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SRELS Journal of Information Management
One solution would be to test each pair of characters as it is read into machine from punched paper tape, punched cards, etc., and to replace each character with non-standard value. ... The third is to add new letters but this may be difficult in many methods of catalogue production in public libraries. ...
Lecture Notes in Computer Science
We also compare our results with those of a state-of-the-art Machine Transliteration system. ... Instead of "generating" the transliterations using a Machine Transliteration system, we "mine" them, using a transliteration similarity model, from the top CLIR results for the query. ... Using this hypothesis, she proposed a measure of the productivity of the context of a word and used it to compile a bilingual translation lexicon from non-parallel English-Chinese corpora  . ...doi:10.1007/978-3-642-00958-7_39 fatcat:dq4oy5xr2nh4racq7tomuqmy4i
We model transliteration mining as an interpolation of transliteration and non-transliteration sub-models. We evaluate on NEWS 2010 shared task data and on parallel corpora with competitive results. ... We propose a novel model to automatically extract transliteration pairs from parallel corpora. ... Alexander Fraser was funded by Deutsche Forschungsgemeinschaft grant Models of Morphosyntax for Statistical Machine Translation. ...doi:10.1162/coli_a_00286 fatcat:vbwx3fgku5bfhns7gpmuzfero4
National Union Catalog
London ;1964, Machines and tooling. Melton Mowbray, Eng., Production Engineering Research Association of Great Britain. v. illus. 28cm. monthly. ... Washington, D,C,, 1962, 6, ;5)p. 28cm, (Its Memorandum, T-15) Caption title, Reproduced from typewritten copy. 1, Income tax-U,S, 2, Non-wage payments- U.S, L Title, MH-L NUC65-19336 Machinery and Allied ...
The interface is targeted for the non-native Japanese speaker and a variety of tools are provided to help formulate Japanese queries. ... Query Generation Features for the Non-Native Speaker One of our primary considerations during the design of the JFDF was to make it easy to operate for the non-native Japanese speakers, which we believe ... They suggested a number of improvements in the man-machine interface design and requested several additional features. ...doi:10.3115/1119149.1119162 dblp:conf/tipster/Mettler93 fatcat:cz5fekigbnfajglvsbaq6gbba4
Transliteration plays a very significant role in machine translation, which has many applications such as cross-lingual information retrieval, communication, question-answering etc. ... If the word to be transliterated is not found in CMU Pronouncing dictionary, Module-II is used. ... Thus, transliteration plays a very important role in translation. Machine Transliteration is automatic transliteration done by machine without human intervention. ...doi:10.26483/ijarcs.v8i8.4801 fatcat:n5ziirgyrrfmrjyf3imh4oa6vi
In this article, we propose a Machine Learning model with the combination of English Urdu word transliteration which will show whether the English news article is similar to the Urdu news article or not ... and Urdu news articles based on transliteration. ... Figure 3: Dictionary based approach Transliteration can be considered as a sub task of machine translation two main type of transliterations are forward transliteration and backward transliteration [10 ...arXiv:2206.11860v1 fatcat:plig3xl73zcefkprw7jpsrrvee
We start with a definition and discussion of the different types of transliteration followed by various deterministic and non-deterministic approaches used to tackle transliteration-related issues in machine ... A substantial proportion of this content is transliterated data. To leverage this huge information repository, there is a matching effort to process transliterated text. ... Sato  proposed a non-productive machine transliteration for English-Japanese NE transliteration. ...doi:10.1007/s12046-018-0828-8 fatcat:dg3gwugmqrfevnzu3deuk5w67i
coverage censor ship be machines and the collection of the next seventeen lectures to appear a quarter of a century hence are reminded of the annual printings in pam phlet format. ... that equally capable speakers will con tinue the series with other topics deserving book bestsellet developments tech niques Impatic nt readers looking forward to such as distribution *k design and book production ...
The proposed method bootstraps statistical machine transliteration using the extracted transliteration fragments to train transliteration models. ... The proposed method extends a many-to-many Bayesian character alignment method by distinguishing transliteration (signal) parts from non-transliteration (noise) parts. ... part (signal), and the non-transliteration part at the end (noiseE). ...doi:10.5715/jnlp.21.1107 fatcat:tbpswyqsy5dclmjzrylzh5ghvi
For corpus validation, shallow machine learning algorithms such as Support Vectors Machine (SVM) and Naive Bays (NB) are used. ... In the proposed approach, Arabizi messages are first transliterated into Arabic. ... Other dominant problems include the non standard romanization (called Arabizi) that Arabic speakers often use in social media. ...doi:10.18653/v1/w18-6249 dblp:conf/wassa/GuellilAABHH18 fatcat:ghyg3iudfrf6vofpz4aqnlx4he
SN Applied Sciences
The tasks like machine translation, Named Entity Recognition, Sentiment Analysis and Parts-Of-Speech tagging are reviewed with respect to Rule, Statistical and Neural based approaches. ... Machine transliteration In natural language processing, machine transliteration plays a vital role in applications like cross-language machine translation, named entity recognition, Fig. 1 Generic model ... Machine transliteration Early in 1994, Arbabi worked on Arabic-English language transliteration using phoneme based model  . ...doi:10.1007/s42452-020-2983-x fatcat:e3u5r5qo7ngapj5mbiwit7qlwi
Transliteration is one module that may produce such specialized output. ... In this paper, as an example, we build a specialized Urdu transliteration module and integrate its output into an Urdu-English MT system. ... Semantically-targeted transliteration We trained two transliteration systems, one for person names and one for all other semantic types (including non-names). ...doi:10.2478/v10108-010-0009-3 fatcat:5uvklgkg7vcmjjqdwpr2dnlbyq
In this paper, we present Sangam, a Perso-Arabic to Indic script machine transliteration system, which can convert with high accuracy text written in Perso-Arabic script to one of the Indic script sharing ... Thus there is a dire need for development transliteration tools for conversion between Perso-Arabic and Indic scripts. ... If there is no word with non-zero probability, then the word is inspected for presence of merged words which can be transliterated to non empty sets of words in S2 words. ...dblp:conf/icon-nlp/LehalS14 fatcat:5vdmblgfnfftbbeiikjx22a6se
This paper provides the thorough survey on machine transliteration models and machine learning approaches used for machine transliteration over the period of more than two decades for internationally used ... Support of local languages can be given in all internet based applications by means of Machine Transliteration and Machine Translation. ... They described a method about transliteration production using the several machine transliteration models and transliteration ranking with web data and relevance scores given by each transliteration model ...doi:10.5121/ijnlc.2015.4202 fatcat:kegqa5k4abahvbno2setnkxwtq
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