Language Resources Research Articles

Conflict Landscapes of the Great War: The Spatial and Ecological Dimension of Military History

The spatial and environmental dimension of WWI has recently taken the central place in academic debates on the military history of the “short twentieth century”. At present, the large-scale conflict of humanity and nature under totalized warfare is recognized as no less significant to the existential experience of combatants and civilians than actual battles. Functioning as a demiurge, the Great War created and re-molded landscapes, accelerated development trends shaped during the industrial era, triggered the construction and demolition of infrastructure, and determined the resource policy, economic practices, and language constructs of national communities during subsequent historical periods. Textual and visual narratives of the war feature the following three dimensions of the environment: a subject and adversary (sometimes even more dangerous than the real enemy); an object of destruction, invasion, and ordering; and an anthropological construct defining behavioral strategies and the memorial culture relating to the conflict. Modern researchers share a unanimous opinion that the pivotal role of the clash between humanity and the environment during WWI for subsequent historical development is paradoxically at odds with the degree to which the clash has been studied. This may be linked with the fact that the multidimensionality of militarized landscapes would require a research methodology incorporating elements of military history, ecology, anthropology, archaeology, geology (landscape studies), and cultural geography. Such a creative symbiosis has become possible only recently, owing to the adoption of the interdisciplinary approach by military historians. The gradual uptake of innovative study techniques has resulted in the uneven development of the spatial and environmental history of the First World War as a research field: at present, the best-studied locations are confined to the western front and, partly, the colonial periphery. This publication presents a review of the recent conceptual publications by authors developing this research avenue and seeks to identify the heuristic potential of the concepts “Anthropocene”, “belligerent landscapes”, “landscape biographies”, and “layered landscapes”, including their applicability to the history of the Eastern Front of the First World War.

Sharing Perceptual Experiences through Language.

The aim of this article is to shed light on how sensory perceptions are communicated through authentic language. What are the language resources available to match multimodal perceptions, and how do we use them in real communication? We discuss insights from previous work on the topic of the interaction of perception, cognition, and language and explain how language users recontextualise perception in communication about sensory experiences. Within the framework of cognitive semantics, we show that the complexities of multimodal perception are clearly reflected in the multifunctional use of words to convey meanings and feelings. To showcase the language resources employed, we base our findings on research on how architects convey their perceptions of built space. Two main patterns emerge: they use multimodal expressions (soft, bland, and jarring) and descriptions of built space through motion (the building reaches out, or routes and directions such as destination, promenade, route, or landscape in combination with verbs such as start and lead) in which case the architect may either be the observer or the emerged actor. The important take-home message is that there is no neat and clear a priori link between words and meanings, but rather "unforeseen" patterns surface in natural production data describing sensory perceptions.

Kencorpus: A Kenyan Language Corpus of Swahili, Dholuo and Luhya for Natural Language Processing Tasks

Indigenous African languages are categorized as under-served in Natural Language Processing. They therefore experience poor digital inclusivity and information access. The processing challenge with such languages has been how to use machine learning and deep learning models without the requisite data. The Kencorpus project intends to bridge this gap by collecting and storing text and speech data that is good enough for data-driven solutions in applications such as machine translation, question answering and transcription in multilingual communities. The Kencorpus dataset is a text and speech corpus for three languages predominantly spoken in Kenya: Swahili, Dholuo and Luhya (three dialects of Lumarachi, Lulogooli and Lubukusu). Data collection was done by researchers who were deployed to the various data collection sources such as communities, schools, media, and publishers. The Kencorpus' dataset has a collection of 5,594 items, being 4,442 texts of 5.6 million words and 1,152 speech files worth 177 hours. Based on this data, other datasets were also developed such as Part of Speech tagging sets for Dholuo and the Luhya dialects of 50,000 and 93,000 words tagged respectively. We developed 7,537 Question-Answer pairs from 1,445 Swahili texts and also created a text translation set of 13,400 sentences from Dholuo and Luhya into Swahili. The datasets are useful for downstream machine learning tasks such as model training and translation. Additionally, we developed two proof of concept systems: for Kiswahili speech-to-text and a machine learning system for Question Answering task. These proofs provided results of a performance of 18.87% word error rate for the former, and 80% Exact Match (EM) for the latter system. These initial results give great promise to the usability of Kencorpus to the machine learning community. Kencorpus is one of few public domain corpora for these three low resource languages and forms a basis of learning and sharing experiences for similar works especially for low resource languages. Challenges in developing the corpus included deficiencies in the data sources, data cleaning challenges, relatively short project timelines and the Coronavirus disease (COVID-19) pandemic that restricted movement and hence the ability to get the data in a timely manner.

