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Journal articles on the topic 'Real-time translation'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

AV, Dr Vijaya Kumar, onika BK, Arun Kumar, Nisha HV, and Susheel Kumar PM. "Real Time Language Translation Collaboration Platform." International Journal of Research Publication and Reviews 5, no. 1 (2024): 2084–88. http://dx.doi.org/10.55248/gengpi.5.0124.0250.

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S, Ms Vijayalakshmi. "AI-Powered Multilingual Chatbot for Real-Time Translation." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46600.

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Abstract - Language barriers prevent effective communication and limit access to valuable information for non-English speakers. Many individuals face challenges in translating regional languages accurately, leading to misunderstandings and restricted opportunities in education, business, and daily interactions. This project aims to develop an AI-powered translation chatbot capable of translating Tamil, Malayalam, Kannada, Hindi, and Telugu into English with high accuracy. By leveraging Natural Language Processing (NLP) and machine learning techniques, the chatbot will provide real-time and con

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S, Ms Vijayalakshmi. "AI-Powered Multilingual Chatbot for Real-Time Translation." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46604.

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Abstract - Language barriers prevent effective communication and limit access to valuable information for non-English speakers. Many individuals face challenges in translating regional languages accurately, leading to misunderstandings and restricted opportunities in education, business, and daily interactions. This project aims to develop an AI-powered translation chatbot capable of translating Tamil, Malayalam, Kannada, Hindi, and Telugu into English with high accuracy. By leveraging Natural Language Processing (NLP) and machine learning techniques, the chatbot will provide real-time and con

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Heinrichs, Arianne. "Translation in real time." Nature Reviews Molecular Cell Biology 9, no. 4 (2008): 266. http://dx.doi.org/10.1038/nrm2382.

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Minas, Dimosthenis, Eleanna Theodosiou, Konstantinos Roumpas, and Michalis Xenos. "Adaptive Real-Time Translation Assistance Through Eye-Tracking." AI 6, no. 1 (2025): 5. https://doi.org/10.3390/ai6010005.

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This study introduces the Eye-tracking Translation Software (ETS), a system that leverages eye-tracking data and real-time translation to enhance reading flow for non-native language users in complex, technical texts. By measuring the fixation duration, we can detect moments of cognitive load, ETS selectively provides translations, maintaining reading flow and engagement without undermining language learning. The key technological components include a desktop eye-tracker integrated with a custom Python-based application. Through a user-centered design, ETS dynamically adapts to individual read

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Gaonkar, Niyati V., and Vishal R. Gori. "Real-Time Bidirectional Translation System Between Text and Indian Sign Language Using Deep Learning and NLP Techniques." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44150.

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In this paper, we present a real-time translation system that bridges the communication gap between the hearing and non-hearing communities. Our system converts English text to Indian Sign Language (ISL) and vice versa, using Natural Language Processing (NLP) techniques and deep learning-based gesture recognition. The system supports video-based gesture recognition for ISL and provides accurate text translations in real-time. This study addresses the technical challenges involved, including feature extraction from gestures and translating com- plex ISL sentences using neural networks like LSTM

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Hasler, Béatrice S., Oren Salomon, Peleg Tuchman, Amir Lev-Tov, and Doron Friedman. "Real-time gesture translation in intercultural communication." AI & SOCIETY 32, no. 1 (2014): 25–35. http://dx.doi.org/10.1007/s00146-014-0573-4.

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Qureshi, Nusrat, and Olivier Duss. "Real-time tracking of transcription-translation coupling." Biophysical Journal 122, no. 3 (2023): 488a. http://dx.doi.org/10.1016/j.bpj.2022.11.2608.

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Yan, Li. "Real-Time Automatic Translation Algorithm for Chinese Subtitles in Media Playback Using Knowledge Base." Mobile Information Systems 2022 (June 18, 2022): 1–11. http://dx.doi.org/10.1155/2022/5245035.

