A Study of Machine Translation Approaches for Gujarati Language

Modh, Jatin C.

doi:10.26483/ijarcs.v9i1.5266

Cited by 5 publications

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“…Identification of all *Corresponding Author www.ijacsa.thesai.org Gujarati idiom phrases is concentrated here. Surrounding words are important for the idioms having more than one literal meaning in Gujarati language [6][7][8][9]. But the dynamic generation, as well as identification of all Gujarati idiom forms from the base form of the idiom, are focused here only.…”

Section: B Gujarati Idiomsmentioning

confidence: 99%

Dynamic Phrase Generation for Detection of Idioms of Gujarati Language using Diacritics and Suffix-based Rules

Modh¹,

Saini²

2021

IJACSA

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Gujarati is the language used for everyday communication in the state of Gujarat, India. The Gujarati language is also officially recognized by the constitution and the government of India. Gujarati script is based on the Devanagari script. An idiom is an expression, phrase, or word that has a different meaning from the literal meaning of the words in it. Idioms represent the cultural heritage of Gujarati language. Idioms are used in Gujarati language for effective communication and convey of an accurate message. No Machine Translation System does the accurate translation of Gujarati idioms to English or any other language. Different idiom phrases can be generated by adding diacritic(s) as well as suffix to the root or base form of the idiom. Many forms of single idiom make automatic idiom identification as well as machine translation more challenging. This paper focuses on the design and implementation of diacritics and suffix-based rules for dynamic phrase generation and detection of idioms of Gujarati language. This implementation helps in identifying Gujarati idiom present in any possible form in the Gujarati text. The obtained results with the execution of 7050 different Gujarati idiom phrases yield an accuracy of 99.73%. The results are encouraging enough to make the proposed implementation useful for Natural Language processing tasks related to Gujarati language idioms.

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Section: B Gujarati Idiomsmentioning

confidence: 99%

Dynamic Phrase Generation for Detection of Idioms of Gujarati Language using Diacritics and Suffix-based Rules

Modh¹,

Saini²

2021

IJACSA

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“…In the database, only bigram and trigram idioms having more than one-meaning are shown. Researchers had already experimented with single meaning idioms [20][21][22]. "Idiom" field stores the bigram/ trigram/n-gram idiom.…”

Section: Algorithmmentioning

confidence: 99%

Using IndoWordNet for Contextually Improved Machine Translation of Gujarati Idioms

Modh¹,

Jatinderkumar²

2021

IJACSA

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Gujarati language is the Indo-Aryan language spoken by the Gujaratis, the people of the state of Gujarat of India. Gujarati is the one of the 22 official languages recognized by the Indian government. Gujarati script was adopted from Devanagari script. Approximately 3000 idioms are available in Gujarati language. Machine translation of any idiom is the challenging task because contextual information is important for the translation of a particular idiom. For the translation of Gujarati idioms into English or any other language, surrounding contextual words are considered for the translation of specific idiom in the case of ambiguity of the meaning of idiom. This paper experiments the IndoWordNet for Gujarati language for getting synonyms of surrounding contextual words. This paper uses n-gram model and experiments various window sizes surrounding the particular idiom as well as role of stop-words for correct context identification. The paper demonstrates the usefulness of context window in case of ambiguity in the meaning identification of idioms with multiple meanings. The results of this research could be consumed by any destination-independent machine translation system for Gujarati language.

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“…If the context is captured properly it helps to deal with the ambiguous situation, where there is more than one different interpretation for the same word or phrase. The context capturing reduces the situation of ambiguity during decision-making in various NLP tasks, such as text translation [1], text simplification [2], information retrieval [3], etc.…”

Section: Introductionmentioning

confidence: 99%

An Overview of Context Capturing Techniques in NLP

Khem,

Panchal,

Bhatt

2023

IJRITCC

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In the NLP context identification has become a prominent way to overcome syntactic and semantic ambiguities. Ambiguities are unsolved problems but can be reduced to a certain level. This ambiguity reduction helps to improve the quality of several NLP processes, such as text translation, text simplification, text retrieval, word sense disambiguation, etc. Context identification, also known as contextualization, takes place in the preprocessing phase of NLP processes. The essence of this identification is to uniquely represent a word or a phrase to improve the decision-making during the transfer phase of the NLP processes. The improved decision-making helps to improve the quality of the output. This paper tries to provide an overview of different context-capturing mechanisms used in NLP.

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A Study of Machine Translation Approaches for Gujarati Language

Cited by 5 publications

References 0 publications

Dynamic Phrase Generation for Detection of Idioms of Gujarati Language using Diacritics and Suffix-based Rules

Dynamic Phrase Generation for Detection of Idioms of Gujarati Language using Diacritics and Suffix-based Rules

Using IndoWordNet for Contextually Improved Machine Translation of Gujarati Idioms

An Overview of Context Capturing Techniques in NLP

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