Language Resources Research Articles

KannadaLex: A lexical database with psycholinguistic information

Databases containing lexical properties are of primary importance to psycholinguistic research and speech-language therapy. Several lexical databases for different languages have been developed in the recent past, but Kannada, a language spoken by 50.8 million people, has no comprehensive lexical database yet. To address this, KannadaLex , a Kannada lexical database is built as a language resource that contains orthographic, phonological, and syllabic information about words that are sourced from newspaper articles from the last decade. Along with these vital statistics like the phonological neighbourhood, syllable complexity summed syllable and bigram syllable frequencies, and lemma and inflectional family information are stored. The database is validated by correlating frequency, a well-established psycholinguistic feature, with other numerical features. The developed lexical database contains 170K words from varied disciplines, complete with psycholinguistic features. This KannadaLex is a comprehensive resource for psycholinguists, speech therapists, and linguistic researchers for analyzing Kannada and other similar languages. Psycholinguists require lexical data for choosing stimuli to conduct experiments that study the factors that enable humans to acquire, use, comprehend, and produce language. Speech and language therapists query these databases for developing the most efficient stimuli for evaluating, diagnosing, and treating communication disorders, and rehabilitation of speech after brain injuries.

Automatic generation of nominal phrases for Portuguese and Galician

Abstract This paper presents XeraWord, an innovative tool for automatically generating nominal phrases. XeraWord can be used for different tasks, ranging from teaching languages to the creation of examples in lexicography, or even for the development of resources for natural language processing. In this area, Xera was the first experiment, allowing the automatic generation of nominal phrases in three languages: German, French and Spanish. This tool was extended to support other languages, namely, Portuguese and Galician. We start by presenting the theory behind the development of Xera and its new version, XeraWord, namely, the applied base methodology, and the natural language processing resources used to support it. Then, TraduWord, a tool specifically developed to construct resources for new languages, is presented. This tool allows the semi-automatic translation of the data required for the nominal phrase generation. For this, we discuss its advantages and disadvantages, analysing the quality of the translated resources, as well as the amount of manual work required to validate and correct these resources.

A stepped wedge trial of a healthcare provider–focused intervention to increase human papillomavirus (HPV) vaccine initiation among survivors of childhood cancer.

10010 Background: Childhood cancer survivors are at increased risk for human papillomavirus (HPV)-related cancers. HPV vaccination is highly protective against HPV acquisition. However, we have previously shown that initiation rates among survivors are low, primarily due to lack of healthcare provider recommendation for the vaccine. Methods: We conducted a stepped wedge trial from 2021 to 2023 to evaluate the effectiveness of an evidence-based healthcare provider-focused intervention (HPV PROTECT; NCT04469569) in increasing HPV vaccine initiation rates 1y following implementation. The intervention includes provider communication training to enhance vaccine recommendation skills, audit/feedback regarding clinic vaccination rates, and patient-directed resources in multiple languages tailored to pediatric oncology settings. We measured the effectiveness of the intervention in a racially, ethnically, and geographically diverse sample of HPV vaccine naïve childhood cancer survivors, aged 9-17y, and ≥1y post-completion of therapy returning to pediatric oncology clinics for follow-up care at 6 sites. The primary outcome of interest was HPV vaccine initiation rates (abstracted from state vaccine registries) at end of each study year. Baseline data were collected for all sites in Y1, three sites were randomly selected to receive the intervention in Y2, and the remaining three in Y3. The intervention effect was tested using a longitudinal logistic regression model for initiation with intervention as the main fixed effect, adjusting for survivor age, cancer diagnosis, time off-therapy, sex, race, ethnicity, and receipt of hematopoietic cell transplantation. The secular trend (estimated using pre-intervention data from Y1 and Y2) was included as an offset, and site was included as a random effect. The intervention effect was reported as odds ratio (OR) for initiation with 95% confidence intervals (CI). Results: A total of 1779 unique vaccine naïve survivors (47.1 % leukemia; 55.1% male; 51.5% non-Hispanic white) completed 2689 clinic visits across 6 sites. Median (range) age at diagnosis was 5.1y (0-16.5), at study entry was 12.3y (9-17.9), and median time off-therapy was 5.5y (1.0-17.3). Overall incident HPV vaccine initiation was 16.0% at baseline. The adjusted odds of vaccine initiation were 1.3-fold (95%CI, 1.03-1.6; p = 0.03) higher post-intervention vs. pre-intervention, accounting for secular trend OR of 1.1. Overall prevalence of vaccine initiation increased from 51.9% pre-intervention to 61.3% post-intervention. Conclusions: The improvement in childhood cancer survivor HPV vaccine initiation rates in a diverse sample following implementation of a healthcare provider-focused intervention underscores the potential for pediatric oncology providers to positively impact HPV vaccine uptake in this vulnerable population. Clinical trial information: NCT04469569 .