Numeral Incorporation as Grammaticalization? A Corpus Study on German Sign Language (DGS)

Numeral incorporation describes the merging of a numeral sign with a lexical sign to create a single sign with a compositional meaning, e.g., “three weeks.” As a phenomenon of simultaneous morphology, numeral incorporation is unique to sign languages. While researchers disagree on the exact morphological structure of the construction, it has, thus far, mainly been described as a synchronic, phonological phenomenon. Using the DGS corpus, a language resource on German Sign Language, we explore the possibility of numeral incorporation resulting from a language change process, specifically a grammaticalization process. Our dataset comprises tokens belonging to nine different signs that may occur in numeral incorporations. We find a cline of three constructions in the corpus, which shows a progression from free morpheme to cliticized morpheme to bound morpheme (affix). A comparison of the usage frequency of the three constructions in different age groups reveals that signers use more incorporations the younger they are. Following the apparent time approach, these observations are taken as indicators of diachronic language change. We describe to what extent the properties of numeral incorporation fit with the grammaticalization hypothesis and conclude that while the emergence of numeral incorporation is an instance of language change and shows some aspects seen in grammaticalization, the gradual change fails to exhibit some crucial aspects of grammaticalization and, thus, should not be regarded as an example thereof.

Linguistically aware evaluation of coreference resolution from the perspective of higher-level applications

Abstract Coreference resolution is an important part of natural language processing used in machine translation, semantic search, and various other information retrieval and understanding systems. One of the challenges in this field is an evaluation of resolution approaches. There are many different metrics proposed, but most of them rely on certain assumptions, like equivalence between different mentions of the same discourse-world entity, and do not account for overrepresentation of certain types of coreferences present in the evaluation data. In this paper, a new coreference evaluation strategy that focuses on linguistic and semantic information is presented that can address some of these shortcomings. Evaluation model was developed in the broader context of developing coreference resolution capabilities for Lithuanian language; therefore, the experiment was also carried out using Lithuanian language resources, but the proposed evaluation strategy is not language-dependent.

Semi-Supervised Semantic Role Labeling with Bidirectional Language Models

The recent success of neural networks in NLP applications has provided a strong impetus to develop supervised models for semantic role labeling (SRL) that forego the requirement for extensive feature engineering. Recent state-of-the-art approaches require high-quality annotated datasets that are costly to obtain and almost unavailable for low-resource languages. We present a semi-supervised approach that utilizes both labeled and unlabeled data to provide performance improvement over a mere supervised SRL model. We show that our proposed semi-supervised SRL model provides larger improvement over a supervised model in the scenario where labeled training data size is small. Our SRL system leverages unlabeled data under the language modeling paradigm. We demonstrate that the incorporation of a self pre-trained bidirectional language model (S-PrLM) into a SRL system can help in SRL performance improvement by learning composition functions from the unlabeled data. Previous researches have concluded that syntax information is very useful for high-performing SRL systems, so we incorporate syntax information by employing an unsupervised approach to leverage dependency path information to connect argument candidates in vector space, which helps in distinguishing arguments with similar contexts but different syntactic functions. The basic idea is to connect predicate ( w p ) with argument candidate ( w a ) with the dependency path ( r ) between them in the embedding space. Experiments on the CoNLL-2008 and CoNLL-2009 datasets confirm that our full SRL model outperforms previous best models in terms of F 1 score.

Detection of Offensive Language and ITS Severity for Low Resource Language

Continuous proliferation of hate speech in different languages on social media has drawn significant attention from researchers in the past decade. Detecting hate speech is indispensable irrespective of the scale of use of language, as it inflicts huge harm on society. This work presents a first resource for classifying the severity of hate speech in addition to classifying offensive and hate speech content. Current research mostly limits hate speech classification to its primary categories, such as racism, sexism, and hatred of religions. However, hate speech targeted at different protected characteristics also manifests in different forms and intensities. It is important to understand varying severity levels of hate speech so that the most harmful cases of hate speech may be identified and dealt with earlier than the less harmful ones. In this work, we focus on detecting offensive speech, hate speech, and multiple levels of hate speech in the Urdu language. We investigate three primary target categories of hate speech: religion, racism, and national origin. We further divide these categories into levels based on the severity of hate conveyed. The severity levels are referred to as symbolization , insult , and attribution . A corpus comprising more than 20,000 tweets against the corresponding hate speech categories and severity levels is collected and annotated. A comprehensive experimentation scheme is applied using traditional as well as deep learning–based models to examine their impact on hate speech detection. The highest macro-averaged F-score yielded for detecting offensive speech is 86% while the highest F-scores for detecting hate speech with respect to ethnicity, national origin, and religious affiliation are 80%, 81%, and 72%, respectively. This shows that results are very encouraging and would provide a lead towards further investigation in this domain.

