Translation Alignment and Extraction Within a Lexica-Centered Iterative Workflow

This thesis addresses two closely related problems. The first, translation alignment, consists of identifying bilingual document pairs that are translations of each other within multilingual document collections (document alignment); identifying sentences, titles, etc, that are translations of each other within bilingual document pairs (sentence alignment); and identifying corresponding word and phrase translations within bilingual sentence pairs (phrase alignment). The second is extraction of bilingual pairs of equivalent word and multi-word expressions, which we call translation equivalents (TEs), from sentence- and phrase-aligned parallel corpora. While these same problems have been investigated by other authors, their focus has been on fully unsupervised methods based mostly or exclusively on parallel corpora. Bilingual lexica, which are basically lists of TEs, have not been considered or given enough importance as resources in the treatment of these problems. Human validation of TEs, which consists of manually classifying TEs as correct or incorrect translations, has also not been considered in the context of alignment and extraction. Validation strengthens the importance of infrequent TEs (most of the entries of a validated lexicon) that otherwise would be statistically unimportant. The main goal of this thesis is to revisit the alignment and extraction problems in the context of a lexica-centered iterative workflow that includes human validation. Therefore, the methods proposed in this thesis were designed to take advantage of knowledge accumulated in human-validated bilingual lexica and translation tables obtained by unsupervised methods. Phrase-level alignment is a stepping stone for several applications, including the extraction of new TEs, the creation of statistical machine translation systems, and the creation of bilingual concordances. Therefore, for phrase-level alignment, the higher accuracy of human-validated bilingual lexica is crucial for achieving higher quality results in these downstream applications. There are two main conceptual contributions. The first is the coverage maximization approach to alignment, which makes direct use of the information contained in a lexicon, or in translation tables when this is small or does not exist. The second is the introduction of translation patterns which combine novel and old ideas and enables precise and productive extraction of TEs. As material contributions, the alignment and extraction methods proposed in this thesis have produced source materials for three lines of research, in the context of three PhD theses (two of them already defended), all sharing with me the supervision of my advisor. The topics of these lines of research are statistical machine translation, algorithms and data structures for indexing and querying phrase-aligned parallel corpora, and bilingual lexica classification and generation. Four publications have resulted directly from the work presented in this thesis and twelve from the collaborative lines of research

Linguistic Motivation in Automatic Sentence Alignment of Parallel Corpora: the Case of Danish-Bulgarian and English-Bulgarian

Proceedings of the 18th Nordic Conference of Computational Linguistics NODALIDA 2011. Editors: Bolette Sandford Pedersen, Gunta Nešpore and Inguna Skadiņa. NEALT Proceedings Series, Vol. 11 (2011), 328-331. © 2011 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/1695

Developing online parallel corpus-based processing tools for translation research and pedagogy

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Comunicação e Expressão, Programa de Pós-Graduação em Letras/Inglês e Literatura Correspondente, Florianópolis, 2013.Abstract : This study describes the key steps in developing online parallel corpus-based tools for processing COPA-TRAD (copa-trad.ufsc.br), a parallel corpus compiled for translation research and pedagogy. The study draws on Fernandes s (2009) proposal for corpus compilation, which divides the compiling process into three main parts: corpus design, corpus building and corpus processing. This compiling process received contributions from the good development practices of Software Engineering, especially the ones advocated by Pressman (2011). The tools developed can, for example, assist in the investigation of certain types of texts and translational practices related to certain linguistic patterns such as collocations and semantic prosody. As a result of these applications, COPA-TRAD becomes a suitable tool for the investigation of empirical phenomena with a view to translation research and pedagogy.Este estudo descreve as principais etapas no desenvolvimento de ferramentas online com base em corpus para o processamento do COPA-TRAD (Corpus Paralelo de Tradução - www.copa-trad.ufsc.br), um corpus paralelo compilado para a pesquisa e ensino de tradução. Para a compilação do corpus, o estudo utiliza a proposta de Fernandes (2009) que divide o processo de compilação em três etapas principais: desenho do corpus, construção do corpus e processamento do corpus. Este processo de compilação recebeu contribuições das boas práticas de desenvolvimento fornecidas pela Engenharia de Software, especialmente as que foram sugeridas por Pressman (2011). As ferramentas desenvolvidas podem, por exemplo, auxiliar na investigação de certos tipos de textos, bem como em práticas tradutórias relacionadas a certos padrões linguísticos tais como colocações e prosódia semântica. Como resultado dessas aplicações, o COPA-TRAD configura-se em uma ferramenta útil para a investigação empírica de fenômenos tradutórios com vistas à pesquisa e ao ensino de tradução