Optimizing patient (pt) care through pt-focused resources to prevent and manage hand-foot skin reaction (HFSR).

e24144 Background: Research has shown that pts and caregivers (non-HCPs) seek medical and disease-related information more than once a month, and this has accelerated due to the COVID-19 pandemic. However, they find it difficult to understand the information they receive and thus, can be misinformed. By understanding the use of fair-balanced medical information (MI) resources by non-HCPs, pharmaceutical companies can develop scientifically accurate yet pt-friendly resources to meet their needs (Goettner, 2022; Rai, 2022). Upon reviewing the unsolicited oncology inquiries received by our MI department, approximately 25% of inquiries were from non-HCPs seeking information. Over the past 3 years, non-HCPs have submitted almost 10,000 inquiries regarding our oncology products, in which 191 inquiries were specifically regarding HFSR and regorafenib and sorafenib. Historically, our MI department responded to non-HCP inquiries by sharing the product label information. However, we identified an unmet need for trustworthy, comprehensive, and accurate pt resources in plain language. Methods: A full literature review was performed, and the relevant data were summarized in plain language for pts. Both HCPs and pts participated in developing the global pt resource on the prevention and management of HFSR for regorafenib and sorafenib. The seven-page interactive brochure was written in 4th to 6th grade reading level which included images and graphics to enhance the understanding of data, easy navigation to the content of interest, and glossary to define key terms. Furthermore, these materials were translated for pts who participated in the regorafenib and sorafenib Patient Support Program in Brazil to further educate and support pts who have started therapy. Results: As of June 2023, the global pt medical resource has been deployed 28 times in Brazil, delivering key information to non-HCPs on their disease and treatment while emphasizing its practical utility and addressing health literacy challenges. We collected feedback from pts who utilized the translated material, and they described it to be “informative” and “helpful” since it empowered them to effectively navigate and address HFSR-associated discomforts during their treatment journey. The feedback has also been utilized to further enhance the resource’s feasibility. Conclusions: The pt feedback on the brochures showcases the value of pt-focused approach in oncology and the positive impact of collective efforts across all stakeholders including pts, pharmaceutical MI departments and pt programs. Furthermore, it demonstrates how MI can bridge the gap between pt insights and clinical knowledge by addressing their needs and providing practical and trustworthy tools. Not only does this initiative enhance pt understanding but also empowers pts to take a more active role in their treatment and fosters shared-decision making.

Use of Technology in English Language Learning: Challenges and Benefits

The integration of technology in English language learning has gained significant attention due to its potential to enhance learning experiences and outcomes. However, its implementation also poses various challenges that need to be addressed. This study aims to explore the major challenges faced by teachers and students in integrating technology into English language learning classrooms, as well as the potential benefits it offers. A mixed-methods approach was employed, combining quantitative data from pre- and post-tests and qualitative data from classroom observations, interviews, and questionnaires. The findings reveal significant challenges, including limited access to technology, lack of digital literacy, and pedagogical considerations. Conversely, the benefits encompass increased motivation, exposure to authentic language resources, personalized learning, and multimodal experiences. By understanding these challenges and leveraging the advantages, educators and stakeholders can make informed decisions and implement effective strategies to optimize technology integration in language classrooms, ultimately enhancing learning experiences and outcomes.

CONTENT AND LANGUAGE INTEGRATED LEARNING (CLIL): RESEARCH INTO ITS EFFICACY AND APPLICATION IN EDUCATION ACROSS EUROPE AND BEYOND

