Bilingual Research Articles

Multi‐lingual encryption technique using Unicode and Riemann zeta function and elliptic curve cryptography for secured routing in wireless sensor networks

AbstractSecure routing and communication with confidentiality based on encryption of texts in multiple natural languages are challenging issues in wireless sensor networks which are widely used in recent applications. The existing works on Elliptic Curve Cryptography based secured routing algorithms are focused only on the encryption and decryption of single language text encrypted over a Prime finite field. In this article, a new algorithm called Multi‐Language ECC encrypted Secure Routing algorithm with trust management is proposed, in order to ensure confidentiality and integrity which focuses on the encryption of plain text using Riemann's zeta function and Elliptic Curve Cryptography for improving the key strength which is applied for encryption over a range of multi languages namely Tamil, English, Hindi French and German which are supported by Unicode and routing the text security. From the experiments conducted using the proposed multi‐lingual encryption algorithm with network routing, we prove that the suggested method provides greater security than the current secure routing algorithms due to the use of Zeta function and Gamma function with ECC key and trust management. but also boasts reduced complexity compared to other existing multi‐lingual encryption algorithms.

MULTI LINGUAL ASR WITH TRANSFORMERS

Recent research has focused on developing multilingual automatic speech recognition (ASR) systems using Transformer-based models. These models aim to address challenges in training and deploying ASR systems for low- resource languages, adapting to multiple domains and languages, and reducing operational costs. Strategies such as locale-group multilingual Transformer language models, adaptable multi- domain language models, and configurable multilingual models have been proposed to improve the performance and efficiency of multilingual ASR. These advancements demonstrate a concerted effort to overcome the challenges of low-resource languages, domain adaptation, and multilingual speech recognition.

Code-switching in the speech of a balanced infant bilingual and early talker

This case study investigates codeswitching in infant bilingualism and may be of special interest due to the fact that its participant is an early talker and a balanced bilingual. Drawing on English/Greek child data, it studies the relationship between language competence and type of code-switching from a developmental perspective, and aims to contribute to a deeper understanding of code-switching in infant bilinguals. Code-switching was facilitated by an early onset of syntax and is interpreted as an outcome of the child's growing grammatical and pragmatic competence, rather than of a lack of linguistic resources. The rich set of longitudinal data features situational, discourse-related and participant-related code-switching events, as well as rare contextualisation examples. Code-switching is observed to be a strategy to attain specific communicative goals, such as disambiguation, clarification, disagreement etc., and is constrained by the grammar of English and Greek and the principles of discourse and language use.

Multilingualism in performance appraisal interviews: strategies to bridge language gaps

This paper explores three multilingual strategies to bridge the lack of a shared first language as they are used during performance appraisal interviews, namely English as a business lingua franca, receptive multilingualism, and a lay interpreter. The study is based on authentic video-recorded performance appraisal interviews at a globally active Belgian company, and follow-up interviews with the managers. The analysis focuses on how the company deals with multilingualism from a management perspective, how the managers perceive these multilingual strategies from a language ideological perspective, and how these language ideological beliefs shape the language practices of the performance appraisal interviews. We conclude that this study provides novel insights into how globalized companies deal with multilingualism in the high-stakes and potentially sensitive interactional context of a performance appraisal interview by underlining the intertwined nature of language ideological beliefs and language practices as part of a broader multilingual language management strategy.

Multilingual Habitus and Language Prestige: Value Profiles of Croatian, English, German, and Italian in Croatia

In a multilingual world, languages represent various forms of capital in society and gain or lose prestige depending on how transferable they are perceived to be into social, cultural, economic, and symbolic capital. The dominance of the English language and social media content in the Information Age affects people’s language worldwide. In many countries, there is a significant trend toward diglossia, where the national language is used alongside English, leading to the marginalization of all other languages. In Croatia, an EU member state, the most popular foreign languages are English, German, and Italian. However, due to the linguistic dominance of English, foreign languages other than English have experienced a loss of status. This shift implies that people’s perceptions of the types of capital those languages represent are changing and that there is a movement from multilingualism toward diglossia. This goes against the strongly promoted idea of multilingualism in the EU, where language variety is considered a valuable form of symbolic and cultural capital. Within that framework, this study aims to examine the attitudes of multilingual speakers in Croatia toward the four languages included in the study. The goal is to determine whether they perceive a language to represent a form of social, cultural, economic, or symbolic capital. Furthermore, based on the results, it will be concluded whether multilingual language practice is affected and whether there is a clash between the desired multilingual habitus of European citizens and their perceptions of language values, which determine their language choices.

