DOCSLIB.ORG

Transfer Pivot Translation in Apertium Shardul Chiplunkar for Google Code-In 2016

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Transfer Pivot Translation in Apertium Shardul Chiplunkar for Google Code-In 2016 Transfer pivot translation in Apertium Shardul Chiplunkar for Google Code-In 2016 Keywords: rule-based machine translation (RBMT), pivot translation, Apertium, ScaleMT Abtract source and final target languages. For example2, Apertium does not have a direct translation system Rule-based machine translation (RBMT) systems from English (eng) to Portuguese (por), but with built with the Apertium platform produce high pivot translation, Spanish (spa) and Catalan (cat) quality translations, given extensive bilingual dic- can be used to translate tionaries and shallow-transfer lexical and structural eng → spa → por rules [1]. I implemented transfer pivot translation— eng → spa → cat → por translation using one or more languages as interme- diate (‘pivot’) translation targets without specially etc. as required. As Apertium is a rule-based plat- modifying the translations in the process (‘trans- form, transfer pivot translation—where no special fer’)—to extend the scope of possible translations modifications are made at any intermediate step—is with minimal additional effort. This paper discusses the easiest way to do this, as opposed to other com- the details of this work and its future implementa- mon approaches to pivot translation which involve tion prospects across Apertium’s API, web interface, statistical approaches. and IRC bot. I implemented transfer pivot translation in Aper- tium’s web API ‘apertium-apy’3 which is modeled on ScaleMT [3], and in the web interface ‘apertium- Introduction html-tools’4. The ScaleMT infrastructure uses parallel asynchronous pipelines for each translation Apertium is a free and open-source RBMT plat- pair, so the challenge was to ensure that a text being form which can build RBMT systems from bilingual translated is correctly passed through multiple such dictionaries and shallow transfer rules for lexical pipelines without slowing down the system. On the selection and structural transfer [1]. Apertium it- other hand, the challenge for the web interface was self has extensively developed some such systems, to create an intuitive interface to view and select such as among various Romance languages ([2] de- from possible pivot translations. I also developed scribes initial work), along with community-driven an interface to pivot translation for Apertium’s IRC systems such as for languages of the Turkic fam- bot begiak. 1 ily . Apart from the morphological analyzer/gener- The following sections of this paper describe, in ator and part-of-speech tagger that each language order, details of contributions to apertium-apy, requires, each language pair requires a bilingual apertium-html-tools, begiak, and possibilities dictionary to find equivalents of lexical forms, lex- for future work. ical selection rules to disambiguate analyses, and shallow-transfer rules to transfer syntactical struc- tures. While this produces high-quality translation Web API systems, these requirements are difficult to fulfill as apertium-apy is modeled after the ScaleMT ar- they must most often be written manually. chitecture for efficiency and scalability [3]. Each Pivot translation is a technique that can expand translation pair, e.g. eng → spa, has an associ- the scope of possible translations using one or more ated pipeline running independently of all other intermediate (‘pivot’) target languages between the 2This will be a running example throughout this paper. 1Outlined at http://wiki.apertium.org/wiki/ 3https://github.com/goavki/apertium-apy Apertium_Turkic#Publications. 4https://github.com/goavki/apertium-html-tools 1 pipelines. Pipelines initialize all required resour- ces when started and maintain them thereafter. Pipelines are started and stopped on various servers by a central router based on the quantity of re- quests and server load. The router also provides an outward-facing REST API with endpoints for func- tions such as translation, morphological analysis and generation, listing available pairs, calculating translation coverage, etc. Pivot translation requires passing the source lan- guage text into one of these pipelines, waiting for its output, then passing it into another pipeline, and so on until the text is obtained in the target lan- guage. However, as the pipelines run independently in parallel, care had to be taken to perform the entire operation asynchronously so as to not block the entire system or slow down individual pipelines with a pivot translation request. The crucial ele- ment that I wrote was a coreduce routine5, which takes a list of functions and the initial arguments as its arguments and asynchronously applies each Figure 1: Target languages for eng with and without function to the result of the previous function. pivot translation I developed two API endpoints6 to access this functionality. The first was translateChain which paths described in the previous