Transliteration Of Words Research Articles

Enhancing the Transliteration of Words written in Javanese Script through Augmented Reality

Enhancing the Transliteration of Words written in Javanese Script through Augmented Reality

A Method for the Affixed Word Transliteration to the Balinese Script on the Learning Web Application

This research proposed a method for the affixed word transliteration to the Balinese Script since there has not been studied yet and it is important since the affixed word needs to be transliterated, inevitably. This research is one of the efforts to preserve digitally the endangered Balinese local language knowledge in Indonesia through the multi-discipline collaboration between Computer Science and Language discipline. The proposed method was taken care of two related aspects, i.e.; (1) A Latin root word has its related Balinese Script root word by using default or special transliteration rule; and (2) A Latin root word with a special transliteration rule for its Balinese Script root word, also need a special transliteration rule for its affixed word. This study was conducted on the pioneering web-based transliteration learning application, BaliScript, that receives the Latin text input and outputs the Balinese Script by using the Noto Serif Balinese font with its dedicated Balinese Unicode. Through the experiment, the proposed method gave the expected transliteration results, added a certain perspective, and strengthened the transliteration knowledge. Future work is to enhance and reuse this method on the mobile computing device, as a part of the Balinese Language ubiquitous learning that supports Balinese Language education, which is a mandatory local subject from the elementary school to the high school in Bali Province.

Learning Better Name Translation for Cross-Lingual Wikification

A notable challenge in cross-lingual wikification is the problem of retrieving English Wikipedia title candidates given a non-English mention, a step that requires translating names written in a foreign language into English. Creating training data for name translation requires significant amount of human efforts. In order to cover as many languages as possible, we propose a probabilistic model that leverages indirect supervision signals in a knowledge base. More specifically, the model learns name translation from title pairs obtained from the inter-language links in Wikipedia. The model jointly considers word alignment and word transliteration. Comparing to 6 other approaches on 9 languages, we show that the proposed model outperforms others not only on the transliteration metric, but also on the ability to generate target English titles for a cross-lingual wikifier. Consequently, as we show, it improves the end-to-end performance of a cross-lingual wikifier on the TAC 2016 EDL dataset.

Between Languages and Cultures: Arabic into English Transliteration in English Travel Literature

This essay aspires to examine the use of transliteration of some words and phrases from Arabic to English in travel literature books. This has been conducted by exploring the transliterated Arabic words and phrases, and comparing the different transliterations of the same words and phrases by different writers. It investigates the way that the travel writers employ in making plural nouns, the use of the definite article (Al) (ال), and Al-tashdid (the duplication of a letter). The conclusion drawn is that travel literature writers resort to transliteration for three reasons; one of the main reasons is that sometimes there is no one-to-one correspondence; the second main reason suggests that transliteration avoids the loss of meaning; and the third one stems from the fact that transliteration helps to find transculturation between cultures. The contributions of this essay would be of concern to scholars, who are interested in Arabic into English transliteration, specifically in English travel literature. According to the researchers’ knowledge, this essay can be considered a leading pioneer study in the field that deals with transliteration from Arabic into English in English travel literature.

A modification of the FRAD model for personal names in non-Roman languages

Purpose– The purpose of this paper is to propose a modification of the Functional Requirements for Authority Data (FRAD) model to accommodate names in non-Roman languages with diverse writing systems.Design/methodology/approach– The model modifies and clarifies the attributes and relationships regarding non-Roman languages of the current FRAD model, based on the definitions of transliteration, transcription, and Romanization in ISO 5127:2001. The modified model overcomes the problems inherent in the current FRAD model when handling writing systems in non-Roman languages.Findings– The proposed model clearly shows the hierarchy of Controlled Access Points (CAPs). CAPs are either based directly on names or derived from other CAPs. For name or person identification, a CAP and its derivations should be treated as a set. The proposed model also resolves ambiguity in the definition of the word transliteration in the current FRAD model.Originality/value– By establishing new relationships and amending the attributes of the FRAD model, the proposed model better expresses personal names in non-Roman languages as well as names in western languages. It also organizes complex writing systems of non-Roman languages. The proposed model could lead to an improved format for authority data and will facilitate international sharing of data.

메타 검색에서 외래어 질의 정제 효과

Foreign word transliterations are not consistently used in documents, which hinders retrieving some important relevant documents in exact term matching information retrieval systems. In this paper, a meta search method is proposed, which expands and refines relevant variant queries from an original input foreign word transliteration query to retrieve the more relevant documents. The method firstly expands a transliteration query to the variants using a statistical method. Secondly the method selects the valid variants: it queries each variant to the retrieval systems beforehand and checks the validity of each variant by counting the number of appearance of the variant in the retrieved document and calculating the similarity of the context of the variant. Experiment result showed that querying with the variants produced at the first step, which is a base method of the test, performed 38% in average F measure, and querying with the refined variants at the second step, which is a proposed method, significantly improved the performance to 81% in average F measure.