Federated learning for privacy-preserving depression detection with multilingual language models in social media posts

The incidences of mental health illnesses, such as suicidal ideation and depression, are increasing, which highlights the urgent need for early detection methods. There is a growing interest in using natural language processing (NLP) models to analyze textual data from patients, but accessing patients' data for research purposes can be challenging due to privacy concerns. Federated learning (FL) is a promising approach that can balance the need for centralized learning with data ownership sensitivity. In this study, we examine the effectiveness of FL models in detecting depression by using a simulated multilingual dataset. We analyzed social media posts in five different languages with varying sample sizes. Our findings indicate that FL achieves strong performance in most cases while maintaining clients' privacy for both independent and non-independent client partitioning.

Challenging the monolingual mindset: language teachers’ pushback and enactment of critical multilingual language awareness in Australian schools

ABSTRACT This study critically interrogates dominant discourses and practices in school settings, which reveal the legitimisation and perpetuation of a monolingual mindset. Through the lens of ‘Critical Multilingual Language Awareness’ (CMLA), this research unpacked the experiences and practices of language teachers who implement the New South Wales (NSW) mandated language curriculum and, where possible, create opportunities for adjustments to language syllabi for greater awareness of diversity and plurilingualism. Data was gathered through in-depth semi-structured interviews with four high-school language teachers at independent schools in NSW, Australia. The interview addressed teachers’ proficiency and knowledge of subject matter, their views of the (im)possibilities of the NSW language curriculum for developing plurilingual learners, and perceived challenges that appear to prevent multi/plurilingualism from being at the forefront of Australian language education. Findings revealed that despite teachers’ strong commitment to languages education, they feel discouraged about the limited focus at national and State government levels on consistent and systematic multilingual education. This not only diminishes every effort made by teachers to transform pedagogies for pedagogies for multilingualism but also legitimises a dominant underlying rhetoric of monolingualism that does not adhere to the principles of educating for democratic citizenship.

A tale of two English teachers: Examining narrative in multilingual writing and teaching

This paper examines how multilingual English language teachers use narrative for learning and teaching writing given their own writing practices and beliefs. The data was collected and analyzed using different narrative approaches to explore the advantages and disadvantages of each of these three models: Labov, Ochs and Capps, and De Fina & Georgakopoulou's Social Interactional Approach (SIA). Each model highlights different aspects of narrative. However, due to the contextual nature of multilingual writing, the SIA model proved to be the most comprehensive for knitting together teacher writing practices, beliefs about language-learning, and their pedagogies. Nevertheless, applying all three models proved useful for highlighting the dynamics of language use in different contexts along with multidimensional aspects of storytelling.

Family language policy in a transnational family living in Finland: multilingual repertoire, language practices, and child agency.

Each multilingual transnational family is unique and thus deserves to be carefully studied in terms of its family language policy (FLP). Speaker-centered approaches can provide a deeper understanding of linguistic diversity in a multilingual setting. The studied Russian-Italian family is raising a multilingual boy (8:2) in Finland. The multilingual repertoire includes Russian, Italian, Finnish, English, and Hebrew. In this case-study, an ethnographic approach is used to explore the multilingual family repertoire by presenting their lived experiences and language practices. I discuss the FLP and child's active role in shaping the family's linguistic practices (child agency). The following methods were combined: semi-structured interviews, language background surveys, written diary entries, self-recordings of interactions in the family, and a language portrait that depicts the child's multilingual repertoire. The interviews and other recordings were transcribed manually. The following research questions guided the study: (1) How do the family members describe their FLP? (2) How does the FLP evolve through everyday interactions (language practices)? (3) How does the child exercise his agency in the family setting? The results reveal that the family's language practices follow predominantly an one person-one language (OPOL) strategy; consequently, the child speaks a different language with each parent. However, the analysis of the language ideologies reveals positive attitudes toward both multilingualism and all the languages in the family's repertoire, which explains the multilingual practices having multiplicity and unexpectedness. FLP is shaping the family language practices. Evidence of language hierarchy can be explained by a number of family-external and family-internal social factors.

A Meta-Analysis of Anomia Treatment in Bilingual Aphasia: Within- and Cross-Language Generalization and Predictors of the Treatment Outcomes.