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Currently, speech technology allows for simultaneous subtitling of live television programs using speech recognition and the respeaking approach. Although many previous studies on the quality of live subtitling utilizing voice recognition have been proposed, little attention has been paid to the quantitative elements of subtitles. Due to the high performance of neural machine translation (NMT), it has become the standard machine translation method. A data-driven translation approach requires high-quality, large-scale training data and powerful computing resources to achieve good performance. H

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Bhargavi, Mrs Jangam, Chitikala Sairam, and Donga Hemanth. "Real time interface for deaf-hearing communication." International Scientific Journal of Engineering and Management 04, no. 03 (2025): 1–7. https://doi.org/10.55041/isjem02356.

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Bridging the communication gap between the deaf and hearing communities using AI is achieved by integrating two key modules: Speech-to-Sign Language Translation and Sign Gesture Detection in Real Time. The first module translates English spoken language into American Sign Language (ASL) animations. It consists of three sub-modules: speech-to-text conversion using the speech recognition module in Python, English text to ASL gloss translation using an NLP model, and ASL gloss to animated video generation, where DWpose Pose Estimation, and an avatar is used for visual representation. The second m

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Reddy, P. Jagadishwar. "Language Translator Web Application." International Journal for Research in Applied Science and Engineering Technology 12, no. 11 (2024): 1151–56. http://dx.doi.org/10.22214/ijraset.2024.65293.

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This project explores a language translation solution using AWS Translate, a robust, neural machine translation service provided by Amazon Web Services (AWS). Traditional translation methods often fall short in contextual accuracy, but cloud-based, deep learning powered services like AWS Translate address these limitations by generating translations that are both fluent and contextually appropriate. In this project, we integrate AWS Translate with a user friendly web application, built using Streamlit, allowing users to perform real-time translations across multiple languages. We evaluate tran

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Gote, Subodini. "Real Time Sign Language Interpreter." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 2565–68. https://doi.org/10.22214/ijraset.2025.66723.

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Communication can be a significant challenge for individuals who are deaf or hard of hearing. Sign language serves as a vital tool for these individuals, utilizing hand gestures, facial expressions, and body movements to convey messages and emotions. In recent years, the development of sign language recognition systems and gesture-based controls has played a pivotal role in bridging the communication gap between deaf and non-deaf people. This paper focuses on the advancements in real-time sign language translation systems, which enable immediate conversion of sign language into other forms of

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Kim, Myongchan, Sungkil Lee, and Seungmoon Choi. "Saliency-Driven Real-Time Video-to-Tactile Translation." IEEE Transactions on Haptics 7, no. 3 (2014): 394–404. http://dx.doi.org/10.1109/toh.2013.58.

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Smailagic, A., D. Siewiorek, and D. Reilly. "CMU wearable computers for real-time speech translation." IEEE Personal Communications 8, no. 2 (2001): 6–12. http://dx.doi.org/10.1109/98.918088.

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B Meenakshi, Mohammed Wajahat Hussain, and Mittapalli Arvind Sai. "Real-Time Multilingual Speech Translation for Peer Communication." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 06 (2025): 2893–98. https://doi.org/10.47392/irjaeh.2025.0427.

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Language continues to be a major obstacle to effective communication in a world that is becoming more interconnected by the day. This paper presented a real-time audio translation system that facilitates multilingual communication during peer-to-peer video calls. The application enables natural communication in the user’s preferred language by utilizing WebRTC for low-latency media transmission and incorporating sophisticated AI models such as Whisper for speech-to-text, GPT for language translation, and gTTS for text-to-speech synthesis. In addition to allowing real-time subtitle overlays and

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Aitha, Sreevarsha, Meghana Mummali, Meera Alphy Dr., and K. Shirisha Mr. "Language Translator Application using Google Translate API." Recent Innovations in Wireless Network Security 6, no. 3 (2024): 41–45. https://doi.org/10.5281/zenodo.13363877.

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<em>The Language Translator Application is a cutting-edge tool designed to facilitate seamless communication across different languages. By leveraging the powerful capabilities of the Google Translation API, this application offers robust translation services that cater to a wide array of languages and use cases. Built using Python, the application combines simplicity and efficiency, providing users with a reliable solution for their translation needs. This project presents the development of a language translator application using the Google Translation API, implemented in Python. The primary

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Bai, Liping. "Translator’s Ideology, Dominant Ideology and the Use of Pseudonym." Archiv orientální 82, no. 3 (2014): 539–54. http://dx.doi.org/10.47979/aror.j.82.3.539-554.