paragraph. For ex- takes a list of languages, e.g. eng|spa|por, and a ample, Figure 1 shows that with eng as the source text in the source language eng, and gives the text language, the only direct translation targets are after performing the eng → spa → por translation. spa, cat, and a couple others, but the pivot targets It would be convenient if apertium-apy auto- include por too. matically chose pivot translation languages if only the source and target were provided. Thus, I im- plemented Dijkstra’s algorithm for finding shortest Web Interface paths between all possible language pairs on a par- ticular server, which are found and recorded by Preliminary changes to apertium-html-tools for the server at start-up for future use. Dijkstra’s pivot translation are shown in Figure 1. A check- algorithm was used in particular because of the pos- box was added to enable pivot translation along sibility of using weights for each direct translation with a link explaining what pivot translation is pair—currently, the weights are all equal and have (termed “multi-step translation” so that the func- no bearing on the path chosen—which is discussed tion is clearer from the name). If this checkbox in the ‘Summary and Future Work’ section. was checked, the dropdown and target language The second API endpoint was listPairs which selection bar, which would otherwise only enable already had modes to list direct pairs, analyzers/gen- direct targets, enabled targets that would require erators, and taggers. I added a mode to take a pivot translation to achieve. To actually perform source language and give all possible target lan- the pivot translation, apertium-html-tools would guages that could be obtained through pivot trans- use the API described previously. lation. This mode merely accesses the list of shortest However, this approach has a few shortcomings: it does not display the pivot translation path for 5Line 251 in in translation.py https://github.com/ a selected target language, or even its length for a goavki/apertium-apy/pull/43/files 6Documented at http://wiki.apertium.org/wiki/ rough measure of accuracy, and it does not allow User:Shardulc. the user to select custom pivot translation paths. I 2 is built using the force-directed graph provisions of the powerful JavaScript visualization library D3.js7. This means that the nodes repel each other and the arrows tend to maintain their length, while the source and target language nodes can be moved around by the user as wanted, making the whole interface dynamic and intuitive. Care was taken to ensure that the interface functions as expected on mobile devices as well. IRC Bot Apertium’s IRC bot begiak could already obtain direct translations using apertium-apy, so adding provisions for pivot translations—of course, per- formed on the API side—was not a difficult matter. However, I discovered a large number of malfunc- tioning or broken API-accessing commands in the process, and rewrote almost the entire module8 so that it could provide access to most, if not all, apertium-apy functions. In order to aid future development, I added docu- mentation for the new code and bot commands, and also created extensive unit tests9 for the module. Future Work Figure 2: Unselected pivot translation graph for eng → por and the same graph upon selecting cat An important possibility for future development is and spa nodes using the quality of direct translations to decide pivot translation paths. Absolute quality evalua- tions for a direct pair are not available and may built a graphical interface to remedy this which is not be practical, but estimates would make a great shown in Figure 2. difference for pivot translation. These estimates The user is presented with a directed graph of could be used as weights in the implementation of possible direct translations that can be used as pivot Dijkstra’s algorithm mentioned in the ‘Web API’ languages for the eng → por translation. The user section, could be served over the API, and could clicks to select pivot languages cat and spa, rep- be used to provide a visual representation of the resented as nodes, which then turn blue; all direct quality of direct translations and pivot paths in the translation pairs, represented as arrows, which are graphical interface in the ‘Web Interface’ section. part of some pivot path involving the selected lan- It is also possible that the weights are adjusted guages also turn blue. (In the figure, there is no depending on the text to be translated after deter- direct translation pair that does not involve spa mining translation coverage for that specific text, or cat, so there are no gray arrows.) If any paths but this appears to be very inefficient. involving only the selected languages exist, the ar- rows for the entire path turn green and the desired 7https://d3js.org/ 8 path can be selected from a ‘Valid Paths’ list. https://github.com/goavki/phenny/blob/master/ modules/apy.py The graph shown is already complex and needs 9https://github.com/goavki/phenny/blob/master/ to be movable and spread out to be of use.
