Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

12 results for “Low Resource Language”
Set a search alert
Research ArticleOpen accessEvery word in the titleEvaluating Machine Translation for Domain Specific Low-Resource Nepali-English Language Pairs: The Impact of Tokenization on Statistical and Neural TechniquesAmit Kumar Roy, Bipul Syam PurkayasthaIn the modern era, the field of Machine Translation (MT) has seen a significant shift towards Neural Machine Translation (NMT) techniques, which have surpassed traditional Statistical Machine Translation (SMT) models in terms of the quality of translation. Despite this, the efficacy of these techniques may differ based on the language combination in consideration. While SMT is somewhat more flexible in … …Journal of Computer Science, Vol. 21, Issue 12 · 24 Jan 2026 · 1,920 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFew-shot Fine-tuning of BERT Multilingual for Hindi Word Sense DisambiguationShailendra Kumar Patel, Rakesh Kumar, Anuj Kumar SirohiWord Sense Disambiguation (WSD) is a fundamental task in Natural Language Processing (NLP), addressing the challenge of identifying correct word meanings in context. This task is particularly complex for morphologically rich and resource-limited languages like Hindi, which exhibit significant lexical ambiguity compounded by limited availability of annotated corpora. To address these challenges, we propose a supervised approach combining the multilingual … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,250 accessesView PDFCite
Research ArticleOpen accessIn the keywordsImplementation of Single Candidate Loss Optimization Algorithm for Loss Optimization of Bhojpuri-English Machine Translation ModelRituraj Dixit, Sarabjeet Singh Bedi, Ibrahim Aljubayri, Mohammad Zubair KhanMachine translation of low-resource Indian languages is necessary as most of the regions still know and speak their specific dialects and are still not comfortable understanding the English language. Indian languages are morphologically rich, due to which there are two big challenges, Ambiguity and Domain adaption, which are faced by researchers during the translation. Lack of data also increases the … …Journal of Computer Science, Vol. 21, Issue 5 · 17 Apr 2025 · 5,151 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEthioLSocMDMTLM: Exploring Application of Topic Modeling for Building Ethiopian Language Social Media Data-Based Multilingual Transformer Language Models for Multilingual Hateful Content DetectionNaol Bakala Defersha, Kula Kekeba Tune, Solomon Teferra AbateThis study proposes topic modeling techniques to develop Ethiopian Language Social Media Data Based Multilingual Transformer Language Models for multilingual hateful content detection. We modified various multilingual pretrained models, investigated the challenges of using pre-trained transformer language models, and built multilingual hateful content detection models. Topic words with rows of 1561, 70, and 1044 extracted from Afaan Oromo, Tigrigna, and … …Journal of Computer Science, Vol. 21, Issue 2 · 31 Dec 2024 · 5,204 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Language Models (LLMs) in the Interpretation of Tuberculosis Concepts: Design of a Virtual Assistant for Clinical Support and Patient EducationMauricio Acevedo-Carrillo, Shirley Fiorella Simbron EspejoTuberculosis (TB) remains a global public health challenge, where access to accurate and up-to-date information is crucial for professionals and patients. This research comparatively evaluated the performance of five language models (LLMs) Med-PaLM 2, GPT-4, MEDITRON-70B, Me-LLaMA, and Clinical Camel in the TB domain and implemented a mobile virtual assistant as a proof-of-concept based on the best-performing model. Clinical accuracy … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 491 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Sentiment Analysis for Malayalam With mBERT: A Profoundly Transparent and Accurate Approach Using LIMEAnitha R., K. S. Anil Kumar, Rajeev R. R. et al.The overlapping sentiment boundaries, intensifiers, and intricate morphological structures in Malayalam present particular difficulties for sentiment analysis, making it hard for traditional machine learning techniques to produce consistent results. We present an explainable sentiment analysis framework in this paper that refines a Multilingual Bidirectional Encoder Representations from Transformers (mBERT) model on a novel constituency-level dataset that has been manually curated … …Journal of Computer Science, Vol. 22, Issue 5 · 2 Jun 2026 · 1,061 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Indian Language Speech Recognition Systems with Language-Independent Phonetic Script: An Experimental ExplorationJose Stephan, Muthayyan Kamalam JayakumarIndia has a distinct linguistic profile that makes it extremely challenging to train Automatic Speech Recognition (ASR) systems correctly because most Indian languages have limited training material and are generally low-resource in nature. However, due to their similarity in phonemes, these languages offer an opportunity to create a single speech recognition technology. This study proposes an optimized phonetic script which … …Journal of Computer Science, Vol. 21, Issue 5 · 9 May 2025 · 6,536 accessesView PDFCite
Research ArticleOpen accessIn the abstractTree Rotations for Dependency Trees: Converting the Head-Directionality of Noun PhrasesIka Alfina, Indra Budi, Heru SuhartantoTo overcome the lack of NLP resources for the low-resource languages, we can utilize tools that are already available for other highresource languages and then modify the output to conform to the target language. In this study, we proposed an approach to convert an Indonesian constituency treebank to a dependency treebank by utilizing an English NLP tool (Stanford CoreNLP) to … …Journal of Computer Science, Vol. 16, Issue 11 · 17 Nov 2020 · 7,796 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Machine Translation for Low-resource English-BanglaMohammad Abdullah Al Mumin, Md Hanif Seddiqui, Muhammed Zafar Iqbal, Mohammed Jahirul IslamNeural machine translation has recently been able to gain state-of-the-art translation quality for many language pairs. However, neural machine translation has been less tested for English-Bangla language pair, two linguistically distant and widely spoken languages. In this paper, we apply neural machine translation to the task of English-Bangla translation in both directions and compare it against a standard phrase-based statistical … …Journal of Computer Science, Vol. 15, Issue 11 · 15 Nov 2019 · 9,865 accessesView PDFCite