Using Data Augmentation and Bidirectional Encoder Representations from Transformers for Improving Punjabi Named Entity Recognition

Named entity recognition (NER) is a task of proper noun identification from natural language text and classification into various types such as location, person, and organization. Due to NER's applications in different natural language processing (NLP) tasks, numerous NER approaches and benchmark datasets have been proposed. However, developing NER techniques for low-resource languages is still limited due to the absence of substantial training datasets. Punjabi is a classic example of low resource language. Although various researchers have worked on Punjabi, they focused on the Gurmukhi script. To overcome the challenges in developing NER for the Shahmukhi script, we present an improved technique for Punjabi NER for the Shahmukhi script in this paper. We firstly extend the existing dataset by adding new NER classes by leveraging a novel Pool of Words data augmentation strategy. Our extended dataset has 11,31,509 tokens and 1,25,789 labeled entities with more named entities (NEs) than the older dataset. In the next step, we fine-tuned a transformer model known as Bidirectional Encoder Representations from Transformers (BERT) for the NER task. We performed experiments using the proposed approach on a new and older dataset version, showing that our method achieved competitive results.

The role of academic libraries in the context of national education policy (NEP)-2020

The National Education Policy (NEP) 2020 aims to transform the education system in India by focusing on holistic and multi-disciplinary education, promoting critical thinking, and creating a learner-centric approach. In this context, academic libraries have an important role to play in supporting the NEP's objectives. This structured abstract is based on a review of the literature related to the role of academic libraries in supporting the NEP 2020. Academic libraries have a significant role in supporting the NEP 2020 by providing access to diverse and quality resources, promoting lifelong learning, facilitating research and innovation, fostering collaboration and networking, and enhancing digital literacy skills. Academic libraries can also contribute to the NEP's goal of promoting multilingualism by providing resources in different languages. Academic libraries have a crucial role to play in supporting the NEP 2020's vision of transforming the education system in India. By providing access to diverse and quality resources, promoting lifelong learning, and enhancing digital literacy skills, academic libraries can contribute to creating a learner-centric and holistic education system.

Magical Realism as the Third Eye: A Postcolonial Re- reading of Ben Okri's The Famished Road

The Famished Road , a novel published in 1991 by Okri which won the Booker Prize . The novel can be interpreted as political allegory , a type of literature in which the characters and events in the text " represent , or ' allegorize , ' historical personages and events , " enabling narrative to serve as a model for political discourse . This article introduces postcolonial studies , focusing particularly on African postcolonial literature . And it also. deals with Hybridizing Political Criticism in The Famished Road : A Study of the Abiku Life " , deals with one of the most important postcolonial aspects called hybridity and how it is reflected in the very nature of its abiku protagonist , Azaro and the rest of the characters . The third chapter titled " Recreating Fragmented Histories of Post colonial Societies " , discusses how the resources of language that have been used to establish the themes of the supernatural and the colonial power . The concluding chapter comes up with a closure where the ideas discussed in the previous chapters are consolidated and establishes Okri's affirmation of Nigeria's complex identity .

The Construal of Specificity in Modification in English

Abstract This study investigates the significance of the construal of specificity in syntax, particularly in modification. In Cognitive Grammar, conceptualizing a situation can be either specific or conversely schematic. Namely, the two conceptualizations focus attention on greater or lesser detail of certain aspects of a situation. Each conceptualization describes the same content but in a peculiar way, and thus results in a distinct meaning. Making use of the language resources, the speaker can map the conceptualizations into different modes of modification: syntactic device by which a noun is accompanied by preceding and/or following modifiers. The aim of the study is to show that the use of a linguistic expression is motivated by the particular construal imposed on its conceptual content relative to communicative purposes. One of the key findings of the study is that specificity intensifies a description and makes it concrete, whereas schematicity attenuates a description and makes it abstract.

ChatGPT failed Taiwan's Family Medicine Board Exam.

