Relevant bibliographies by topics / Translations into Kannada

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Academic literature on the topic 'Translations into Kannada'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Translations into Kannada"

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Prasada, Padma, and Malode Vishwanatha Panduranga Rao. "Reinforcement of low-resource language translation with neural machine translation and backtranslation synergies." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 3 (September 1, 2024): 3478. http://dx.doi.org/10.11591/ijai.v13.i3.pp3478-3488.

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<p><span lang="EN-US">This research investigates challenges and advancements in neural machine translation (NMT), specifically targeting English-to-Kannada translation. Emphasizing the scarcity of data and linguistic complexity in low-resource languages (LRL), particularly Kannada, the study underscores the need for specialized techniques. Starting with exploration of Kannada's historical and cultural significance, the paper highlights critical importance of linguistic comprehension. The primary objective is to develop robust NMT models for precise and contextually relevant translations in low-resource scenarios. The novelty of this research lies in its innovative approach to Kannada NMT challenges, incorporating comprehensive examination of historical and cultural context to establish strong linguistic foundation. Motivated by the urgency to address translation needs in LRL, the paper proposes novel strategies, advocating notably for backtranslation to generate synthetic parallel corpora. Rigorous testing, including bilingual evaluation understudy (BLEU) score assessments, evaluates effectiveness of these proposed approaches. Beyond assessing backtranslation, the study explores challenges faced by Kannada NMT in handling dialectical and spelling variations. The research reports substantial 83-percentage-point average increase in BLEU scores, contingent on aligning unique Kannada terms with the same domain as existing occurrences. This study contributes significantly to Kannada natural language processing by offering novel insights into NMT intricacies and providing practical solutions for enhancing translation accuracy in low-resource settings.</span></p>
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Koudur, Shashikantha. "Languages, Castes and Hierarchy: Basel Mission in Nineteenth-Century Coastal Karnataka." South Asia Research 40, no. 2 (April 26, 2020): 250–65. http://dx.doi.org/10.1177/0262728020915563.

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In the former South Kanara or south coastal Karnataka region, the presence of overlapping languages, mainly Tulu and Kannada, posed prolonged dilemmas in the nineteenth century for the Basel Mission. The choice of language was important for their evangelical work, supported by important language-related activities such as dictionary making, grammar writing and translations. Since language use was intertwined with caste hierarchy, this raised issues over the position of lower castes, mainly Billavas, for the native elites and upper castes. This article argues that the prioritisation of Kannada, and relegation of Tulu to a secondary position, was an outcome not only of missionary perceptions of the larger Kannada context, but also more importantly can be traced back to elite representations regarding the subaltern Tulu culture and lifeworld. As missionary intervention in education and native language use challenged the status quo of social hierarchy among local communities, this sparked efforts by the native elites to reclaim and restore the earlier hierarchy. In the process, the native elite representations of Tulu language and culture became at the same time an effort at dismissal and appropriation.
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SUNNY, Ms ANCY K. "A Novel Approach to Malayalam Speech-to-Text and Text-to-English Translation." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 6, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem33108.

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This paper presents a novel approach to facilitate Malayalam speech-to-text transcription and subsequent translation into English text. The proposed system leverages advancements in speech recognition, natural language processing, and machine translation techniques. We demonstrate the effectiveness of our approach through a practical implementation and evaluation. Introduction: The ability to accurately transcribe spoken language and translate it into other languages has numerous applications in today's digital world. However, the development of such systems for languages with complex structures, such as Malayalam, presents unique challenges. In this paper, we propose a solution to address these challenges by combining state-of-the-art technologies in speech recognition and machine translation. Literature Review: Previous studies have explored various approaches to speech-to-text transcription and machine translation. However, few have focused specifically on the Malayalam language. Existing systems often struggle with accurately transcribing and translating Malayalam due to its complex morphology and syntax. Methodology: Our approach consists of several key steps: Speech Recognition : We employ the SpeechRecognition library to transcribe spoken Malayalam into text. Text Preprocessing: The transcribed text undergoes preprocessing, including tokenization and normalization, using the IndicNLP library. Translation: The preprocessed text is translated into English using a custom-built translation model implemented with CTranslate2 and SentencePiece. Results: We evaluated our system using a dataset of spoken Malayalam sentences. The system achieved a high accuracy in speech recognition and produced fluent translations into English. Discussion: Our results demonstrate the feasibility and effectiveness of our approach in accurately transcribing and translating spoken Malayalam. However, certain challenges remain, such as handling dialectal variations and improving translation quality for complex sentences. Conclusion: In conclusion, we have presented a novel approach to Malayalam speech-to-text transcription and text-to-English translation. Our system shows promising results and opens up possibilities for further research and development in this area. References: [1] S. K. Sheshadri, B. S. Bharath, A. H. N. S. C. Sarvani, P. R. V. B. Reddy, and D. Gupta, “Unsupervised neural machine translation for english to kannada using pre-trained language model,” pp. 1–5, 2022. [2] A. H. Patil, S. S. Patil, S. M. Patil, and T. P. Nagarhalli, “Real time machine translation system between indian languages,” pp. 1778–1783, 2022.
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Arnold, B. J., H. Du, S. Eremenco, and D. Cella. "Using the FACT-Neurotoxicity Subscale to evaluate quality of life in patients from across the globe." Journal of Clinical Oncology 25, no. 18_suppl (June 20, 2007): 17032. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.17032.

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17032 Background: Translation of Patient Reported Outcomes measures is an essential component of research methodology in preparation for multinational clinical trials. One such measure is the FACT-Neurotoxicity Subscale (FACT-Ntx) which is aimed at the evaluation of quality of life of cancer patients suffering from neurotoxicity, a side effect of certain treatments. Methods: This study set out to linguistically validate the FACT-Ntx for use in Denmark, India, Lithuania and S. Africa. The sample consisted of 176 patients (96 males & 80 females), with varying cancer diagnoses and a mean age of 51 years, speaking 11 languages: Afrikaans (15), Danish (25), Gujarati (15), Hindi (15), Kannada (15), Lithuanian (15), Malayalam (15), Marathi (15), Punjabi (15), Tamil (15) and Telugu (16). The FACT-Ntx was translated using standard FACIT methodology. Patients diagnosed with cancer, at any stage, receiving any treatment experiencing neurotoxicity completed the respective translated version and participated in cognitive debriefing interviews to give their opinion on any problems with the translations or the content of the FACT-Ntx. Statistical analyses (descriptive statistics, one-way ANOVA and reliability analyses) were performed on the quantitative data. Participant comments were analyzed qualitatively. Results: The FACT-Ntx translations showed good reliability and linguistic validity. The internal consistency of all languages combined was .86. All items correlated at an acceptable level. The Ntx score differed across self-reported Performance Status Rating (PSR) groups (nonparametric Kruskal-Wallis test p<.0001). A nonparametric Generalized Linear Model (GLM) approach (with multiple comparison adjusted significance level 0.017) showed a difference between ‘PSR=0’ and ‘PSR=1’ (p=0.0002) and a difference between ‘PSR=0’ and ‘PSR=2’ (p<.0001), both with ‘PSR=0’ patients reporting less neurotoxicity. Conclusions: The FACT-Ntx has shown acceptable reliability and linguistic validity in 11 languages. The instrument has also shown adequate sensitivity in differentiating patients with no symptoms and normal activity from patients reporting some symptoms. We consider these translations acceptable for use in international research and clinical trials. No significant financial relationships to disclose.
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UROLAGIN, SIDDHALING, K. V. PREMA, and N. V. SUBBA REDDY. "KANNADA ALPHABETS RECOGNITION WITH APPLICATION TO BRAILLE TRANSLATION." International Journal of Image and Graphics 11, no. 03 (July 2011): 293–314. http://dx.doi.org/10.1142/s0219467811004159.