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This article seeks to decipher the intricate relationship between translation, the translator’s ideology, the dominant ideology, and the use of pseudonym. It does so through analyzing Liang Shiqiu’s Chinese version of George Orwell’s political satire Animal Farm, written under the pen name of Li Qichun. We will investigate the similarities and differences between Liang’s translations under the pseudonym and the ones written under his real name. In addition, we will explore the conflicts that existed between the translator’s ideology and the dominant ideology of the time when the translation wa

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Kothari, Nitin, Chandra Prakash Jain, Dipesh Soni, Avinash Kumar, Anshumaan Dadheech, and Himanshu Sharma. "INSTANT LANGUAGE TRANSLATION APP." International Journal of Technical Research & Science 9, Spl (2024): 27–35. http://dx.doi.org/10.30780/specialissue-iset-2024/018.

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The Real-Time Language Translation App is a solution aimed at addressing to the frequently found problem of language barriers in global communication. This app, which bridges linguistic gaps in communication between individuals and organizations, is based on state-of-the-art language processing technologies. The app provides instantaneous and accurate translations for conversations, documents, and various forms of by communication by utilizing artificial intelligence and natural language processing to translate spoken and written text in real-time. The Real-Time Language Translation App fundam

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Avinash, M., H. Sai Pranav, S. Hem Kesav, Tahmina Akter Khusba, and P. Paramasivan. "Unlocking Multilingual Communication: Exploring the Potential of a Chat Application." FMDB Transactions on Sustainable Computer Letters 2, no. 2 (2024): 85–98. http://dx.doi.org/10.69888/ftscl.2024.000183.

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Language barriers limit cross-cultural communication and collaboration in an increasingly interconnected world. Innovative multilingual chat apps use cutting-edge technologies to bridge language gaps and stimulate meaningful connections. This abstract describes a complicated multilingual chat application leveraging the MERN stack and AWS Translation services to revolutionize digital cross-cultural communication. Real-time translation in multilingual chat apps solves the problems. These algorithms recognize cross-linguistic interactions to provide inclusive digital environments where individual

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Rane, Kirti, Tanaya Bagwe,, Shruti Chaudhari, Ankita Kale, and Gayatri Deore. "Enhancing En-X Translation: A Chrome Extension-Based Approach to Indic Language Models." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42782.

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Language translation is the lifeblood of any communication that crosses linguistic boundaries. Recent trends in the domain of neural machine translation (NMT) are already superior to the old traditions. In such circumstances, the works done by Prahwini et al. (2024) and Vandan Mujadia et al. (2024) highlight the application of NMT for resource-constrained Indian languages. In view of many challenges like parallel corpus scarcity, we present a real-time adaptable translation model that works on the Fairseq framework. It provides high-accuracy translations for Assamese, Gujarati, Kannada, Bengal

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., Srisailanath. "Language Translator with Machine Learning (English-French)." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 5506–9. https://doi.org/10.22214/ijraset.2025.69523.

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In today’s globalized world, the need for efficient language translation tools has become critical. This project aims to develop a “Language Translation System” by integrating GNMT (Google Neural Machine Translation) Translation API and a user-friendly Streamlit interface. The system leverages advanced deep learning models trained on extensive datasets to provide accurate and context-aware translations. By focusing on accessibility and precision, the project seeks to bridge linguistic barriers and facilitate seamless communication. Users can input English text, select the desired target langua

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Raees, Azam, and Murtaza Ghulam. "Impact of Artificial Intelligence on English Language Translation." International Journal of Innovative Science and Research Technology (IJISRT) 10, no. 1 (2025): 1893–903. https://doi.org/10.5281/zenodo.14831448.