The present meta-analysis investigated the efficacy of anomia treatment in bilingual and multilingual persons with aphasia (BPWAs) by assessing the magnitudes of six anomia treatment outcomes. Three of the treatment outcomes pertained to the "trained language": improvement of trained words (treatment effect [TE]), within-language generalization of semantically related untrained words (WLG-Related), and within-language generalization of unrelated words (WLG-Unrelated). Three treatment outcomes were for the "untrained language": improvement of translations of the trained words (cross-language generalization of trained words [CLG-Tx]), cross-language generalization of semantically related untrained words (CLG-Related), and cross-language generalization of unrelated untrained words (CLG-Unrelated). This study also examined participant- and treatment-related predictors of these treatment outcomes. This study is registered in the International Prospective Register of Systematic Reviews (PROSPERO) under the number CRD42023418147. Nine electronic databases were searched to identify word retrieval treatment studies of poststroke BPWAs of at least 6 months postonset. Pre- and posttreatment single-word naming scores were extracted for each eligible participant and used to calculate effect sizes (within-case Cohen's d) of the six treatment outcomes. Random-effects meta-analyses were conducted to assess weighted mean effect sizes of the treatment outcomes across studies. Multiple linear regression analyses were used to examine the effects of participant-related variables (pretreatment single-word naming and comprehension representing poststroke lexical processing abilities) and treatment-related variables (type, language, and duration). The methodological quality of eligible studies and the risk of bias in this meta-analysis were assessed. A total of 17 published studies with 39 BPWAs were included in the meta-analysis. The methodological quality of the included studies ranged from fair (n = 4) to good (n = 13). Anomia treatment produced a medium effect size for TE (M = 8.36) and marginally small effect sizes for WLG-Related (M = 1.63), WLG-Unrelated (M = 0.68), and CLG-Tx (M = 1.56). Effect sizes were nonsignificant for CLG-Related and CLG-Unrelated. TE was significantly larger than the other five types of treatment outcomes. TE and WLG-Related effect sizes were larger for BPWAs with milder comprehension or naming impairments and for treatments of longer duration. WLG-Unrelated was larger when BPWAs received phonological treatment than semantic and mixed treatments. The overall risk of bias in the meta-analysis was low with a potential risk of bias present in the study identification process. Current anomia treatment practices for bilingual speakers are efficacious in improving trained items but produce marginally small within-language generalization and cross-language generalization to translations of the trained items. These results highlight the need to provide treatment in each language of BPWAs and/or investigate other approaches to promote cross-language generalization. Furthermore, anomia treatment outcomes are influenced by BPWAs' poststroke single-word naming and comprehension abilities as well as treatment duration and the provision of phonological treatment. https://doi.org/10.23641/asha.25595712.

Bilingual Language Dominance and Code-switching Patterns

Abstract Code-switching, the alternation between two languages in an interaction, is a salient characteristic of bilingual speech, but there is substantial variability in code-switching patterns among bilinguals. Language dominance, the relative strength of a bilingual’s languages, has been suggested as a key factor that impacts both the frequency with which a bilingual engages in code-switching and the directionality of code-switching. This study examines the relationship between language dominance and code-switching engagement and directionality. A total of 454 Spanish–English bilinguals completed questionnaires regarding language dominance, code-switching engagement, and code-switching directionality. Results demonstrated an impact of language dominance on code-switching engagement, with more balanced bilinguals reporting greater code-switching, although significant individual variation remained. A weak link between language dominance and directionality was also found. These findings suggest that while language dominance may serve to constrain a bilingual’s range of possible engagement with code-switching, it represents a distinct characteristic of a bilingual’s language profile.

Degree of multilingual engagement modulates resting state oscillatory activity across the lifespan

Multilingualism has been demonstrated to lead to a more favorable trajectory of neurocognitive aging, yet our understanding of its effect on neurocognition across the lifespan remains limited. We collected resting state EEG recordings from a sample of multilingual individuals across a wide age range. Additionally, we obtained data on participant multilingual language use patterns alongside other known lifestyle enrichment factors. Language experience was operationalized via a modified multilingual diversity (MLD) score. Generalized additive modeling was employed to examine the effects and interactions of age and MLD on resting state oscillatory power and coherence. The data suggest an independent modulatory effect of individualized multilingual engagement on age-related differences in whole brain resting state power across alpha and theta bands, and an interaction between age and MLD on resting state coherence in alpha, theta, and low beta. These results provide evidence of multilingual engagement as an independent correlational factor related to differences in resting state EEG power, consistent with the claim that multilingualism can serve as a protective factor in neurocognitive aging.

Screening for Cognitive Impairment in Bilinguals: What Is the Influence of the Language of Assessment?