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In this paper, an effort is made to apply optical character recognition (OCR) for Braille translation on Kannada characters. In general, OCR systems for Indian language are more complex due to larger number of vowels, consonants, and conjuncts and Indian languages are inflectional and agglutinative in nature. Specifically, characters of Kannada script have higher similarity in shape and higher variability across fonts, making recognition of characters a difficult task. A decision tree is developed in this research work. The main motivations are that decision trees provide a natural way to incorporate prior knowledge of domain and many Kannada characters have similar looking shapes. The similar looking characters can be grouped and then further partitioned into categories at various levels to effectively create a decision tree. To facilitate this, three modular classifiers are developed based on the nature of Kannada characters. These modular classifiers are employed at nodes of the decision tree. The Braille equivalent of Kannada characters is obtained by translation rules. An overall accuracy of classification and Braille translation of 93.80% is obtained.
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Ancy, R. J., Rekha P. Shenoy, Laxminarayan Sonde, and Imran Pasha Mohammed. "Translation and Validation of the Kannada Version of the Psychosocial Impact of Dental Aesthetics Questionnaire." Journal of Indian Association of Public Health Dentistry 21, no. 4 (2023): 300–305. http://dx.doi.org/10.4103/jiaphd.jiaphd_20_22.

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Background: The Psychosocial Impact of Dental Aesthetics Questionnaire (PIDAQ) is used to evaluate the self-reported impact of dental esthetics on quality of life of adolescents. Aim: PIDAQ was not available in Kannada. Prompted by the importance that this type of questionnaire has acquired, this study aimed to translate the original English version of PIDAQ into Kannada and to assess the validity and reliability of the translated Kannada version in order to provide a theoretical basis for further application in Kannada-speaking adolescents. Materials and Methods: A school-based descriptive cross-sectional study was conducted among 13–19-year-old adolescents. The study was conducted on a pilot sample (n = 20), and a final study sample (n = 92) was selected conveniently from five different higher secondary schools in Mangalore. PIDAQ was given. Dental esthetics was assessed using the Aesthetic Component of Index of Orthodontic Treatment Need and the Dental Aesthetic Index. Internal consistency was measured using Cronbach’s alpha coefficient. Construct validity was studied by carrying out factor analysis. Test–retest reliability was tested using intra-class correlation coefficient. Results: The Kannada PIDAQ showed good reliability with Cronbach’s alpha of 0.832 and overall test–retest reliability ranging from 0.723 to 0.980. The construct validity was good with formation of two new domains “Self-consciousness” and “Aspiration.” Conclusion: The good validity and reliability of Kannada PIDAQ make it a suitable tool for assessment of the psychosocial impact of dental esthetics among adolescents who are fluent in reading, writing, and understanding Kannada.
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Naik, Bharathi, Shankar Prasad Nagaraju, Vasudeva Guddattu, Naveen Salins, Ravindra Prabhu, Anuja Damani, Prathvi Naik, Krithika S. Rao, Indu Ramachandra Rao, and Pankaj Singhai. "Kannada Translation and Validation of the ESAS-r Renal for Symptom Burden Survey in Patients with End-Stage Kidney Disease." Indian Journal of Palliative Care 29 (May 30, 2023): 195–99. http://dx.doi.org/10.25259/ijpc_216_2022.