Extração de combinações lexicais restritas pela deteção da não composionalidade de expressões pluriverbais

In this article an evaluation of a method for extracting restricted lexical combinations from parallel corpora by detecting non-compositionality of multiword expressions in translation will be presented. This method presupposes that by finding sequences of words whose translation does not follow a simple word-to-word conversion of the component words, a collocation is probably present. Word bigrams are used.Neste artigo apresentamos uma avaliação sobre um método para extrair combinações lexicais restritas a partir de corpora paralelos, pela deteção da não composicionalidade de expressões pluriverbais na tradução. Este método baseia-se na presunção de que, encontrando sequências de palavras cuja tradução não siga a tradução palavra por palavra dos seus componentes, é provável estar-se perante uma colocação. São usadas palavras brigrama.info:eu-repo/semantics/publishedVersio

Machine translation of non-contiguous multiword units

Non-adjacent linguistic phenomena such as non-contiguous multiwords and other phrasal units containing insertions, i.e., words that are not part of the unit, are difficult to process and remain a problem for NLP applications. Non-contiguous multiword units are common across languages and constitute some of the most important challenges to high quality machine translation. This paper presents an empirical analysis of non-contiguous multiwords, and highlights our use of the Logos Model and the Semtab function to deploy semantic knowledge to align non-contiguous multiword units with the goal to translate these units with high fidelity. The phrase level manual alignments illustrated in the paper were produced with the CLUE-Aligner, a Cross-Language Unit Elicitation alignment tool.info:eu-repo/semantics/acceptedVersio

Defining a probabilistic translation dictionaries algebra

Probabilistic Translation Dictionaries are around for some time, but there is a lack of a formal definition for their structure and base operations. In this article we start by discussing what these resources are, what researchers are using them for, and what tools can be used to create this them. Including a formal definition and a proposal for a XML schema for dictionaries interchange. Follows a discussion of a set of useful operations that can be performed over probabilistic translation dictionaries, like union, intersection, domain restriction and compo- sition. Together with this algebra formalization some insights on the operations usefulness and application are presented.This work is partially supported by Per-Fide. The Per-Fide project is supported in part by a grant (Reference No. PTDC/CLEL-LI/108948/2008) from the Portuguese Foundation for Science and Technology and it is co-funded by the European Regional Development Fund

Definition of interfaces

The aim of this report is to define the interfaces for the tools used in the MT development and evaluation scenarios as included in the QTLaunchPad (QTLP) infrastructure. Specification of the interfaces is important for the interaction and interoperability of the tools in the developed QTLP infrastructure. In addressing this aim, the report provides: 1. Descriptions of the common aspects of the tools and their standardized data formats; 2. Descriptions of the interfaces for the tools for interoperability. where the tools are categorized into preparation, development, and evaluation categories including the human interfaces for quality assessment with multidimensional quality metrics. Interface specifications allow a modular tool infrastructure, flexibly selecting among alternative implementations, enabling realistic expectations to be made at different sections of the QTLP information flow pipeline, and supporting the QTLP infrastructure. D3.2.1 allows the emergence of the QTLP infrastructure and helps the identification and acquisition of existing tools (D4.4.1), the integration of identified language processing tools (D3.3.1), their implementation (D3.4.1), and their testing (D3.5.1). QTLP infrastructure will facilitate the organization and running of the quality translation shared task (D5.2.1). We also provide human interfaces for translation quality assessment with the multidimensional quality metrics (D1.1.1). D3.2.1 is a living document until M12, which is when the identification and acquisition of existing tools (D4.4.1) and the implementation of identified language processing tools (D3.4.1) are due