Bilingualism's impact on cognitive assessment remains underexplored. This study analyzes the efficacy of the Mini-Mental State Examination (MMSE) as a screening tool for bilinguals, specifically examining the influence of language choice on balanced and unbalanced Lebanese bilinguals (Arabic-French) and its implications for diagnosing cognitive impairment. Ninety-three bilingual healthy controls (mean age = 67.99 ± 9.3) and 29 Alzheimer's disease patients (mean age = 77.2 ± 5.9), including 26 with mild and 3 with moderate dementia, underwent MMSE assessments in both Arabic and French. The study aimed to assess language impact on cognitive screening outcomes in different bilingual subtypes. Sensitivity in screening for cognitive impairment using the MMSE varied based on language and bilingualism subtype. For unbalanced bilinguals, using the prominent language increased sensitivity. Conversely, in balanced bilinguals, employing the societal majority language enhanced sensitivity. This suggests that the conventional use of the non-prominent language in cognitive screening for foreigners/immigrants may result in a subtle loss of MMSE sensitivity. This study emphasizes the critical role of language choice in cognitive assessment for bilinguals. The MMSE's sensitivity is influenced by language selection, with clinical implications for screening procedures. Recommendations include using the prominent language for cognitive screening in dominant bilinguals and the societal majority language for balanced bilinguals. This nuanced approach aims to improve the accuracy and cultural sensitivity of cognitive screening in bilingual populations, addressing the gap in current assessment practices.

Students’ Perceived Language Competence and Attitudes Towards Multilingualism at a South African University

South Africa is well-known for the implementation of multilingual language policies at various educational levels which are upheld by its Constitution. Higher education institutions in the country strive to comply with the call to bolster multilingualism, but the number of research studies that have focused on students’ language proficiency and language attitudes is remarkably low. To analyse these issues, the current study relied on a questionnaire that was filled out by 789 university students from an institution whose language policy promotes the use of three languages, namely Afrikaans, English, and Xhosa. The statistical analyses performed revealed that English proficiency is perceived as high and attitudes towards this language are very favourable; however, this is not the case with Afrikaans and, above all, Xhosa, which was not well known by the majority of students at the university and attitudes towards it were far from positive.

Eliciting the Translation Ability of Large Language Models via Multilingual Finetuning with Translation Instructions

Abstract Large-scale pretrained language models (LLMs), such as ChatGPT and GPT4, have shown strong abilities in multilingual translation, without being explicitly trained on parallel corpora. It is intriguing how the LLMs obtain their ability to carry out translation instructions for different languages. In this paper, we present a detailed analysis by finetuning a multilingual pretrained language model, XGLM-7.5B, to perform multilingual translation following given instructions. Firstly, we show that multilingual LLMs have stronger translation abilities than previously demonstrated. For a certain language, the translation performance depends on its similarity to English and the amount of data used in the pretraining phase. Secondly, we find that LLMs’ ability to carry out translation instructions relies on the understanding of translation instructions and the alignment among different languages. With multilingual finetuning with translation instructions, LLMs could learn to perform the translation task well even for those language pairs unseen during the instruction tuning phase.

Adapting multilingual vision language transformers for low-resource Urdu optical character recognition (OCR).

In the realm of digitizing written content, the challenges posed by low-resource languages are noteworthy. These languages, often lacking in comprehensive linguistic resources, require specialized attention to develop robust systems for accurate optical character recognition (OCR). This article addresses the significance of focusing on such languages and introduces ViLanOCR, an innovative bilingual OCR system tailored for Urdu and English. Unlike existing systems, which struggle with the intricacies of low-resource languages, ViLanOCR leverages advanced multilingual transformer-based language models to achieve superior performances. The proposed approach is evaluated using the character error rate (CER) metric and achieves state-of-the-art results on the Urdu UHWR dataset, with a CER of 1.1%. The experimental results demonstrate the effectiveness of the proposed approach, surpassing state of the-art baselines in Urdu handwriting digitization.

Prompt-based learning framework for zero-shot cross-lingual text classification

Cross-lingual text classification is a challenging task that aims to train classifiers with data in one language, known as the source language, and apply the acquired knowledge to data in another language, referred to as the target language. Recent advancements in multilingual pre-trained language models (PLMs) have made significant progress in addressing cross-lingual issues, and the application of prompt-based learning has further improved task performance. However, these models still face challenges such as the gap between cross-lingual classification tasks and pre-training tasks of PLMs, as well as issues related to scarce resources and data noise, which hinder the full exploitation of the implicit knowledge in PLMs. In this paper, we propose a Prompt-based Cross-lingual Learning (PCL) framework that combines language-agnostic continuous prompt learning with self-learning process. Specifically, PCL framework leverages language-agnostic prompts and PLMs to achieve semantic transfer between source and target languages. To enhance the semantic relationship between prompts and category labels, a label attention module is introduced. Additionally, a set of self-training rules is proposed, which includes a scoring function. In a few-shot setting, noisy data is dynamically filtered through scoring and ranking of the data. During each training iteration, both the model and scoring function weights are updated, further improving the discrimination capability of the model. In summary, the proposed PCL framework builds upon cross-lingual prompt learning, effectively removing noisy data and applying it to zero-shot cross-lingual text classification, which is beneficial for engineering applications. The findings of this study have implications for prompt learning method. The PCL framework achieves state-of-the-art performance in cross-lingual text classification task, with a 14% performance improvement compared to basic soft prompt learning. This demonstrates its potential in addressing classification problems in resource-limited scenarios.