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Objectives: End-stage kidney disease (ESKD) is a life-limiting illness that leads to significant health-related suffering for the patients and their caregivers. Moreover, disease-directed options such as dialysis and renal transplant might not be universally accessible. Inadequate assessment and management of symptoms often lead to diminished quality of life. For evaluating symptoms and their associated distress, various tools have been identified. However, these are not available for the native Kannada-speaking population for assessing ESKD symptom burden. In this study, we determined the reliability and validity of the Edmonton Symptom Assessment System Revised Renal (ESAS-r: Renal) in Kannada-speaking ESKD patients. Materials and Methods: ESAS-r: Renal English version was translated into Kannada using the forward and backward method. The translated version was endorsed by Nephrology, Palliative care, Dialysis technology and Nursing experts. As a pilot study, 12 ESKD patients evaluated the content of the questionnaires for appropriateness and relevance. The ESAS-r: Renal Kannada version was validated by administering this tool to 45 patients twice a fortnight. Result: The translated ESAS-r: Renal Kannada version questionnaire had an acceptable face and content validity. Experts’ opinion was assessed by content validity ratio (CVR), and the value of CVR of ESAS-r: Renal Kannada version was-‘1’-. Internal consistency of the tool was assessed among Kannada-speaking ESKD patients; its Cronbach’s α was 0.785, and test-retest validity was 0.896. Conclusion: The validated Kannada version of ESAS-r: Renal was reliable and valid for assessing symptom burden in ESKD patients.
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Reddy, P. Deepak. "Multilingual Speech to Text using Deep Learning based on MFCC Features." Machine Learning and Applications: An International Journal 9, no. 02 (June 30, 2022): 21–30. http://dx.doi.org/10.5121/mlaij.2022.9202.

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The proposed methodology presented in the paper deals with solving the problem of multilingual speech recognition. Current text and speech recognition and translation methods have a very low accuracy in translating sentences which contain a mixture of two or more different languages. The paper proposes a novel approach to tackling this problem and highlights some of the drawbacks of current recognition and translation methods. The proposed approach deals with recognition of audio queries which contain a mixture of words in two different languages - Kannada and English. The novelty in the approach presented, is the use of a next Word Prediction model in combination with a Deep Learning speech recognition model to accurately recognise and convert the input audio query to text. Another method proposed to solve the problem of multilingual speech recognition and translation is the use of cosine similarity between the audio features of words for fast and accurate recognition. The dataset used for training and testing the models was generated manually by the authors as there was no pre-existing audio and text dataset which contained sentences in a mixture of both Kannada and English. The DL speech recognition model in combination with the Word Prediction model gives an accuracy of 71% when tested on the in-house multilingual dataset. This method outperforms other existing translation and recognition solutions for the same test set. Multilingual translation and recognition is an important problem to tackle as there is a tendency for people to speak in a mixture of languages. By solving this problem, the barrier of language and communication can be lifted and thus can help people connect better and more comfortably with each other.
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Usha, S. M., D. Mahesh Kumar, and H. B. Mahesh. "Traffic Signboard Recognition and Text Translation System using Word Spotting and Machine Learning." ITM Web of Conferences 50 (2022): 01010. http://dx.doi.org/10.1051/itmconf/20225001010.

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This project will help the non-native people of Karnataka to easily understand the kannada boards and travel easily. The main task of this work is to recognize the kannada traffic text boards and translate that to English language. Histogram equalization is used to find the gap between the characters. K-means clustering is used to divide the characters into different clusters then the segmented characters are passed to the pretrained model to recognize what the characters means. The model used for recognizing the traffic text is convolutional neural networks. The methodologies used here is the image augmentation, converting RGB image to grey scale and normalizing the image to reduce the noise. The validation accuracy obtained while training the model with coloured images, normalized image, grey scale image and normalized grey scale image is respectively 98.88%, 98.85%, 98.8% and 99.39% and while testing this model with kannada language, the testing accuracy obtained respectively with coloured images, normalized image, grey scale and normalized grey scale image is 95.91%, 96.58%, 95.42% and 96.98 % . In this work, word spotting method is employed for kannada language recognition. The performance of this system is faster since machine learning algorithms are used here.
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Javaregowda, D. C., B. Parthasarathy, A. Suresh, D. Lokanath, K. Govind Babu, B. Ullas, G. Anupama, and K. Sani. "Validation of 12-item general health questionnaire into Kannada language." Journal of Clinical Oncology 25, no. 18_suppl (June 20, 2007): 17077. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.17077.