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In order to address issues like ethical dilemmas, cultural bias, and complex text interpretation, this study intends to investigate the revolutionary effects of artificial intelligence on English language translation, emphasizing its improvements in accuracy, accessibility, and real-time capabilities. The translation of English has been transformed by artificial intelligence (AI), which has improved accessibility, accuracy, and speed. AI-powered solutions like Google Translate and Deeply have greatly enhanced the quality of translations through sophisticated neural machine translation algorith

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Vasu, Kapil, Dheeraj, Chauhan Ritik, and Singh Amardeep. "Real-Time Language Translator with Sign Language Recognition: A Multi-Modal Approach." International Journal of Innovative Science and Research Technology (IJISRT) 10, no. 2 (2025): 567–70. https://doi.org/10.5281/zenodo.14921228.

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This research explores the development of a real-time language translation system integrating speech recognition, text-based translation, and sign language recognition. The system employs Google Translate API for multilingual translation, MediaPipe Hands for sign language recognition, and SpeechRecognition for real-time voice input. The study aims to bridge communication gaps between spoken, written, and signed languages. The paper presents implementation details, experimental results, and future scope for improvement. Findings indicate promising accuracy in sign recognition and speech transla

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Papi, Sara, Peter Polák, Dominik Macháček, and Ondřej Bojar. "How “Real” is Your Real-Time Simultaneous Speech-to-Text Translation System?" Transactions of the Association for Computational Linguistics 13 (April 3, 2024): 281–313. https://doi.org/10.1162/tacl_a_00740.

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Abstract Simultaneous speech-to-text translation (SimulST) translates source-language speech into target-language text concurrently with the speaker’s speech, ensuring low latency for better user comprehension. Despite its intended application to unbounded speech, most research has focused on human pre-segmented speech, simplifying the task and overlooking significant challenges. This narrow focus, coupled with widespread terminological inconsistencies, is limiting the applicability of research outcomes to real-world applications, ultimately hindering progress in the field. Our extensive liter

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Mohammed, Sahar Yousif, and Mohammad Aljanabi. "Advancing Translation Quality Assessment: Integrating AI Models for Real-time Feedback." EDRAAK 2024 (January 5, 2024): 1–7. https://doi.org/10.70470/edraak/2024/001.

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With the use of AI models for real-time reception a feedback, this review attempts to show how the assessment of the quality of translation is changing. The investigation covers aspects such as the technical side of the integration, efficiency and minimization of human errors, influence upon the translation industry including its services, costs and competitiveness and so forth. User experience and feedback, ethical issues, and implementation barriers are addressed for a more holistic view of the impacts of AI translation assessment. The discussion goes further and addresses the future of it,

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N, KEERTHI, CHETANA P. SUTHAR, and LEKHANA E. "REAL-TIME ACCENT TRANSLATOR." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40714.

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This paper introduces the "Real-Time Accent Translator," a lightweight and accessible web-based application that bridges the gap between multilingual communication and accent adaptation. Built on Flask, the system integrates Google Translate and Google Text-to-Speech (gTTS) APIs to provide seamless translation and speech synthesis. Users can input text in a source language, specify the target language, and optionally adjust accents for languages such as English. The application translates the text, synthesizes speech with the desired accent, and provides an audio output in real time. The archi

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Capece, Mark C., Guy L. Kornberg, Alexey Petrov, and Joseph D. Puglisi. "A simple real-time assay for in vitro translation." RNA 21, no. 2 (2014): 296–305. http://dx.doi.org/10.1261/rna.047159.114.

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Haj Aliwi, Hadeel Saleh, and Putra Sumari. "Real-Time Audio Translation Module Between Iax And Rsw." International journal of Computer Networks & Communications 6, no. 3 (2014): 121–29. http://dx.doi.org/10.5121/ijcnc.2014.6310.

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Wruck, Florian, Alexandros Katranidis, Knud H. Nierhaus, Georg Büldt, and Martin Hegner. "Translation and folding of single proteins in real time." Proceedings of the National Academy of Sciences 114, no. 22 (2017): E4399—E4407. http://dx.doi.org/10.1073/pnas.1617873114.

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Protein biosynthesis is inherently coupled to cotranslational protein folding. Folding of the nascent chain already occurs during synthesis and is mediated by spatial constraints imposed by the ribosomal exit tunnel as well as self-interactions. The polypeptide’s vectorial emergence from the ribosomal tunnel establishes the possible folding pathways leading to its native tertiary structure. How cotranslational protein folding and the rate of synthesis are linked to a protein’s amino acid sequence is still not well defined. Here, we follow synthesis by individual ribosomes using dual-trap optic

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Lee, Dong-Uk, Min-Seo Kim, Nam-Ho Kim, and Gwang-Mi Choi. "Implementation of Real-Time Sign Language AI Translation Program." Journal of Digital Contents Society 24, no. 10 (2023): 2585–91. http://dx.doi.org/10.9728/dcs.2023.10.24.10.2585.

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Lee, Dong-Uk, Min-Seo Kim, Nam-Ho Kim, and Gwang-Mi Choi. "Implementation of Real-Time Sign Language AI Translation Program." Journal of Digital Contents Society 24, no. 10 (2023): 2585–91. http://dx.doi.org/10.9728/dcs.2023.24.10.2585.

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Ms., H. Vaishnavi, Seetha Rama Raju SV Mr., Adaveni Nithin Mr., and Sandhya N. Dr. "Real-Time Sign Language Detection and Translation Using CNN." Journal of Scholastic Engineering Science and Management 2, no. 8 (2023): 1–11. https://doi.org/10.5281/zenodo.8170563.

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<strong>Our project focuses on the development of a computer application and the training of a model specifically  designed to interpret real-time video footage of hand gestures in American Sign Language (ASL). The primary objective  is to create a system that can accurately recognize and translate these gestures into corresponding text formats on the screen.  To achieve this, we have successfully implemented a set of 27 symbols representing the alphabet (A-Z) in ASL, along  with a symbol for blank or no gesture. Our project aims to provide a reliable and efficient tool for

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Yang, Ning. "Optimization and Performance Analysis of Real-time Speech Translation Systems Based on Mobile Technology." International Journal of Interactive Mobile Technologies (iJIM) 18, no. 23 (2024): 57–71. https://doi.org/10.3991/ijim.v18i23.52879.

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As globalization deepens and mobile technology rapidly advances, the demand for crosslinguistic communication has been steadily increasing, making real-time speech translation systems a research focus. However, given the limited computational capacity and storage space of mobile devices, optimizing system performance while maintaining translation quality has become a critical challenge. Current optimization approaches for real-time speech translation systems primarily focus on improvements to model architectures and hardware acceleration, often neglecting a systematic study of model compressio

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Ankit, Patil, Saudagar Karishma, Maharnawar Atul, Rangatwan Tejas, and Priyadarshini I. "Image Captioning in Real Time." Advancement in Image Processing and Pattern Recognition 5, no. 2 (2022): 1–12. https://doi.org/10.5281/zenodo.6759892.

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The current development in Deep Learning based Machine Translation and Computer Vision have led to incredible Image Captioning models using advanced techniques like Deep Learning. Even if these models are very accurate, they often rely on the use of exorbitant computation hardware making it problematic to apply these models in real-time scenarios, where their actual uses can be noticed. This model uses a hybrid CN-NRNN model, where the CNN part of the model system uses the Xception model for transfer learning, and RNNs are widely used in language modeling. The Flickr8k dataset is used for real

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Mayavathi, V. A., Ballani Vignesh, V. Hemavathi, Aditi Gupta, K. Gnanendra Varma, and Dr Galiveeti Poornima. "Realtime Accent Translation." International Journal for Research in Applied Science and Engineering Technology 13, no. 1 (2025): 1256–64. https://doi.org/10.22214/ijraset.2025.66549.

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Abstract: Accent Translation in Real-Time is one of the very first projects meant to overcome the barriers erected by regional accents in spoken languages. It uses the state-of-the-art research on speech recognition, NLP, and speech synthesis while translating speech from a source accent into a neutral or target accent in real-time. Accent detection and modification may include the use of deep learning models, like RNNs or transformers. In addition to the regional phonetic features, audio inputs on words with contextual meanings allow the reconstruction of the speech to conserve a desirable ac

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Pleijel, Richard. "Translation teams as cognitive systems." Developments in Cognitive Translation and Interpreting Studies 8, no. 2 (2021): 307–27. http://dx.doi.org/10.1075/cogls.00080.ple.