Content and Language Integrated Learning (CLIL) is an educational approach that simultaneously teaches a non-language subject and a foreign language, enhancing both content knowledge and language skills. Originating in Europe, CLIL focuses on the 4Cs: content, communication, cognition, and culture, ensuring balanced subject matter and language proficiency. CLIL is distinct from bilingual or immersion education by its integrated approach. The Council of Europe supports CLIL to promote multilingualism and improve curricula quality. This study aims to analyze the foreign experience with CLIL, explore its didactic potential, and evaluate its implementation prospects in Ukraine. CLIL is characterized by integrating subject content with language learning, fostering language development through meaningful contexts, and enhancing cognitive skills like critical thinking and problem-solving. It also promotes cultural awareness and can be adapted to various educational contexts and proficiency levels. It has been defined that effective CLIL implementation requires trained teachers and appropriate materials. The methodology has spread across Europe, with various models tailored to different educational contexts. The Adjunct Model integrates language learning with subject teaching, the Embedded Model fully integrates language and content, and the Dual-Focus Model balances content and language objectives. Successful examples include bilingual schools in Hungary and long-standing practices in Bulgaria. The advantages of CLIL’s implementation have been defined. They include increased motivation, contextual language learning, preparation for a globalized world, and enhanced language proficiency. It also promotes content knowledge alongside language skills, offers international opportunities, and bridges language and content classes. However, challenges include the need for trained teachers, balancing content and language instruction, resource limitations, and large class sizes. Overcoming these challenges involves professional development, collaboration, material development, gradual integration, and using technology. The conclusion has been formulated that CLIL enhances language skills and subject knowledge, transforming educational approaches and improving learning outcomes.

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.

Who do we mobilise? Applied transformative mobilities research in a real-world laboratory

ABSTRACT In this paper we reflect on insights concerning participation in and effects of a real-world laboratory designed to disrupt car dependency in everyday practices in an urban setting. After outlining the project and key findings, we critically reflect on design and achievements of this real-world laboratory more generally. In particular, we discuss the following questions: Who is it that we can address through transformative mobilities research in real-world laboratories? Who are the participants and what are their motives for taking part in the research? To contextualize the research findings within a real-world setting and research paradigm we extend the scope to a second set of questions: How can we conceptualise the relationship between participants and researchers and how do we account for opposing rationalities of interruption (research) and maintenance (participants) of the organisation of everyday life? How does this research enable transformative mobilities? And, finally, what can we say about the scope of our findings and reflections? In the thicket of doing transformative research encouraging and accompanying volunteers to become active in transformative mobility research becomes questions of language, educational background and time resources from the involved, but also being aware of institutionalized change actor networks, unchallenged hierarchies of superior “academic” research and being part of political struggles that require to look closely within and outside of the actual real-world-experiment especially in times of multiple crises. To design and research with those who want to contribute to change is legitimate. However, it is necessary to keep this selectivity in mind.

The Nobel Prize in Literature: An Analysis of Success Stories and Development of Possible Recommendations

ABSTRACT The relevance of the research is determined by the interest of a wide readership in the criteria for selecting nominees and the choice of laureates of the Nobel Prize in Literature in the world, as well as the main factors that help to win. The purpose of this article is to study the creativity of writers and poets who received the award over the past three years from the viewpoint of national identity, language and its linguistic status, translation aspect, reception of creativity and influence on the world community, and readiness to solve global issues of humanity through their manifestation in texts. The methodological basis of the article is a theoretical and comparative approach to the linguistic analysis of the literary heritage of one author or another. This article points out the main issues that exist in the international community in determining the nominees and laureates of the Nobel Prize; it characterizes how national identity, the use of national language resources, and the presence or absence of translations of literary works influence the choice of the winner; it also considers how political and global processes can affect the selection of candidates, as well as how the main recommendations were formulated.

Multimodal Discourse Analysis of Classroom Oral Presentations at Tertiary Level

The study was an investigation of tertiary classroom student presenters’ use of language, gesture, positioning and movement in the lesson. Teaching and learning in the classroom is a multi-semiotic experience and the current study provides the insights into their distinct pedagogies. Raised comprehension of semiotization and resemiotization has multiplied the responsibilities of both teachers and students. 12 teachers and 320 student presenters’ use of semiotic resources at tertiary level had been investigated quantitatively and qualitatively through thematic analysis. The semiotic resources of language, gesture and the use of space through the positioning and movement of teachers and students have been discussed in relation to the pedagogy they realise, which require insinuations in teaching and learning both.

Breaking Down Walls: Challenges in Teaching English to School Level Students

This paper addresses the challenges associated with English language instruction in rural schools of India. The language policy in school education poses both societal and individual hurdles. The prevailing quality of English language education in many Indian schools is concerning, with issues such as teacher proficiency, access to language resources, and instructional materials being primary concerns. Rural students face particularly arduous circumstances, lacking the resources and opportunities available to their urban counterparts, such as language labs and audio-visual aids. English is often perceived as a subject rather than a language by rural students, hindering their engagement and proficiency. Many students approach English studies solely for examination purposes, focusing on rote memorization rather than genuine language acquisition. This fear of English is compounded by the limited vision of some teachers, who prioritize exam results over long-term student development. Key Words: Rural, proficiency, circumstances, acquisition, resources memorization

Depression Intensity Identification using Transformer Ensemble Technique for the Resource-constrained Bengali Language

Depression is an ordinary mental health-related disorder that hampers people’s daily activities, and sometimes, it destroys an individual’s life. It is one of the major social issues at present. Since depressed people use various social networking sites for sharing their thoughts and feelings, many scholars have tried to identify depression texts in highly resourced languages like English; however, only a small quantity of papers are detected in the resource-constrained Bengali language. This paper focuses on developing a depression intensity detection system from Bengali text data. In this regard, this study experiments on a 2,596 sample-sized dataset with four levels of depression by utilizing five state-of-the-art transformer models, including multilingual Bidirectional Encoder Representations from Transformers, DistilmBERT, XLM-RoBERTa, Bangla-BERT-Base, and BanglaBERT, and suggests a new ensemble method called MaxOfAvgProb. This method goes beyond the performance of the previous work on the same dataset, scoring 63.47% F1-score and 62.90% accuracy. To increase the reliability of the proposed method, we utilize this approach on another available dataset with 4,897 entries. In this case, our recommended method also surpasses the performance of the existing work on the same dataset, with accuracy at 86.45% and F1-score at 86.35%. Identifying the intensity of depression, depressed people may get proper counseling or treatment from their respected guardians or psychologists according to the victims’ level of depression.

A Survey on Conversational AI Question answering System for Low Resource Language

Question-and-answer (QA) systems allow users to pose questions about the information accessible in a variety of formats, such as structured and unstructured information in natural languages. It contributes significantly to conversational artificial intelligence (AI), which has led to the creation of a novel research field on conversational question answering (CQA), in which a system is required to understand the provided context before engaging in multi-turn QA to satisfy a user's informational needs. While the majority of currently done research focuses on single-turn QA, pre-trained language models and the availability of large multi-turn QA datasets have recently made multi-turn QA more significant. This study aims to give a thorough analysis of the most recent CQA research trends, mostly based on publications that have been reviewed in recent years. Our data indicates a shift in the industry's preference for multi-turn QA over single-turn QA, which has numerous advantages for conversational AI. In order to create a solid basis for the field of CQA, this survey aims to serve as the pinnacle for the research community.

‘I like exploring other languages’: primary and lower secondary students’ attitudes towards plurilingual education

ABSTRACT While teachers’ beliefs about plurilingual education are widely studied, there is a gap in research exploring learners’ orientations. Drawing on a conceptualisation of plurilingual education distinguishing between three pluralistic approaches to languages and a transversal dimension focusing on learners’ language resources, the article investigates primary and lower secondary students’ attitudes towards plurilingual education in response to plurilingual education being implemented in the students’ language teaching. Based on interview data collected in a multiple-case study from majority and minority language students in Grades 1, 5 and 7, the analysis displays consistent learner positivity towards plurilingual education, especially emphasising the éveil aux langues approach whereas the integrated didactic approach as well as intercomprehension between related languages receive less attention. The findings indicate that the attitudes towards plurilingual education are linked to the learners’ language resources creating a framework for the students’ encounters and comparisons with other languages. Combining the findings and research literature on plurilingualism as a universal criterion for all learners in a modern, globalised world, the article suggests a continuum of the learner's plurilingualism. However, the findings reveal that experienced plurilingual education contexts do not only foster positive attitudes towards linguistic diversity, but that discriminating language-hierarchising attitudes co-exist.

Neural machine translation for low resource Indian language: Hindi-Kangri

Neural Machine Translation (NMT) for low resource languages is a challenging task due to unavailability of large parallel corpus. The efficacy of Transformer based NMT models largely depends on scale of the parallel corpus and the configuration of hyperparameters implemented during model training. This study aims to delve into and elucidate the impact of hyperparameters on the performance of NMT models for low resource languages. To accomplish this, a series of experiments are conducted using an open-source Hindi-Kangri corpus to train both supervised and semi-supervised NMT models. Throughout the experimentation process, a significant number of discrepancies were identified within the data-set, necessitating manual correction. The best translation performance evaluated with respect to the metrics such as BLEU (0–1), SacreBLEU (0–100), Chrf (0–100), Chrf+ (0–100), Chrf++ (0–100) and TER (%) is (0.15, 14.98, 41.43, 41.49, 38.77, 68.20) for Hindi to Kangri direction, and (0.283, 28.17, 49.71, 50.64, 48.63, 51.25) for Kangri to Hindi direction.

Computational model of engagement with stigmatised sentiment: COVID and general vaccine discourse on social media

The growth rate of new social media users continues to surpass new Internet users and new unique mobile phone subscribers and this trend remains consistent over the past 5 years (2019–2023). The most frequently visited types of websites or apps worldwide are chat and messaging, closely followed by social networks and this trend has also remained relatively constant. The dominating role of social media, especially as a source for information seeking, is staggering, particularly during the COVID-19 pandemic. However, the research in Keller et al. (J Mec Internet Res 16:e8, 2014) indicates that not many experts consider social media as a tool for sharing their expertise or for integrating social media into their research efforts. This is a troubling fact, especially considering that stigmatised health narrative are fueled in the face of uncertainty and spread very quickly among the lay population. The latter contributes to the spread of misinformation and, consequently, fosters hesitancy about preventive measures such as vaccines. This research presents new evidence on engagement with stigmatised vaccine discourse on Facebook (Meta), Twitter (X), YouTube and Reddit. Engagement with health-related sentiment can be an important indicator of perceptions regarding preventive measures. The current research can draw the attention of public health experts to the connection between stigmatised discourse and engagement in health discussions, as well as the potential impact of other linguistic features on engagement. It can also guide health authorities and medical professionals in developing effective communication strategies for the general public. Moreover, there are only a handful of studies discussing engagement with socially shared health-care discussions. The research focuses on examining engagement with stigmatised sentiment in vaccination discussions during and prior to the COVID-19 pandemic, using a cross-sectional approach. The study is based on primary data from social media domains, supplemented by secondary data analyses of literature related to the topic. To achieve the research goal, the study employs a multi-method design primarily based on quantitative methods of content analyses, such as Linguistic Inquiry and Word Count (LIWC) (Pennebaker et al. in Linguistic inquiry and word count: Liwc 2001, vol 71. Lawrence Erlbaum Associates, Mahway, 2001) to extract general language features and analyse stigmatised sentiment as the result of previous research findings in Straton et al. (Stigma annotation scheme and stigmatized language detection in health-care discussions on social media. In: Proceedings of The 12th Language Resources and Evaluation Conference (LREC, 2020), pp 1178–1190 (European Language Resources Association, 2020), Straton (Appl Intell, pp 1–26, 2022). Unsupervised K-means clustering methods, along with F-score and Z-score measures, are applied to draw insights from the features. The goal is to explore the phenomena of engagement with socially shared health information, investigate whether stigma can affect the engagement, and identify any other language features that may have an impact. Highly engaging general vaccine discussions before the pandemic appear to be more planned and less emotional. They exhibit reasoning and differentiation typical of more complex discussion sections, incorporating references to authority and family concerns simultaneously. The engaging messages convey stigmatised sentiment, likely shared either with the intent to deceive, or are based on a genuinely biased belief. Some elements of stigmatised discussions indicate deception, while others are more frequent in truthful statements. Engaging content in COVID vaccine discussions, similar to general vaccine content, lacks emotional elements and exhibits high linguistic complexity. However, there seems to be no connection between engagement and stigmatised sentiment. This difference is likely due to the removal of public anti-vaccination pages during the pandemic where anti-vaccination groups moved to discussion section of posts that try to disprove vaccine conspiracy theories. Mixing polarised groups will result in different feedback and engagement with the content. Almost half of the features in COVID and general vaccine discussions have a similar impact on engagement. However, further exploration of the findings suggests that there are distinct differences. Understanding the differences is very important to prevent generalisation errors in the conclusions drawn from the data. Engagement with written text on social media should be measured within a narrow scope: limited regional, demographic and temporal scope. Otherwise, interpretation of the findings risks on being inconsistent.

