Rule-Based Translation of Spanish Verb-Noun Combinations into Basque

Iñurrieta, Uxoa; Aduriz, Itziar; Ilarraza, Arantza Díaz de; Labaka, Gorka; Sarasola, Kepa

doi:10.18653/v1/w17-1720

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…In previous work, in-depth lexical and morphosyntactic information about verb+noun MWEs (VNMWEs) was proven to have a positive impact both in identification [7] and in MT [8]. Detailed data was manually provided in these experiments, and the results obtained using a controlled set of sentences were promising.…”

Section: Introductionmentioning

confidence: 92%

“…Both can benefit from identifying MWEs, since properly identifying MWEs can be helpful to solve ambiguities when parsing, as well as to select the correct translation for a given word combination. For instance, if we consider the words look and up, distinguishing the occurrences in examples (8) and (9) would help both applications: on the one hand, it would be easier for the parser to tag the words after look up as direct object in the first sentence but to treat them as part of a prepositional phrase in the second one; on the other hand, MT systems need to know when to translate the words non-compositionally (example 8) and when compositionally (example 9). (8).…”

Section: Related Workmentioning

confidence: 99%

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Learning about phraseology from corpora: A linguistically motivated approach for Multiword Expression identification

et al. 2020

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Multiword Expressions (MWEs) are idiosyncratic combinations of words which pose important challenges to Natural Language Processing. Some kinds of MWEs, such as verbal ones, are particularly hard to identify in corpora, due to their high degree of morphosyntactic flexibility. This paper describes a linguistically motivated method to gather detailed information about verb+noun MWEs (VNMWEs) from corpora. Although the main focus of this study is Spanish, the method is easily adaptable to other languages. Monolingual and parallel corpora are used as input, and data about the morphosyntactic variability of VNMWEs is extracted. This information is then tested in an identification task, obtaining an F score of 0.52, which is considerably higher than related work.

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Section: Introductionmentioning

confidence: 92%

Section: Related Workmentioning

confidence: 99%

Learning about phraseology from corpora: A linguistically motivated approach for Multiword Expression identification

et al. 2020

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“…The rule-based translation is a strategy that analyses the word's input until a group of words (sentence) [14]. The translation analysis finds specific combinations of words or signs (blocks) that generate a sign.…”

Section: Nlp With Rule-based and Statistical Translationmentioning

confidence: 99%

Adaptive Language Processing Unit for Malaysian Sign Language Synthesizer

Maarif

Gunawan

Akmeliawati

2021

IJRA

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Language Processing Unit (LPU) is a system built to process text-based data to comply with the rules of sign language grammar. This system was developed as an important part of the sign language synthesizer system. Sign language (SL) uses different grammatical rules from the spoken/verbal language, which only involves the important words that Hearing/Impaired Speech people can understand. Therefore, it needs word classification by LPU to determine grammatically processed sentences for the sign language synthesizer. However, the existing language processing unit in SL synthesizers suffers time lagging and complexity problems, resulting in high processing time. The two features, i.e., the computational time and success rate, become trade-offs which means the processing time becomes longer to achieve a higher success rate. This paper proposes an adaptive Language Processing Unit (LPU) that allows processing the words from spoken words to Malaysian SL grammatical rule that results in relatively fast processing time and a good success rate. It involves n-grams, NLP, and Hidden Markov Models (HMM)/Bayesian Networks as the classifier to process the text-based input. As a result, the proposed LPU system has successfully provided an efficient (fast) processing time and a good success rate compared to LPU with other edit distances (Mahalanobis, Levensthein, and Soundex). The system has been tested on 130 text-input sentences with several words ranging from 3 to 10 words. Results showed that the proposed LPU could achieve around 1.497ms processing time with an average success rate of 84.23% for a maximum of ten-word sentences.

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“…Euskara bezalako hizkuntza txikietarako, berriz, egokiagoak dira bigarren multzokoak, corpus paraleloak txiki samarrak baitira estatistikaren bidez kalitatezko itzulpen automatikoak lortzeko. Bestalde, erregeletan oinarritutako sistemek arau linguistikoak eta hiztegi elebidun orokorrak izaten dituzte oinarrian, eta horiek bakarrik ez dira nahikoa UFak zuzen itzultzeko; emaitza txukunak lortu ahal izateko, behar-beharrezkoa dute UFen inguruko informazio gehigarria (Wehrli et al, 2009;Iñurrieta et al, 2017).…”

Section: Laburpenaunclassified

II. Ikergazte. Nazioarteko ikerketa euskaraz. Kongresuko artikulu bilduma. Giza Zientziak eta Artea

2017

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Ekarpen honek laburbiltzen duen ikerketaren helburua germaniar hizkuntza guztiek amankomunean daukaten arbasoaren hitz-ordena berreraikitzea da. Horretarako orain arte egin diren saiakerekin zerikusia duen eta aldi berean berritzailea den hurbilpena egiten du autoreak: Adarkatze Norabide Teorian (Branching Direction Theory) (Dryer, 1992) oinarritutako ikerketa da. Teoria hau hitzordenaren unibertsal tipologikoen inguruan egindako ikerketaren ondorioa da. Gainera, erabiltzen diren datuetatik asko oso gutxi aztertutako germaniar hizkuntza batetik atereak dira, sajoiera zaharretik, hain zuzen ere. Emaitzek orain arteko ikerketaren aurkikuntzak hobetzen dituzte.Hitz gakoak: aitzingermanikoa, sajoiera zaharra, Adarkatze Norabide Teoria, unibertsal tipologikoak, hitz-ordena

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Rule-Based Translation of Spanish Verb-Noun Combinations into Basque

Cited by 3 publications

References 8 publications

Learning about phraseology from corpora: A linguistically motivated approach for Multiword Expression identification

Learning about phraseology from corpora: A linguistically motivated approach for Multiword Expression identification

Adaptive Language Processing Unit for Malaysian Sign Language Synthesizer

II. Ikergazte. Nazioarteko ikerketa euskaraz. Kongresuko artikulu bilduma. Giza Zientziak eta Artea

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