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Abstract This paper aims to bring research on different forms of group-level cognition into conversation with Cognitive Translation Studies (CTS), the focal point of the paper being cognitive processes in translation teams. It is argued that an analysis of cognition in translation teams, which exhibit the properties of a cognitive system, needs to be placed on group-level. A case study of a team, translating the Hebrew Bible Book of Psalms into Swedish in the 1980’s, is presented. The empirical base for the case study consists of archival material in the form of draft translations and paratext

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Zhao, Hongdan. "Realization of Chinese-English Bilingual Speech Dialogue System using Machine Translation Technology." Journal of Electrical Systems 20, no. 6s (2024): 1751–62. http://dx.doi.org/10.52783/jes.3093.

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The realization of a Chinese-English bilingual speech dialogue system through machine translation technology involves developing a sophisticated system capable of seamlessly translating spoken language between Chinese and English in real-time. This system employs cutting-edge machine learning algorithms, neural networks, and natural language processing techniques to accurately interpret and translate speech inputs from one language to another. By integrating advanced speech recognition and translation models, users can engage in fluid and natural conversations across language barriers, opening

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N, Sudiksha. "Talking Fingers: Bridging the Communication Gap through Real-Time Speech-to-Indian Sign Language Translation." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem40875.

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"Talking Fingers" is an innovative initiative to be developed to facilitate communication between hearing and non-hearing individuals by building a web-based system that can translate spoken language into Indian Sign Language (ISL). Being an essential means of communication among millions in India, ISL remains underdeveloped by technologies that are dominated by American and British Sign Languages. Current tools rely on the basic word-by-word translation with no contextual or grammatical accuracy. The proposed system will thus integrate speech recognition, NLP, and ISL visuals for real-time, c

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Yusnita, Lita, Rosalina Rosalina, Rusdianto Roestam, and R. B. Wahyu. "Implementation of Real-Time Static Hand Gesture Recognition Using Artificial Neural Network." CommIT (Communication and Information Technology) Journal 11, no. 2 (2017): 85. http://dx.doi.org/10.21512/commit.v11i2.2282.

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This paper implements static hand gesture recognition in recognizing the alphabetical sign from “A” to “Z”, number from “0” to “9”, and additional punctuation mark such as “Period”, “Question Mark”, and “Space” in Sistem Isyarat Bahasa Indonesia (SIBI). Hand gestures are obtained by evaluating the contourrepresentation from image segmentation of the glove wore by user. Then, it is classified using Artificial Neural Network (ANN) based on the training model previously built from 100 images for each gesture. The accuracy rate of hand gesture translation is calculated to be 90%. Moreover, speech

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Carmichael, Stephen W. "Visualizing Gene Expression in Real-Time." Microscopy Today 13, no. 3 (2005): 3–7. http://dx.doi.org/10.1017/s1551929500051567.

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Gene expression has been visualized for a few decades, but in static forms such as blots and gene chips. Susan Janicki, Toshiro Tsukamoto, Sim one Salghetti, William Tansey, Ravi Sachidanandam, Kannanganattu Prasanth, Thomas Ried, Yaron Shav-Tal, Edouard Bertrand, Robert Singer, and David Spector have recently designed a cell line in which gene expression can be observed with stunningly accurate spatial and temporal resolution. Gene expression is a cascade of events beginning with transcription of RNA from the DNA template and ending with translation into a protein sequence. Janicki et al. wer

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Deepika Kongara. "A Framework for Character Recognition APP Using ML Kit." Journal of Information Systems Engineering and Management 10, no. 41s (2025): 940–52. https://doi.org/10.52783/jisem.v10i41s.8021.