ОСНОВНЫЕ ПРОБЛЕМЫ ЛИНГВОЭКОЛОГИИ: ТЕОРЕТИЧЕСКИЙ И ПРИКЛАДНОЙ АСПЕКТЫ

The author identifies the main problem field of linguoecology, gives a brief overview of linguoecological ideas and problems arising in linguistic society as a result of violation of the necessary relationship between native and acquired language resources, presents the results of a study of oral spontaneous discourse to identify existing problems of language ecology in the speech of native speakers of the Russian language.
 During the study, the author analyzed 36 recordings of oral spontaneous discourse with a total duration of 7,2 hours, representing dialogues and polylogues received from informal informants- native speakers of the Russian language – students, cafe visitors, public transport passengers, participants of TV discussions, represented in approximately equal percentages.
 The main methods of work are the method of auditory analysis, descriptive method (observation, analysis, generalization, classification), statistical method.

Exploring Undergraduate Latine Students’ Learning Experiences in STEM Courses

ABSTRACT We used a phenomenological research design to explore 19 Latina and Queer identifying undergraduate students’ lived experiences in STEM undergraduate courses at a Hispanic-Serving Institution (HSI). Eighteen participants self-identified as female and one identified as genderqueer with an average undergraduate grade point average of 3.07. The following themes emerged from phenomenological data analysis: failure to acknowledge students’ cultural and language resources; deficit assumptions about students’ background, abilities, and potential; absence of active and collaborative learning and practical and real-world examples; minimal feedback on student learning and growth; disregard for student voices in design of assessments; and misalignment between assessments and evaluation tools to measure those assessments. We provide implications for faculty developers at HSIs and other institutions of higher education.

BiLSTMs and BPE for English to Telugu CLIR

A crucial component of Cross Lingual Information Retrieval (CLIR) is Neural Machine Translation (NMT). NMT performs a good job of transforming queries in the English language into Indian languages. This study focuses on the translation of English queries into Telugu. For translations, the NMT will make use of a parallel corpus. Due to a lack of resources in the Telugu language, it is exceedingly challenging to provide NMT with sizable parallel corpora. Thus, the NMT will encounter an issue known as Out of Vocabulary (OOV). Long Short-Term Memory (LSTM) with Byte Pair Encoding (BPE), which breaks up rare words into subwords and attempts to translate them to solve the OOV issue. Issues such as Named Entity Recognition (NER) continue to plague it. In sequence-to-sequence models, bidirectional LSTMs can solve certain NER challenges. Systems that need to be trained in both directions to recognize named entities can benefit from the use of Bidirectional LSTMs (BiLSTMs). The translation efficiency of NMT with BiLSTMs is significantly higher than normal LSTMs, as indicated by the accuracy metrics and Bilingual Evaluation Understudy (BLEU) score.

Utilizing BiLSTM For Fine-Grained Aspect-Based Travel Recommendations Using Travel Reviews In Low Resourced Language

Recommender systems have become an essential tool for enhancing user experiences by providing personalized recommendations. In this study, we present a novel approach to constructing a recommender system specifically tailored for Malayalam travel reviews. Our objective was to extract relevant features from these reviews and employ a bidirectional Long Short-Term Memory (BiLSTM) architecture to construct a robust and accurate recommendation model. We focused on four key features extracted from the travel reviews: travel mode, travel type, location climate, and location type. The travel mode feature encompassed the mode of transport opted for the travel such as bus, car, train, etc., while the travel type captured the nature of the trip, including family, friends, or solo travel. Additionally, we considered the climate of the location, including rainy, snowy, hot, and dry, among others, and the location type, such as beach, hilly, or forest destinations. To construct our recommender system, we implemented a BiLSTM architecture, a powerful deep-learning model known for effectively capturing temporal dependencies in sequential data. This architecture allowed us to process the extracted features and learn the underlying patterns within the Malayalam travel reviews. Our experiments were conducted on a comprehensive dataset of Malayalam travel reviews, carefully curated for this study. The dataset encompassed a diverse range of travel experiences, enabling our model to learn from a wide variety of user preferences and recommendations. The performance evaluation of our recommender system yielded promising results. With an accuracy of 83.65 percent, our model showcased its ability to accurately predict and recommend travel options based on the extracted features from the reviews. The high accuracy achieved by our model underscores the effectiveness of the BiLSTM architecture in capturing the nuances of the Malayalam language and understanding the subtle preferences expressed in travel reviews. The practical implications of our work are significant, as it offers a valuable tool for travelers seeking personalized recommendations based on their travel preferences. The use of the Malayalam language in this context expands the reach of recommender systems to a wider audience, catering specifically to individuals who prefer to consume content and make decisions in their native language.