Load more

Recommended publications
  • "Machine Translation Evaluation Through Post-Editing…"
    ©inTRAlinea & Anna Fernández Torné (2016). "Machine translation evaluation through post-editing measures in audio description", inTRAlinea Vol. 18. Permanent URL: http://www.intralinea.org/archive/article/2200 inTRAlinea [ISSN 1827-000X] is the online translation journal of the Department of Interpreting and Translation (DIT) of the University of Bologna, Italy. This printout was generated directly from the online version of this article and can be freely distributed under the following Creative Commons License. Machine translation evaluation through post-editing measures in audio description By Anna Fernández Torné (Universitat Autònoma de Barcelona, Spain) Abstract & Keywords English: The number of accessible audiovisual products and the pace at which audiovisual content is made accessible need to be increased, reducing costs whenever possible. The implementation of different technologies which are already available in the translation field, specifically machine translation technologies, could help reach this goal in audio description for the blind and partially sighted. Measuring machine translation quality is essential when selecting the most appropriate machine translation engine to be implemented in the audio description field for the English-Catalan language combination. Automatic metrics and human assessments are often used for this purpose in any specific domain and language pair. This article proposes a methodology based on both objective and subjective measures for the evaluation of five different and free online machine translation systems. Their raw machine translation outputs and the post-editing effort that is involved are assessed using eight different scores. Results show that there are clear quality differences among the systems assessed and that one of them is the best rated in six out of the eight evaluation measures used.
    [Show full text]
  • A Finite-State Morphological Analyser for Sindhi
    A Finite-State Morphological Analyser for Sindhi Raveesh Motlani1, Francis M. Tyers2 and Dipti M. Sharma1 1FC Kohli Center on Intelligent Systems (KCIS), International Institute of Information Technology Hyderabad, Telangana, India 2 HSL-fakultehta, UiT Norgga árktalaš universitehta N-9019 Romsa [email protected], [email protected], [email protected] Abstract Morphological analysis is a fundamental task in natural-language processing, which is used in other NLP applications such as part-of-speech tagging, syntactic parsing, information retrieval, machine translation, etc. In this paper, we present our work on the development of free/open-source finite-state morphological analyser for Sindhi. We have used Apertium’s lttoolbox as our finite-state toolkit to implement the transducer. The system is developed using a paradigm-based approach, wherein a paradigm defines all the word forms and their morphological features for a given stem (lemma). We have evaluated our system on the Sindhi Wikipedia, which is a freely-available large corpus of Sindhi and achieved a reasonable coverage of about 81% and a precision of over 97%. Keywords: Sindhi, Morphological Analysis, Finite-State Machines [ɓ] ٻ [ɲ] ڃ [ŋ] ڱ Introduction .1 [ɠ] [ʄ] [bʱ] ڀ ڄ ڳ Morphology describes the internal structure of words in a [dʱ] ڌ [cʰ] ڇ [k] ڪ language. A morphological analysis of a word involves [ɗ] ڏ [ʈʰ] ٺ [ɳ] ڻ ,describing one or more of its properties such as: gender [ɖ] ڊ [ʈ] ٽ [pʰ] ڦ number, person, case, lexical category, etc. Morphological [ɖʱ] ڍ [tʰ] ٿ [ɽ] ڙ -analysis of a word thus becomes a fundamental and cru cial task in natural-language processing for any language.