Parental ideologies in multilingual Family Language Policies in the Basque Autonomous Community (Spain)

The study of Family Language Policy (FLP) with a minority language has most often focused on the policies on the minority language within the framework of the hegemonic position of a majority language. This article, however, takes the view that a multilingual approach is needed to better understand parental decisions in their FLPs when a foreign language is also present in the education of their children. The data presented in this article is based on a PhD research project which studies the FLPs of Basque parents living in a mostly Spanish-speaking area of the Basque Autonomous Community (BAC) and whose children attend a Basque-medium school with early introduction of English as the L3. Results show that their ideological positioning in relation to Basque, the different values attached to each of their children’s languages, as well as their ideas about multilingualism determine to a great extent their FLPs. Whilst all parents support Basque and positively value learning English, some differences have been identified: Basque is prioritised above all by the most activist parents, who establish an iron-cast hierarchy among languages; English has been found to have a clear value and function, but its place in this hierarchy varies; and in all cases, Spanish is considered to be guaranteed and not requiring special ad hoc strategies. The study confirms the ideological positioning in relation to the minority language as a key factor in minority language FLPs, but also shows the impact of ideas about multilingual upbringing in their decisions, their expectations, and the degree of satisfaction or frustration with results.

An Analysis of the Mediating Role of Language in Education in the Context of Internationalisation of Education

In the context of the internationalization of education, multilingual language learning and teaching play a fundamental and very important role in the education system, where different groups learn a uniform curriculum based on different cultural backgrounds and linguistic understandings. This thesis analyses the reason for the imbalance of educational resources for minorities in the educational process. Multilingual teaching materials and related materials are outdated or unavailable. Groups learning through "bridge" languages do not acquire languages through their mother tongue, which makes the acquisition process difficult. On this basis, the thesis proposes to improve pedagogical diversity by increasing teachers' motivation to learn and teach multilingualism. The second is that the creation and enrichment of multilingual corpora and teaching materials can enhance research on multilingualism. The third is a way to reduce the quality gap with the majority population in education by promoting cooperation between universities companies and institutions.

Tibetan Sentence Boundaries Automatic Disambiguation Based on Bidirectional Encoder Representations from Transformers on Byte Pair Encoding Word Cutting Method

Sentence Boundary Disambiguation (SBD) is crucial for building datasets for tasks such as machine translation, syntactic analysis, and semantic analysis. Currently, most automatic sentence segmentation in Tibetan adopts the methods of rule-based and statistical learning, as well as the combination of the two, which have high requirements on the corpus and the linguistic foundation of the researchers and are more costly to annotate manually. In this study, we explore Tibetan SBD using deep learning technology. Initially, we analyze Tibetan characteristics and various subword techniques, selecting Byte Pair Encoding (BPE) and Sentencepiece (SP) for text segmentation and training the Bidirectional Encoder Representations from Transformers (BERT) pre-trained language model. Secondly, we studied the Tibetan SBD based on different BERT pre-trained language models, which mainly learns the ambiguity of the shad (“།”) in different positions in modern Tibetan texts and determines through the model whether the shad (“།”) in the texts has the function of segmenting sentences. Meanwhile, this study introduces four models, BERT-CNN, BERT-RNN, BERT-RCNN, and BERT-DPCNN, based on the BERT model for performance comparison. Finally, to verify the performance of the pre-trained language models on the SBD task, this study conducts SBD experiments on both the publicly available Tibetan pre-trained language model TiBERT and the multilingual pre-trained language model (Multi-BERT). The experimental results show that the F1 score of the BERT (BPE) model trained in this study reaches 95.32% on 465,669 Tibetan sentences, nearly five percentage points higher than BERT (SP) and Multi-BERT. The SBD method based on pre-trained language models in this study lays the foundation for establishing datasets for the later tasks of Tibetan pre-training, summary extraction, and machine translation.