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17077 Background: The cancer load in India is enormous and majority of the cases present in an advanced stage. There is no valid translation of 12-item General Health Questionnaire (GHQ-12) in Kannada, which is a simple but indispensable tool in the comprehensive cancer care (both for metastatic and in adjuvant settings). Therefore we thought of developing and validating the GHQ-12 Questionnaire into Kannada language. Methods: The study was conducted at kidwai memorial institute of Oncology, Bangalore, a tertiary cancer center with an annual attendance of 16,000 new cases. We have chosen educated patients who can speak and write both English and Kannada. We used ’forward-backward’ translation procedure into Kannada. We used scores from 0–3 for the Questionnaire. Total score for both languages was calculated. Internal consistency was assessed by Cronbach's alpha coefficient. Validity was performed using convergent validity. Finally, the factor structure of the questionnaire was extracted by performing principal component analysis using oblique factor solution. Results: A total of 118 patients with various malignancies were entered into the study. The mean age was 36.8 ± 12.1 years. The mean GHQ score was 21.6 ± 9.1 for the English and 22.6 ± 8.1 for Kannada. Reliability analysis showed satisfactory result (Cronbach's alpha coefficient = 0.79). The principal component analysis with oblique rotation solution showed that the GHQ-12 was a measure of psychological morbidity with four -factor structure that jointly accounted for 48 % of the variance. Conclusions: The Kannada version of the GHQ-12 is a reliable and valid instrument with a good structural characteristic. It can be used for measuring psychological well being at our institute for those patients who can read and write only Kannada. No significant financial relationships to disclose.
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Books on the topic "Translations into Kannada"

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Rao, Ub Narasinga. A handbook of Kannada proverbs, with English equivalents. New Delhi: Asian Educational Services, 1988.

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1925-, Śarma Rāmacandra, ed. From Cauvery to Godavari: Modern Kannada short stories. New Delhi, India: Penguin Books, 1992.

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Kabaphēs, Kōnstantinos Petrou. Vasanta nannoḷagide: Kavaphi kavitegaḷu. Beṅgalūru: Dhātri Pustaka, 2010.

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Amr̥ta, Sōmēśvara. Karegāḷi: Tuḷu-Kannaḍa bhāvagītagaḷu. Kōṭekāru: Prakr̥ti Prakāśana, 2004.

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editor, Paṭṭaṇaśeṭṭi Mālati, and Karnāṭaka Sāhitya Akāḍemi, eds. "Thou art translated": Doffing the Kannada hat to Shakespeare : Shakespeare in the Kannada world : Jan 2013 - March 2016 (combined edition) : Aniketana, a quarterly journal of Kannada language and literature. Bengaluru: Karnataka Sahithya Academy, 2016.

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editor, Paṭṭaṇaśeṭṭi Mālati, and Karnāṭaka Sāhitya Akāḍemi, eds. Women's voices in Kannada: Jan 2012 - December 2012 (combined edition) : Aniketana, a quarterly journal of Kannada language and literature. Bengaluru: Karnataka Sahithya Academy, 2015.

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Vivēka Rai, Bi. E., editor, translator, Kannada University Prasaranga, and Kannada University. Center for Translations, eds. Classical Kannada poetry and prose: A reader : selections: Halmidi Edict, 5th century, to Janna, 13th century, in translation. Hampi: Prasaranga, Kannada University, 2015.

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translator, Sukanya Kanarally, Sahitya Akademi, and Central Institute of Indian Languages, eds. An afternoon with Shakuntala and other stories. New Delhi: Sahitya Akademi, 2016.

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Basava. Forever saints: Selected vachanas of Basavanna, Allama Prabhu, and Akka Mahadevi. Mysore: Jagadguru Sri Shivarathreeswara Granthamala, 2006.

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Bhālacandra, Jayaśeṭṭī, ed. "Vacana". Beṅgalūra: Karnāṭaka Sāhitya Akādamī, 1998.

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Book chapters on the topic "Translations into Kannada"

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Kragh, Ulrich Timme, and Abhishek Jain. "1. Jane, Come with Me to India." In Prismatic Jane Eyre, 92–183. Cambridge, UK: Open Book Publishers, 2023. http://dx.doi.org/10.11647/obp.0319.04.