    [Show full text]
  • Multi-Script Morphological Transducers and Transcribers for Seven Turkic
    Multi-script morphological transducers and transcribers for seven Turkic languages Jonathan Washington, Francis Tyers, Oğuzhan Kuyrukçu Swarthmore College, Indiana University / Высшая Школа Экономики, Boğaziçi Üniversitesi [email protected], [email protected], [email protected] This paper describes ongoing work to augment morphological transducers for seven Turkic languages with support for multiple scripts each, as well as respective IPA transcription systems. Evaluation demonstrates that our approach yields coverage equivalent to or not much lower than that of the base transducers. Background. A morphological transducer converts between form and analysis, e.g. алмалардан ↔ алма<n><pl> <abl>, where the form-to-analysis task is termed “morphological analysis” and the analysis-to-form task is termed “morphological generation”. Existing Free/Open-Source morphological transducers for Turkic languages (Wash- ington et al. 2020) are implemented in only one orthography, despite a number of the languages being currently written in two or more orthographies, or having a large body of text written in an orthography that was recently switched away from. This paper builds on work in which Cyrillic support was added to a transducer for Crimean Tatar which had been implemented in the Latin script (Tyers et al. 2019). We leverage morphological transducers for Kazakh (imple- mented in the Cyrillic script), Kyrgyz (Cyrillic), Turkmen (Latin), Qaraqalpaq (Latin), Uzbek (Latin), and Uyghur (Perso-Arabic), and add support for analysis and generation in additional scripts that are currently or have recently been used for the languages. Specifically, we add Cyrillic support to Turkmen, Qaraqalpaq, Uzbek, and Uyghur transducers; Perso-Arabic support to the Kazakh and Kyrgyz transducers; Latin script to the Kazakh and Uyghur transducers; and IPA support to all of them.
    [Show full text]
  • Developing Morph-Analyzer for Urdu Using Apertium: Some Issues
    Developing Morph-Analyzer for Urdu Using Apertium: Some issues Shahid Mushataq Bhat [email protected] Linguistic Data Consortium for Indian Languages (LDCIL) CIIL, Mysore Content: Introduction Morphological features of Urdu Apertium (LT-toolbox): Some background Computing Noun-morphology using LT Toolbox Split-Orthography of Urdu Conclusion Introduction: Automatic morphological analysis is the fundamental task in NLP that can be employed in enhancing the accuracy of POS-taggers, Chunkers, Parsers and Information retrieval systems. Computational morphology models the internal structure of words i-e the way; words are built out of minimal units called morphemes. Most of natural languages construct words by concatenating morphemes together in strict orders. Such Concatenative morphotactics is highly productive, particularly, in agglutinative languages like Tamil, Kannada, Manipuri, etc but in some languages like Hebrew and Arabic (Semitic languages) infixation is the main morphological operation (instead of concatenation), constituting Non-Concatenative (Templatic or Root & Pattern) morphology. Continues …… Beyond this Concatenative and Non-Concatenative polarity, Urdu nouns (unlike nouns of other Indian Languages) show the interplay of both types of morphologies. So, morphological structure of Urdu like Tagalog (a language of Philippines) can’t be computed adequately unless dual nature of its morphology is not taken into account. “The morphotactic limitations of the traditional implementations are the direct result of relying solely
    [Show full text]
  • Estudio Comparativo De Tres
    TRABAJO DE FIN DE GRADO FACULTAD DE CIENCIAS HUMANAS Y SOCIALES GRADO EN TRADUCCIÓN E INTERPRETACIÓN ESTUDIO COMPARATIVO DE TRES TRADUCTORES AUTOMÁTICOS EN LÍNEA : DEEP L, YANDEX Y APERTIUM Autora: Mónica Adán Soriano Directora: Profesora Mª Luisa Romana García Madrid, junio 2019 Resumen : Este trabajo tiene la finalidad de comparar traductores automáticos en línea para así determinar cuál es el traductor más avanzado para un texto técnico. Para ello, primero, habrá un análisis de la evolución histórica de la traducción automática y sus usos, así como los programas desarrollados para ello. Se explicarán además los diferentes sistemas de traducción automática que existen y cómo funcionan. En la parte experimental, se escogerá un texto de carácter técnico en español y de oraciones que supongan un reto para un traductor y se procesará en los tres traductores automáticos escogidos según su modalidad para realizar una traducción al inglés. Una vez obtenidas las respuestas, se analizarán los errores cometidos por los traductores automáticos, concluyendo así con los errores más comunes y el mejor traductor automático en línea así como los usos que se le pueden dar. Palabras clave: traducción automática, sistemas basados en estadística, Yandex, sistemas neuronales, DeepL, sistemas basados en reglas, Apertium, errores de traducción. Abstract : The aim of this dissertation is to do a comparative research analysis on three automatic translation programs available on the internet to determine which is the most advanced for a technical text. First, we will do an analysis on the historic evolution of automatic translation and the several uses given to it, as well as the diverse programs developed for it and how they work.
    [Show full text]
  • The Apertium Bilingual Dictionaries on the Web of Data
    Undefined 0 (0) 1 1 IOS Press The Apertium Bilingual Dictionaries on the Web of Data Jorge Gracia a;∗, Marta Villegas b, Asunción Gómez-Pérez a, and Núria Bel b, a Ontology Engineering Group, Universidad Politécnica de Madrid Campus de Montegancedo s/n Boadilla del Monte 28660 Madrid. Spain E-mail: {jgracia,asun}@fi.upm.es b Institut Universitari Linguistica Aplicada, Universitat Pompeu Fabra Roc Boronat, 138 08018 Barcelona. Spain E-mail: {marta.villegas,nuria.bel}@upf.edu Abstract. Bilingual electronic dictionaries contain collections of lexical entries in two languages, with explicitly declared trans- lation relations between such entries. Nevertheless, they are typically developed in isolation, in their own formats and accessible through proprietary APIs. In this paper we propose the use of Semantic Web techniques to make translations available on the Web to be consumed by other semantic enabled resources in a direct manner, based on standard languages and query means. In particular, we describe the conversion of the Apertium family of bilingual dictionaries and lexicons into RDF (Resource Descrip- tion Framework) and how their data have been made accessible on the Web as linked data. As result, all the converted dictionaries (many of them covering under-resourced languages) are connected among them and can be easily traversed from one to another to obtain, for instance, translations between language pairs not originally connected in any of the original dictionaries. Keywords: linguistic linked data, multilingualism, Apertium, bilingual dictionaries, lexicons, lemon, translation 1. Introduction In this article we will focus on the case of electronic bilingual dictionaries as a particular type of languages The publication of bilingual and multilingual lan- resources.
    [Show full text]
  • Apertium: a Free/Open-Source Platform for Machine Translation and Basic Language Technology Mikel L
    Apertium: A free/open-source platform for machine translation and basic language technology www.apertium.org Mikel L. Forcada1 Francis M. Tyers2,3 1Departament de Llenguatges i Sistemes Inform`atics, Universitat d’Alacant, E-03690 Sant Vicent del Raspeig (Spain) 2Department of Linguistics, Indiana University, IN 47405, U.S.A. 3 School of Linguistics, Higher School of Economics, Moscow, Russia [email protected], [email protected] Apertium components Languages and language pairs Since 2005, Apertium provides: 1. A free/open-source, modular, shallow/deep transfer, language-independent Language data is encoded mostly in XML, but some language pairs contain data machine translation engine with: text format management, finite-state lexical encoded in other text-based formats. processing, statistical and constraint-based lexical disambiguation, Stable language pairs (bilingual data) include: discontiguous multi-word assembly and disassembly, anaphora resolution, and shallow structural transfer based on finite-state pattern matching. afr hbs bel crh kaz ind mlt pol urd 2. Free/open-source linguistic data in well-specified XML formats for a variety of languages and language pairs nld bre epo eus cym mkd slv isl rus tur tat zsm ara szl hin 3. Free/open-source tools: compilers to turn linguistic data into an efficient fra oci eng bul swe ukr form used by the engine and software to learn disambiguation or translation spa dan rules from corpora. Interfaces with external technologies: HFST (for some morphologically-rich arg ast por ron sme nno languages), VISL CG-3 (for rule-based lexical disambiguation). cat glg nob Machine translation but not only! ita srd For many of these languages, there are separate monolingual packages.
    [Show full text]
  • A Rule-Based Shallow-Transfer Machine Translation System for Scots and English
    A Rule-based Shallow-transfer Machine Translation System for Scots and English Gavin Abercrombie [email protected] Abstract An open-source rule-based machine translation system is developed for Scots, a low-resourced minor language closely related to English and spoken in Scotland and Ireland. By concentrating on translation for assimilation (gist comprehension) from Scots to English, it is proposed that the development of dictionaries designed to be used within the Apertium platform will be sufficient to produce translations that improve non-Scots speakers understanding of the language. Mono- and bilingual Scots dictionaries are constructed using lexical items gathered from a variety of resources across several domains. Although the primary goal of this project is translation for gisting, the system is evaluated for both assimilation and dissemination (publication-ready translations). A variety of evaluation methods are used, including a cloze test undertaken by human volunteers. While evaluation results are comparable to, and in some cases superior to, those of other language pairs within the Apertium platform, room for improvement is identified in several areas of the system. Keywords: Scots, machine translation, assimilation 1. Introduction (‘what did he do that for’). There are also notable differ- The Scots language is spoken by over 1.5 million people ences to English in negation e.g. huvnae (‘have not’), din- in Scotland1 and a further 140,000 in Ireland,2 but is low- nae (‘do not’), and the double modal e.g. he’ll can dae that resourced in terms of technology - as far as I am aware there (‘he’ll be able to do that’) (Beal, 1997).
    [Show full text]
  • Apertium-Icenlp: a Rule-Based Icelandic to English Machine Translation System
    Apertium-IceNLP: A rule-based Icelandic to English machine translation system Martha Dís Brandt, Hrafn Loftsson, Francis M. Tyers Hlynur Sigurþórsson School of Computer Science Dept. Lleng. i. Sist. Inform. Reykjavik University Universitat d’Alacant IS-101 Reykjavik, Iceland E-03071 Alacant, Spain {marthab08,hrafn,hlynurs06}@ru.is [email protected] Abstract translate between the source language (SL) and the target language (TL). We describe the development of a pro- SMT has many advantages, e.g. it is data-driven, totype of an open source rule-based language independent, does not need linguistic ex- Icelandic English MT system, based on perts, and prototypes of new systems can by built → the Apertium MT framework and IceNLP, quickly and at a low cost. On the other hand, the a natural language processing toolkit for need for parallel corpora as training data in SMT Icelandic. Our system, Apertium-IceNLP, is also its main disadvantage, because such corpora is the first system in which the whole are not available for a myriad of languages, espe- morphological and tagging component of cially the so-called less-resourced languages, i.e. Apertium is replaced by modules from languages for which few, if any, natural language an external system. Evaluation shows processing (NLP) resources are available. When that the word error rate and the position- there is a lack of parallel corpora, other machine independent word error rate for our pro- translation (MT) methods, such as rule-based MT, totype is 50.6% and 40.8%, respectively. e.g. Apertium (Forcada et al., 2009), may be used As expected, this is higher than the corre- to create MT systems.
    [Show full text]
  • Proceedings of the 21St Annual Conference of the European Association for Machine Translation
    Proceedings of the 21st Annual Conference of the European Association for Machine Translation 28{30 May 2018 Universitat d'Alacant Alacant, Spain Edited by Juan Antonio P´erez-Ortiz Felipe S´anchez-Mart´ınez Miquel Espl`a-Gomis Maja Popovi´c Celia Rico Andr´eMartins Joachim Van den Bogaert Mikel L. Forcada Organised by research group The papers published in this proceedings are |unless indicated otherwise| covered by the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 International (CC-BY-ND 3.0). You may copy, distribute, and transmit the work, provided that you attribute it (au- thorship, proceedings, publisher) in the manner specified by the author(s) or licensor(s), and that you do not use it for commercial purposes. The full text of the licence may be found at https://creativecommons.org/licenses/by-nc-nd/3.0/deed.en. c 2018 The authors ISBN: 978-84-09-01901-4 Rule-based machine translation from Kazakh to Turkish Sevilay Bayatli Sefer Kurnaz Dept. Elec. and Computer Engineering Dept. Elec. and Computer Engineering Altınbaş Üniversitesi Altınbaş Üniversitesi [email protected] [email protected] Ilnar Salimzianov Jonathan North Washington Francis M. Tyers School of Science and Technology Linguistics Deptartment School of Linguistics Nazarbayev University Swarthmore College Higher School of Economics [email protected] [email protected] [email protected] Abstract all the dictionary entries and transfer rules. Con- versely, in a corpus-based/statistical MT approach This paper presents a shallow-transfer ma- (Koehn, 2010), no such effort is required as the sys- chine translation (MT) system for translat- tem can be automatically built from parallel corpora ing from Kazakh to Turkish.