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Character recognition applications are pivotal in enabling real-time translation and digitization of printed and handwritten text. Text recognition can be implemented using a variety of technologies found in the field of software development, but here for Android mobile development, the ML Kit is used. The goal is to create an Android character recognition app, especially for Devanagari script (with language converter software included as a feature), using the ML kit without Firebase that will make recognizing, learning, and language translation easier and will promote stress-free communicatio

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Bādere, Aiga. "Labskanīgs mašīntulkojums – ieguvums un risks." Vārds un tā pētīšanas aspekti: rakstu krājums = The Word: Aspects of Research: conference proceedings, no. 28 (November 25, 2024): 12–23. https://doi.org/10.37384/vtpa.2024.28.012.

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Today, translation cannot be imagined without various language technologies, including opportunities provided by machine translation. Owing to the neural machine translation, MT has become a revolution, and from 2016, it is continuing its triumphal march around the world, i. e., MT used to be one of many tools used by translators, while now it is one of the leading tools. Neural MT undoubtedly offers several advantages compared to rule-based and statistical MT. More and more systems are also adaptive and learn in real time, thus ensuring consistency and speed. The systems also provide fluent t

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K., Akshay, Aravind Das, Carral Vincent, Betty Babu, and Rasmi P. "Real Time Translation of Malayalam Notice Boards to English Directions." International Journal of Computer Applications 178, no. 26 (2019): 6–10. http://dx.doi.org/10.5120/ijca2019919079.

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NOVITASARI, Sashi, Sakriani SAKTI, and Satoshi NAKAMURA. "Neural Incremental Speech Recognition Toward Real-Time Machine Speech Translation." IEICE Transactions on Information and Systems E104.D, no. 12 (2021): 2195–208. http://dx.doi.org/10.1587/transinf.2021edp7014.

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Sanaullah, Muhammad, Babar Ahmad, Muhammad Kashif, et al. "A Real-Time Automatic Translation of Text to Sign Language." Computers, Materials & Continua 70, no. 2 (2022): 2471–88. http://dx.doi.org/10.32604/cmc.2022.019420.

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Otoom, Mwaffaq, and Mohammad A. Alzubaidi. "Ambient intelligence framework for real-time speech-to-sign translation." Assistive Technology 30, no. 3 (2017): 119–32. http://dx.doi.org/10.1080/10400435.2016.1268218.

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M, Yasaswini, Sanjay S 2, Lokesh U, and Arun M. A. "Real Time Hand Sign Language Translation: Text and Speech Conversion." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 008 (2024): 1–12. http://dx.doi.org/10.55041/ijsrem36998.

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The Sign Language conversion project presents a real-time system that can interpret sign language from a live webcam feed. Leveraging the power of the Media pipe library for landmark detection, the project extracts vital information from each frame, including hand landmarks. The detected landmark coordinates are then collected and stored in a CSV file for further analysis. Using machine learning techniques, a Random Forest Classifier is trained on this landmark data to classify different sign language patterns. During the webcam feed processing, the trained model predicts the sign language cla

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Olderog, Ernst-Rüdiger. "Translation and Optimization in the Verification of Real-Time Systems." Electronic Notes in Theoretical Computer Science 82, no. 2 (2004): 345. http://dx.doi.org/10.1016/s1571-0661(05)82594-0.

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Milón, Pohl, Cristina Maracci, Liudmila Filonava, Claudio O. Gualerzi, and Marina V. Rodnina. "Real-time assembly landscape of bacterial 30S translation initiation complex." Nature Structural & Molecular Biology 19, no. 6 (2012): 609–15. http://dx.doi.org/10.1038/nsmb.2285.

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Papatsimouli, Maria, Panos Sarigiannidis, and George F. Fragulis. "A Survey of Advancements in Real-Time Sign Language Translators: Integration with IoT Technology." Technologies 11, no. 4 (2023): 83. http://dx.doi.org/10.3390/technologies11040083.

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Real-time sign language translation systems are of paramount importance in enabling communication for deaf and hard-of-hearing individuals. This population relies on various communication methods, including sign languages and visual techniques, to interact with others. While assistive technologies, such as hearing aids and captioning, have improved their communication capabilities, a significant communication gap still exists between sign language users and non-users. In order to bridge this gap, numerous sign language translation systems have been developed, encompassing sign language recogni

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