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The essay presents the reception of Jane Eyre on the Indian subcontinent. It examines the Indian motif within Brontë’s novel, surveys seven literary and cinematographic Jane Eyre adaptations in five Indian languages produced between 1914 and 1972, discusses the history of Indian translation practices and presents eighteen Jane Eyre translations into nine Indian languages that appeared between 1953 and 2020, and finally synoptically analyses four passages from two literal translations into Hindi and Kannada and an abridged translation into Gujarati. Throughout, the essay proposes a new approach to narrative analysis based on an Indian dramaturgical model, a new definition of translation and adaptation based on the Indian philosophical notion of transformation, and a new criterion drawn from Indian poetics for distinguishing between the notions of adaptation, abridgement, and translation.
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Tharakeshwar, V. B. "Translating tragedy into Kannada." In Benjamins Translation Library, 57–74. Amsterdam: John Benjamins Publishing Company, 2009. http://dx.doi.org/10.1075/btl.86.07tha.

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Tharakeshwar, V. B. "Translation and the Making of Modern Kannada Literature." In Indian Modernities, 258–308. London: Routledge India, 2023. http://dx.doi.org/10.4324/9781003405788-21.

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Reddy, Mallamma V., and M. Hanumanthappa. "Indic Language Machine Translation Tool: English to Kannada/Telugu." In Lecture Notes in Electrical Engineering, 35–49. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1143-3_4.

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S., Parameswarappa, and Narayana V.N. "Disambiguating Phrasal Verbs in English to Kannada Machine Translation." In Wireless Networks and Computational Intelligence, 405–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31686-9_47.

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Hegde, Asha, Hosahalli Lakshmaiah Shashirekha, Anand Kumar Madasamy, and Bharathi Raja Chakravarthi. "A Study of Machine Translation Models for Kannada-Tulu." In Third Congress on Intelligent Systems, 145–61. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9225-4_12.

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Hegde, Asha, and Hosahalli Lakshmaiah Shashirekha. "KanSan: Kannada-Sanskrit Parallel Corpus Construction for Machine Translation." In Communications in Computer and Information Science, 3–18. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-33231-9_1.

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Gurevitch, Eric. "Practices of Translation in Medieval Kannada Sciences: ‘Removing the Conflict Between Textual Authority and the Worldly’." In Narratives on Translation across Eurasia and Africa, 249–70. Turnhout, Belgium: Brepols Publishers, 2022. http://dx.doi.org/10.1484/m.cat-eb.5.127944.

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Kumar, Raghvendra, Prasant Kumar Pattnaik, and Priyanka Pandey. "Conversion of Higher into Lower Language Using Machine Translation." In Web Semantics for Textual and Visual Information Retrieval, 92–107. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2483-0.ch005.

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This chapter addresses an exclusive approach to expand a machine translation system beginning higher language to lower language. Since we all know that population of India is 1.27 billion moreover there are more than 30 language and 2000 dialects used for communication of Indian people. India has 18 official recognized languages similar to Assamese, Bengali, English, Gujarati, Hindi, Kannada, Kashmiri, Konkani, Malayalam, Manipuri, Marathi, Nepali, Oriya, Punjabi, Sanskrit, Tamil, Telugu, and Urdu. Hindi is taken as regional language and is used for all types of official work in central government offices. Commencing such a vast number of people 80% of people know Hindi. Though Hindi is also regional language of Jabalpur, MP, India, still a lot of people of Jabalpur are unable to speak in Hindi. So for production those people unswerving to know Hindi language we expand a machine translation system. For growth of such a machine translation system, used apertium platform as it is free/open source. Using apertium platform a lot of language pairs more specifically Indian language pairs have already been developed. In this chapter, develop a machine translation system for strongly related language pair i.e Hindi to Jabalpuriya language (Jabalpur, MP, India).
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Bhagya, C. S. "Emergency in Ellipses." In The Oxford Handbook of Modern Indian Literatures, C49P1—C49P57. Oxford University Press, 2023. http://dx.doi.org/10.1093/oxfordhb/9780197647912.013.49.

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Abstract This chapter argues that U. R. Ananthamurthy’s 1976 novella Bara represents the Indian National Emergency (1975–1977) through ellipses. In the narrative, the bureaucratic machinery of the central and state governments colludes with self-regarding local leaders to exacerbate an ongoing ecological crisis—the titular “bara,” or drought—therefore worsening its impact on the depicted community in rural Karnataka. By situating its allusive form against patterns of representation in the anglophone literature of the Emergency, and alongside the National Award–winning Kannada film adaptation by M. S. Sathyu (1980), the chapter offers an intermedial, comparative analysis of Bara and its imagination of postcolonial Indian modernity. The chapter examines the novella’s linguistic idiosyncrasies and translational makeup to argue that “instability”—as feature and aesthetic—marks its form, its philosophy, and its negotiation of Emergency politics.
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Conference papers on the topic "Translations into Kannada"

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Shetty, Sannidhi, Pratiksha Narasimha Nayak G, Pranamya Mady, Vaishnavi K. Bhustali, and Chetana Hegde. "English to Kannada Translation Using BERT Model." In 2023 International Conference on Network, Multimedia and Information Technology (NMITCON). IEEE, 2023. http://dx.doi.org/10.1109/nmitcon58196.2023.10276314.

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Jamuna and H. R. Mamatha. "An Empirical Analysis of PoS Tagging for Kannada Machine Translation." In 2023 International Conference on Applied Intelligence and Sustainable Computing (ICAISC). IEEE, 2023. http://dx.doi.org/10.1109/icaisc58445.2023.10201030.

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Gadugoila, Hemalatha, Shailashree K. Sheshadri, Priyanka C. Nair, and Deepa Gupta. "Unsupervised Pivot-based Neural Machine Translation for English to Kannada." In 2022 IEEE 19th India Council International Conference (INDICON). IEEE, 2022. http://dx.doi.org/10.1109/indicon56171.2022.10039732.

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Parameswarappa, S., and V. N. Narayana. "Sense disambiguation of simple prepositions in English to Kannada Machine Translation." In 2012 International Conference on Data Science & Engineering (ICDSE). IEEE, 2012. http://dx.doi.org/10.1109/icdse.2012.6282320.

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Patil, Harshita Sahebgouda, K. V. Ikshu, Supreet Sidagondappagouda Patil, Sneha Manjunath Janawad, U. Purushotham, and K. V. Jyothi Prakash. "Translation of Different Dialects of Kannada to English Using Machine Learning." In 2024 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES). IEEE, 2024. http://dx.doi.org/10.1109/icsses62373.2024.10561318.

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Sindhu D.V and Sagar B.M. "A case study on linguistic divergences in Kannada-Telugu Machine Translation perceptive." In 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS). IEEE, 2016. http://dx.doi.org/10.1109/csitss.2016.7779448.

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Kashi, Sumukh R., Vineeth H R, and Gururaja H S. "eGRUMET: Enhanced Gated Recurrent Unit Machine for English to Kannada lingual Translation." In 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2023. http://dx.doi.org/10.1109/icccnt56998.2023.10307428.

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Kodabagi, Mallikarjun M., and S. A. Angadi. "A methodology for machine translation of simple sentences from Kannada to English language." In 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2016. http://dx.doi.org/10.1109/ic3i.2016.7917967.

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Rupanagudi, Sudhir Rao, Sushma Huddar, Varsha G. Bhat, Suman S. Patil, and Bhaskar M. K. "Novel methodology for Kannada Braille to speech translation using image processing on FPGA." In 2014 International Conference on Advances in Electrical Engineering (ICAEE). IEEE, 2014. http://dx.doi.org/10.1109/icaee.2014.6838445.

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Sheshadri, Shailashree K., B. Sai Bharath, Alapati Hari Naga Sree Chandana Sarvani, Potta Reddy Vijaya Bharathi Reddy, and Deepa Gupta. "Unsupervised Neural Machine Translation for English to Kannada Using Pre-Trained Language Model." In 2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2022. http://dx.doi.org/10.1109/icccnt54827.2022.9984521.

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