ANNOTATION MODEL FOR LOANWORDS IN INDONESIAN CORPUS: A LOCAL GRAMMAR FRAMEWORK

There is a considerable number for loanwords in Indonesian language as it has been, or even continuously, in contact with other languages. The contact takes place via different media; one of them is via machine readable medium. As the information in different languages can be obtained by a mouse click these days, the contact becomes more and more intense. This paper aims at proposing an annotation model and lexical resource for loanwords in Indonesian. The lexical resource is applied to a corpus by a corpus processing software called UNITEX. This software works under local grammar framewor

Linguistically-Informed Neural Architectures for Lexical, Syntactic and Semantic Tasks in Sanskrit

The primary focus of this thesis is to make Sanskrit manuscripts more accessible to the end-users through natural language technologies. The morphological richness, compounding, free word orderliness, and low-resource nature of Sanskrit pose significant challenges for developing deep learning solutions. We identify four fundamental tasks, which are crucial for developing a robust NLP technology for Sanskrit: word segmentation, dependency parsing, compound type identification, and poetry analysis. The first task, Sanskrit Word Segmentation (SWS), is a fundamental text processing task for any other downstream applications. However, it is challenging due to the sandhi phenomenon that modifies characters at word boundaries. Similarly, the existing dependency parsing approaches struggle with morphologically rich and low-resource languages like Sanskrit. Compound type identification is also challenging for Sanskrit due to the context-sensitive semantic relation between components. All these challenges result in sub-optimal performance in NLP applications like question answering and machine translation. Finally, Sanskrit poetry has not been extensively studied in computational linguistics. While addressing these challenges, this thesis makes various contributions: (1) The thesis proposes linguistically-informed neural architectures for these tasks. (2) We showcase the interpretability and multilingual extension of the proposed systems. (3) Our proposed systems report state-of-the-art performance. (4) Finally, we present a neural toolkit named SanskritShala, a web-based application that provides real-time analysis of input for various NLP tasks. Overall, this thesis contributes to making Sanskrit manuscripts more accessible by developing robust NLP technology and releasing various resources, datasets, and web-based toolkit.Comment: Ph.D. dissertatio

Machine Translation Using Open NLP and Rules Based System “English to Marathi Translator”

This paper presents a proposed system for machine translation of English Interrogative and Assertive sentences to their Marathi counterpart. The system takes simple all English sentences as an input and performs its lexical analysis using parser. Every token produced by parser is searched in the English lexicon using Lexical analysis. If the token is found in then lexicon, its morphological information is preserved. Here we broadly use Open NLP and Rule Based System. Machine Translation is main areas which focusing to Natural Language Processing where translation is done from One Language to Another Language preserving the meaning of the sentence. Big amount of research is being done in this Machine Translation. However, research in Natural Language processing remains highly centralized to the particular source and due to the large variations in the syntactical building of languages

Development of Multilingual Resource Management Mechanisms for Libraries

Multilingual is one of the important concept in any library. This study is create on the basis of global recommendations and local requirement for each and every libraries. Select the multilingual components for setting up the multilingual cluster in different libraries to each user. Development of multilingual environment for accessing and retrieving the library resources among the users as well as library professionals. Now, the methodology of integration of Google Indic Transliteration for libraries have follow the five steps such as (i) selection of transliteration tools for libraries (ii) comparison of tools for libraries (iii) integration Methods in Koha for libraries (iv) Development of Google indic transliteration in Koha for users (v) testing for libraries (vi) results for libraries. Development of multilingual framework for libraries is also an important task in integrated library system and in this section have follow the some important steps such as (i) Bengali Language Installation in Koha for libraries (ii) Settings Multilingual System Preferences in Koha for libraries (iii) Translate the Modules for libraries (iv) Bengali Interface in Koha for libraries. Apart from these it has also shows the Bengali data entry process in Koha for libraries such as Data Entry through Ibus Avro Phonetics for libraries and Data Entry through Virtual Keyboard for libraries. Development of Multilingual Digital Resource Management for libraries by using the DSpace and Greenstone. Management of multilingual for libraries in different areas such as federated searching (VuFind Multilingual Discovery tool ; Multilingual Retrieval in OAI-PMH tool ; Multilingual Data Import through Z39.50 Server ). Multilingual bibliographic data edit through MarcEditor for the better management of integrated library management system. It has also create and editing the content by using the content management system tool for efficient and effective retrieval of multilingual digital content resources among the users