Chat Generative Pre-trained Transformer (ChatGPT), OpenAI Limited Partnership, San Francisco, CA, USA is an artificial intelligence language model gaining popularity because of its large database and ability to interpret and respond to various queries. Although it has been tested by researchers in different fields, its performance varies depending on the domain. We aimed to further test its ability in the medical field. We used questions from Taiwan's 2022 Family Medicine Board Exam, which combined both Chinese and English and covered various question types, including reverse questions and multiple-choice questions, and mainly focused on general medical knowledge. We pasted each question into ChatGPT and recorded its response, comparing it to the correct answer provided by the exam board. We used SAS 9.4 (Cary, North Carolina, USA) and Excel to calculate the accuracy rates for each question type. ChatGPT answered 52 questions out of 125 correctly, with an accuracy rate of 41.6%. The questions' length did not affect the accuracy rates. These were 45.5%, 33.3%, 58.3%, 50.0%, and 43.5% for negative-phrase questions, multiple-choice questions, mutually exclusive options, case scenario questions, and Taiwan's local policy-related questions, with no statistical difference observed. ChatGPT's accuracy rate was not good enough for Taiwan's Family Medicine Board Exam. Possible reasons include the difficulty level of the specialist exam and the relatively weak database of traditional Chinese language resources. However, ChatGPT performed acceptably in negative-phrase questions, mutually exclusive questions, and case scenario questions, and it can be a helpful tool for learning and exam preparation. Future research can explore ways to improve ChatGPT's accuracy rate for specialized exams and other domains.

Speech Synthesis in the “Mother Tongue”: Designing, Training, and Evaluating a Text-to-Speech System for Yiddish

Abstract Although few linguistic corpora are available in Yiddish, there are numerous sources of so-called “found data” that can be adapted for language research, pedagogy, and resource development. We describe the steps taken to create the first speech synthesis (text-to-speech) program in Yiddish. A state-of-the-art TTS model, FastSpeech 2, was trained on a hand-corrected data set consisting of literary texts paired with audio narrations by native speakers of the Polish and Lithuanian dialects. A quantitative evaluation by listeners found that the system produced speech that was both intelligible and natural-sounding. To demonstrate the system’s applications for language pedagogy, we offer a qualitative evaluation of Yiddish phonological features that are present or absent in a sample of synthesized recordings. We hope that the success of speech synthesis in Yiddish will inspire future projects to enable technological support for other minority languages in which transcribed recordings are available.

Using SFL-based text analysis to inform instruction for emergent bilingual learners

Emergent Bilingual Learners (EBs) need language-focused instructional support if they are to access content, make meaning, and engage critically with academic texts in English. Text analysis informed by systemic functional linguistics (SFL) helps teachers identify “the language of schooling” (Schleppegrell, 2004) which they will need to make visible to their students. The authors, both teacher educators in an ESOL endorsement program, recognize that both the teacher candidates who are analyzing texts and the students whose instruction will be informed by the analysis engage in literacy practices that may not be recognized and valued by all teachers or aligned with the language demands of mandatory, high-stakes assessments. With that in mind, we envision a text analysis assignment that promotes language as meaning based, rather than rule based, and additive, rather than subtractive (Garcia, 2009) in terms of the language resources of teachers and students in language learning settings. Additionally, we look for ways to support our teacher candidates in interrogating texts critically as part of their analysis to uncover dominant perspectives. This practice-based article models the process of SFL-based text analysis facilitated by a text analysis tool we designed. The goal is that teachers can apply what they have learned from their analysis to create language-focused instruction that both supports academic language learning and promotes critical stances towards the connections between language choices and meaning making in specific academic contexts/disciplines. Additionally, we encourage teachers to use a variation of this text analysis format with students to explore how language is used in the text to develop all languages in the students' linguistic repertoire.

Динамика лексикона молодежных субкультур (по материалам интернет-форумов)

The article examines the dynamic processes in the sphere of subcultural language nomination and their socio-cultural conditionality. The research is carried out on the material that has not been previously considered in the dynamic aspect (slang of football fans, hip-hop culture, and k-pop representatives), new words of student slang are involved, the dynamics of which is currently studied unsystematically. The replenishment of the lexicon of these subcultures is revealed in the projection of modern material on the slang dictionaries of the past years. In the course of the study, the thematic dominants in the field of slang innovations were identified (names of representatives of subcultures and their idols, names of types of subcultural activities and their products). Among the main socio-cultural factors that led to updating the vocabulary of subcultures, transformations in the higher education system (student slang), youth music fashion (slang of the subcultures of k-pop and hip-hop), rotation of players in the team (slang of football fans) were noted. The lexicon of musical subcultures is replenished mainly by transliterated borrowings. The slang of students and football fans is updated due to the native language resources used by nominators in acts of univerbation, abbreviation, suffix word formation. In these areas, the special productivity of the nomination game techniques (phonetic mimicry, structural and semantic phraseological transformations) was noted, which indicates a high level of linguistic creativity of slang speakers.

Impact on Mental Health of Immigrants: When Will the World Stop?

Providing language resources and support can help reduce the impact of language barriers on the mental health of immigrants and help them better integrate into their new communities. Immigrants can experience trauma, social isolation, discrimination, cultural dissonance and language barriers, which can lead to mental health issues such as anxiety, depression and PTSD.

Exploring L2 students’ experiences with an integrated teacher written and spoken feedback strategy

AbstractThis qualitative case study explores second‐language (L2) students’ experiences through their sequential exposure to teacher written and spoken feedback that was offered from a meaning‐making perspective (i.e., the perspective that highlights the relationship between language resources and meaning). The study drew on L2 students’ interviews, reflections, their sequential interactions with teacher written and spoken feedback, and their writing pieces collected from an English writing course at a Chinese university. The study showed that meaning‐making‐based teacher written feedback afforded L2 students time to independently digest and address their writing issues related to the relationship between language and meaning, despite the observable confusions students encountered. Echoing teacher written feedback, teacher spoken feedback, as a follow‐up, further highlighted writing as a meaning‐making process, dynamically helping the students to understand or challenge the written feedback and mitigating contextual constraints on their uptake of teacher written feedback. These findings underscore the usefulness of sequentially implementing teacher written and spoken feedback, especially from a meaning‐making perspective, to sensitize L2 students to the relationship between language and meaning and to enhance their success in writing.

Graduating points of view in Spanish written language

Abstract This paper focuses on some language resources for graduating points of view in written Spanish language in the field of history. The analysis is framed in systemic functional linguistic theory, a multifunctional theory of language (Halliday with Matthiessen 2014), and focuses on the appraisal system, which organises interpersonal meanings at the stratum of discourse semantics in language (Martin and White 2005; Martin 2019; White 2021). In particular, it considers the coupling and necessary complementarity of graduation and engagement subsystems, as part of the appraisal system, for building intersubjectivity in texts. To achieve this purpose, the analysis explores the role of the Spanish lexicogrammatical system of modality (modalisation and modulation) in the construction of dialogicity in historical documents.

Dialogic co-creation in English language teaching and learning: a personal experience

Abstract This report will discuss the development and implementation of a dialogic co-creation model for English language teaching in the Language Resource Centre at the Technical University of Darmstadt, Germany. The focus of this report will be on the impact of content co-creation and its impact on learner and teacher autonomy in English language learning and teaching. This collaborative, dialogic model draws primarily on principles of dialogism and exploratory talk (ET) and exemplifies a novel, learner-centered method for curriculum development and teaching in Higher Education. This learner-centered perspective advances an in-depth understanding of the relationship between language learner and teacher, content and language integrated learning (CLIL), language for specific purposes (LSP), their respective content boundaries, the role of content expert and the inhibition threshold. Three examples of teaching English to university professors and professional staff using this model will be discussed. The author proposes that such a model could be adapted and scaled into larger student groups, too.

“Welcome to pure food city”: tracing discourses of health in the promotional publications of the Postum Cereal Company, 1920-1925

PurposeThis paper aims to investigate three promotional publications produced by the Postum Cereal Company – A Trip Through Postumville (1920), How I Make Postum (1924) and The Wonderful Lunch Boxes (1925) – with the aim of understanding how language and other semiotic resources are used to promote its products as good and healthy choices.Design/methodology/approachThe three publications were collected from the HathiTrust Digital Library and University of South Florida Tampa Special Collections. They were subjected to multimodal critical discourse analysis to tease out their subtle characteristics and how a combination of language, image, colour, typography and composition are used to represent certain ideas and values related to health and well-being.FindingsThe publications subscribe to three distinct genres – “inside the factory”, “friendly spokesperson” and “fictional world” – each of which are aimed at different target audiences. The first seeks to promote Postum as an open and transparent company; the second to promote Postum as a company that cares about its consumers; and the third to promote the health benefits of Postum in a fun and accessible manner. Nonetheless, they are united in their overall objective to link the regular consumption of Postum as essential for good health.Originality/valueTo date, few studies have been conducted on the Postum Cereal Company, while the limited research conducted on promotional publications has tended to overlook discourses of health and well-being. The three genres outlined in this study, thus, have the potential to foster a reappraisal of promotional publications and showcase their ability to offer new understandings on historical approaches to marketing, particularly the link with health and science.