효과적인 외래어 이형태 생성을 위한 확률 문맥 의존 치환 방법

완전 일치 방법을 주로 사용하는 정보 검색 시스템에서 외래어 이형태를 검색할 수 있도록 위해서는 외래어 이형태를 자동 생성하는 전처리나 질의어 확장이 필요하다. 본 연구에서는 하나의 외래어가 입력되면, 이를 근거로 실제 사용될 만한 외래어 이형태들을 효과적으로 생성하기 위한 방법을 제안한다. 혼동 자소를 단순하게 치환하는 방법은 불필요한 이형태를 과도하게 생성하므로, 본 연구에서는 실제 문서에 사용된 외래어 이형태들로부터 혼동 패턴을 학습하고, 이를 확률로 계산하여 생성 순서를 조절하였다. 특히, 혼동 패턴에서 좌우문맥을 고려하고 지역 치환 확률과 전역 치환 확률을 계산하여 조기에 많이 사용하는 이형태를 생성하도록 하였다. KT SET 2.0에서 추출한 이형태 데이터에 대해 실험한 결과, 상위 20개의 생성으로도 평균 80% 이상 찾아내어 이 방법이 매우 효과적임을 보였다. An information retrieval system, using exact match, needs preprocessing or query expansion to generate transliteration variants in order to search foreign word transliteration variants in the documents. This paper proposes an effective method to generate other transliteration variants from a given transliteration. Because simple rewriting of confused characters produces too many false variants, the proposed method controls the generation priority by learning confusion patterns from real uses and calculating their probability. Especially, the left and right context of a pattern is considered, and local rewriting probability and global rewriting probability are calculated to produce more probable variants in earlier stage. The experimental result showed that the method was very effective by showing more than 80% recall with top 20 generations for a transliteration variants set collected from KT SET 2.0.

입말 표기를 이용한 영어 단어 검색

Users of searching Internet English dictionary sometimes do not know the correct spelling of the word in mind, but remember only its pronunciation. In order to help these users, we propose a method to retrieve English words effectively with a spoken word transliteration that is a Korean transliteration of English word pronunciation. We develop KONIX codes and transform a spoken word transliteration and English words into them. We then calculate the phonetic similarity between KONIX codes using edit distance and 2-gram methods. Experimental results show that the proposed method is very effective for retrieving English words with a spoken word transliteration.

New evidence for phonological processing during visual word recognition: the case of Arabic.

Lexical decision and naming were examined with words and pseudowords in literary Arabic and with transliterations of words in a Palestinian dialect that has no written form. Although the transliterations were visually unfamiliar, they were not easily rejected in lexical decision, and they were more slowly accepted in phonologically based lexical decision. Naming transliterations of spoken words was slower than naming of literary words and pseudowords. Apparently, phonological computation is mandatory for both lexical decision and naming. A large frequency effect in both lexical decision and naming suggests that addressed phonology is an option for familiar orthographic patterns. The frequency effect on processing transliterations indicated that lexical phonology is involved with prelexical phonological computation even if addressed phonology is not possible. These data support a combination between a cascade-type process, in which partial products of the grapheme-to-phoneme translation activate phonological units in the lexicon, and an interactive model, in which the activated lexical units feed back, shaping the prelexical phonological computation process.

The Origin and Development of the Burmese Composite Word (Mô Kwan:)

[Abbreviations of titles of books and works in this article are the same as those employed in The New Burmese-English Dictionary, pt. I, compiled by Stewart and Dunn. The transliteration of words taken from the Inscriptions of Burma (Old Burmese) follows the system devised by C. O. Blagden and Chas. Duroiselle (see Epigraphia Birmanica, vol. i, pt. i, pp. 6–12): that of words from other Burmese works is similar, with the addition of the tone-mark () and the symbol (^) representing the Burmese + .]There are few such words in the Burmese language as the composite word A Mô Kwan:. It has excited the curiosity and attention of Burmese scholars, and will always conjure up interesting reminiscences in the mind of Burmese historians. The word is about 700 years old and has undergone remarkable changes of form and meaning. (Amu Kwan, Amū Kwan)It has been established by Professor G. H. Luce that the origin of Mô Kwan: is Amu Kwan, which occurs in a Burmese inscription of the 13th century. During the reign of Narathihapati (1254–87), the last king of the Pagan Dynasty, “Saka era 628 (A.D. 1266), in the Pisyak (Vaisakhā) year, on Thursday”, the daughter of minister Singasū dedicated lands to a monastery and “informed the great and noble king (of her act of merit). The king thereupon poured out pure water and had the record of the deed placed in the archives (Amu Kwan tan e).” Again, “Saka era 633 (A.D. 1271) in the Āsin (Asvin) year, on Friday, the 10th of the waxing moon of the month of Tan Khū (April), when the honourable Lady (Queen) Phwa Jaw went to the Ornamented Abode (Kwan Prok), she showed the list of her dedications to the great king; and the king had it placed in the archives (Amū Kwan tan e’).”