Qualification: 
MCA, BSc
jayashree@am.amrita.edu

Jayashree currently serves as an Assistant Professor at the Department of Computer Science Applications at Amrita School of Engineering, Amritapuri.

Publications

Publication Type: Conference Paper

Year of Publication Title

2019

Jayashree Nair, “Generating Noun Declension-case markers for English to Indian Languages in Declension Rule based MT Systems”, in IEEE 8th International Advance Computing Conference (IACC 2018), Uttar Pradesh, India., 2019.[Abstract]


Machine Translation is a branch of research under Computational Linguistics that deals with the automatic/semi-automatic translation of a natu-ral/human language into another. The language that is being translated is termed as Source Language(SL) and the language into which translation is done, is termed Target Language(TL). This paper presents an English to Indian Languages Machine Translation technique that is based on the rules of grammar, namely word declensions or inflections, and sentence formation rules of the target languages, i.e. Indian Languages. Declensions are variations or inflections of words in language and Indian languages are richly declensional or inflectional languages. This study is on generating Noun Declension-case markers for English to Indian languages in Declension Rule based Machine Translation. This paper also describes about the various approaches to machine translation along with their system architectures. The proposed Declension based RBMT is explained with its architecture and each of the modules and their functionalities are elaborated in detail. The input and output, to and from the system are also described with an example. The research works that are similar with the proposed system, such as ANUSAARAKA and ANGLABHARATI are also explored.

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2019

Jayashree Nair and Sadasivan, A., “A Roman to Devanagari Back-Transliteration Algorithm based on Harvard-Kyoto Convention”, in 2019 5th International Conference for Convergence in Technology, I2CT 2019, Pune, Maharastra, 2019.[Abstract]


Transliteration is the process to transcribe a script of one language into another, while, backward or back transliteration is converting back the transliterated text into its original script. The highly technical phonetic system of Sanskrit seems to have made the preparation of transliteration scheme quite arduous. This study is focused on development of a rule-based, grapheme model character alignment back-transliteration algorithm of Sanskrit script, transcribed ASCII(American Standard Code for Information Interchange)-encoded English to Devanagari, pursuant to the Harvard-Kyoto (HK) convention. Accordingly , the paper presents the context of the utility for such an algorithm. It also describes the various standard schemes available for transcribing Devanagari into Roman. A survey on the evolution of scripts in India suggests the Brahmi script as the foundation for the origin of variants like Devanagari. Since the nineteenth century, various transliteration schemes based on Roman script have evolved. The International Alphabet of Sanskrit Transliteration (IAST) schemes used diacritics to disambiguate phonetic similarities and seem to have induced much strenuous venture for the non-professionals. The ASCII-based, HK and its variant, Indian Language Transliteration (ITRANS) schemes do not use diacritics and hence accounted to be the simplest. Our rationale for the use of HK scheme, stem from its prime traits of Sanskrit Unicode encoding. We have also explained the Sanskrit alphabet and its classifications, which are incorporated into our proffered process. We appraise the complexity of our pseudo-coded algorithm and finally, we propose an extension of this work in the creation of similar tools, for other Indian languages that use the Devanagari script, such as Hindi and Marathi.

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2019

Jayashree Nair and Vinod, J., “Design of a Morphological Generator for an English to Indian Languages in a Declension Rule-based Machine Translation System”, in First International Conference on Advances in Electrical and Computing Technologies 2019 | ICAECT, Coimbatore, 2019.[Abstract]


Morphology is a branch of linguistics that deals with the internal structure of words in a natural language. Any word in a natural language is comprised of one or more morphemes. A morpheme is a smallest linguistic unit that forms a word. A morphological analyzer is a tool that analysis a given input word and outputs its internal structure along with its different morphemes. Conversely, a morphological generator creates the possible word(s) given the morphemes. This paper presents a design of a morphological generator for an English to Malayalam and English to Hindi rule-based machine translation system using declension rules. Declensions also termed as inflections are the different variations or inflected forms of a particular word in a language. Morphological generator is an essential part in the machine translation process that creates inflected words from the root word according to the morphological rules of a language. Machine translation is the branch of computational linguistics that automatically translates human language to another. The language to be translated is labeled as source language (SL) and the language into which translation is done is termed as target language (TL). The declension rule-based machine translation is accomplished by using grammar rules according to the word inflections of the target language. The proposed Morphological Generator module is elucidated with its framework and each of its modules and their working are expatiated in detail. The input to and the output from the module is also illustrated using examples.

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2016

Jayashree Nair, Krishnan, K. A., and Deetha, R., “An Efficient English to Hindi Machine Translation System Using Hybrid Mechanism”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016.[Abstract]


India is a multilingual country; different states have different territorial languages but not all Indians are polyglots. There are 18 constitutional languages and ten prominent scripts. The majority of the Indians, especially the remote villagers, do not understand, read or write English, therefore implementing an efficient language translator is needed. Machine translation systems, that translate text form one language to another, will enhance the knowledgeable society of Indians without any language barrier. English, being a universal language and Hindi, the language used by the majority of Indians, we propose an English to Hindi machine translation system design based on declension rules. This paper also describes the different approaches of Machine Translation.

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2016

A. Ajesh, Jayashree Nair, and Jijin, P. S., “A Random Forest Approach for Rating-based Recommender System”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016.[Abstract]


Recommender system has emerged as an integral part of the online shopping sites as it promotes sales. It recommends intuitive products based on users preference which solves the issue of information overload. Recommender system constitutes information filtering mechanism which filters vast amount of data. Algorithms such as SVD, KNN, Softmax Regression has already been used in the past to form recommendations. In this paper we propose a system which uses clustering and random forest as multilevel strategies to predict recommendations based on users ratings while targeting users mind-set and current trends. The result has been evaluated with the help of RMSE (Root Mean Square Error). Feasible performance has been achieved.

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Publication Type: Journal Article

Year of Publication Title

2018

Jayashree Nair, Menon, S., Prasad, A., C, D., Haridas, K., A, G. P., M, F. L., and Mohan, R., “Skilling, Productivity, And Sustainability: A Case Study Of Women Villagers In Himachal Pradesh”, 2018 IEEE Technological Innovations in ICT for Agriculture and Rural Development, TIAR 2018, 2018.

Faculty Research Interest: