. • We propose guidelines for faculty members to carry out an inclusive pedagogy in their classes. • Relationships, resources, methodologies, adjustments, mentoring and evaluation are indispensable. • The guidelines improve the quality of teaching and will benefit all students as a whole. This paper provides a useful guide of recommendations drawn from the experiences described by 25 Spanish inclusive faculty members of the area of Social and Legal Sciences. We used a qualitative methodology and data was gathered using interviews. The action guidelines and recommendations obtained are based on the implementation of an inclusive pedagogy that prioritises the participation and success of all students. The results are divided into six categories: faculty-student relationship, resources, methodology, reasonable adjustments, mentoring and evaluation. Lastly, this study shows that the teaching strategies that promote inclusion do not only benefit students with disabilities, but have a general positive effect on all students. [ABSTRACT FROM AUTHOR]