    [Show full text]
  • Apertium: a Rule-Based Machine Translation Platform
    Apertium: A rule-based machine translation platform Francis M. Tyers HSL-fakultehta UiT Norgga árktalaš universitehta 9018 Romsa (Norway) 28th September 2014 1 / 41 Outline Introduction Design Development Status Teaching Courses Google Summer of Code Google Code-in Research New language pairs Applying unsupervised methods Hybrid systems Future work and challenges Challenges Plans Collaboration 1 / 41 History I 2004 — Spain gets a new government which launches a call for proposals to build machine translation systems for the languages of Spain I The Universitat d’Alacant (UA), in consortium with EHU, UPC, UVigo, Eleka, Elhuyar (Basque Country) and Imaxin (Galicia) get funded to develop two MT systems: I Apertium: Spanish–Catalan, Spanish–Galician I Matxin: Spanish!Basque I Apertium was not built from scratch, but was rather a rewrite of two existing closed-source systems which had been built by UA 2 / 41 Focus I Marginalised: Languages which are on the periphery either societally or technologically (from Breton to Bengali). I Lesser-resourced: Languages for which few free/open-source language resources exist. I Closely-related: Languages which are suited to shallow-transfer machine translation. 3 / 41 Translation philosophy I Build on word-for-word translation I Avoid complex linguistic formalisms I We like saying “only secondary-school linguistics required”1 I Intermediate representation based on morphological information I Transformer-style systems I Analyse the source language (SL), then I Apply rules to ‘transform’ the SL to the TL 1Otte, P. and Tyers, F. (2011) “Rapid rule-based machine translation between Dutch and Afrikaans”. Proceedings of the 16th Annual Conference of the European Association of Machine Translation 4 / 41 Pipeline SL deformatter text morph.
    [Show full text]
  • The Apertium Bilingual Dictionaries on the Web of Data
    Semantic Web 0 (0) 1 1 IOS Press The Apertium Bilingual Dictionaries on the Web of Data Editor(s): Philipp Cimiano, Universität Bielefeld, Germany Solicited review(s): Roberto Navigli, Sapienza University of Rome, Italy; Bettina Klimek, University of Leipzig, Germany; Sebastian Hellmann, University of Leipzig, Gemany; one anonymous reviewer Jorge Gracia a;∗, Marta Villegas b, Asunción Gómez-Pérez a, and Núria Bel b, a Ontology Engineering Group, Universidad Politécnica de Madrid Campus de Montegancedo s/n Boadilla del Monte 28660 Madrid. Spain E-mail: {jgracia,asun}@fi.upm.es b Institut Universitari Linguistica Aplicada, Universitat Pompeu Fabra Roc Boronat, 138 08018 Barcelona. Spain E-mail: {marta.villegas,nuria.bel}@upf.edu Abstract. Bilingual electronic dictionaries contain collections of lexical entries in two languages, with explicitly declared trans- lation relations between such entries. Nevertheless, they are typically developed in isolation, in their own formats and accessible through proprietary APIs. In this paper we propose the use of Semantic Web techniques to make translations available on the Web to be consumed by other semantic enabled resources in a direct manner, based on standard languages and query means. In particular, we describe the conversion of the Apertium family of bilingual dictionaries and lexicons into RDF (Resource De- scription Framework) and how their data have been made accessible on the Web as linked data. As a result, all the converted dictionaries (many of them covering under-resourced languages) are connected among them and can be easily traversed from one to another to obtain, for instance, translations between language pairs not originally connected in any of the original dictionaries.
    [Show full text]