Parallel corpora word alignment and applications

Parallel corpora are valuable resources on natural language processing and, in special, on the translation area. They can be used not only by translators, but also analyzed and processed by computers to learn and extract information about the languages. In this document, we talk about some processes related with the parallel corpora life cycle. We will focus on the parallel corpora word alignment. The necessity for a robust word aligner arrived with the TerminUM project which goal is to gather parallel corpora from different sources, align, analyze and use them to create bilingual resources like terminology or translation memories for machine translation. Aligner, an open-source word aligner developed by Djoerd Hiemstra. Its results were interesting but it worked only for small sized corpora. The work done began with the reengineering of Twente-Aligner, followed by the analysis of the alignment results and the development of several tools based on the extracted probabilistic dictionaries. The re-engineering process was based on formal methods: the algorithms and data structures were formalized, optimized and re-implemented. The timings and alignment results were analysed. The speed improvement derived from the re-engineering process and the scale-up derived of the alignment by chunks, permitted the alignment of bigger corpora. Bigger corpora makes dictionaries quality raise, and this makes new problems and new ideas possible. The probabilistic dictionaries created by the alignment process were used in different tasks. A first pair of tools was developed to search the dictionaries and their relation to the corpora. The probabilistic dictionaries were used to calculate a measure of how two sentences are translations of each other. This naive measure was used to prototype tools for aligning word sequences, to extract multiword terminology from corpora, and a “by example” machine translation software.Os corpora paralelos são recursos muito valiosos no processamento da linguagem natural e, em especial, na área da tradução. Podem ser usados não só por tradutores, mas também analisados e processados por computadores para aprender e extrair informação sobre as línguas. Neste documento, falamos sobre alguns dos processos relacionados como ciclo de vida dos corpora paralelos. Iremo-nos focar no alinhamento de corpora paralelo à palavra. A necessidade de um alinhador à palavra robusto apareceu com o projecto TerminUM, que tem como principal objectivo recolher corpora paralelos de diferentes fontes, alinhar e usá-los para criar recursos bilingues como terminologia ou memórias de tradução para tradução automática. O ponto de arranque foi o Twente-Aligner, um alinhador à palavra open-source, desenvolvido por Djoerd Hiemstra. Os seus resultados eram interessantes mas só funcionava para corpora de tamanhos pequenos. O trabalho realizado iniciou com a re-engenharia do Twente-Aligner, seguida pela análise dos resultados do alinhamento e o desenvolvimento de várias ferramentas baseadas nos dicionários probabilísticos extraídos. O processo de re-engenharia foi baseado em métodos formais: os algoritmos e estruturas de dados foram formalizados, optimizados e re-implementados. Os tempos e resultados de alinhamento foram analizados. Os melhoramentos em velocidade derivados do processo de re-engenharia e a escalabilidade derivada do alinhamento por fatias, permitiu o alinhamento de corpora maiores. Corpora maiores fazem aumentar a qualidade dos dicionários, o que torna novos problemas e ideias possíveis. Os dicionários probabilísticos criados pelo processo de alinhamento foram usados em tarefas diferentes. Um primeiro par de ferramentas foi desenvolvido para procurar nos dicionários e a sua relação com os corpora. Os dicionários probabilísticos foram usados para calcular uma medida de quão duas frases são tradução uma da outra. Esta medida foi usada para prototipar ferramentas para o alinhamento de sequências de palavras, extrair terminologia multipalavra dos corpora, e uma aplicação automática de tradução "por exemplo"

Coreference resolution for portuguese using parallel corpora word alignment

A área de Extração da Informação tem como objetivo essencial investigar métodos e técnicas para transformar a informação não estruturada presente em textos de língua natural em dados estruturados. Um importante passo deste processo é a resolução de correferência, tarefa que identifica diferentes sintagmas nominais que se referem a mesma entidade no discurso. A área de estudos sobre resolução de correferência tem sido extensivamente pesquisada para a Língua Inglesa (Ng, 2010) lista uma série de estudos da área, entretanto tem recebido menos atenção em outras línguas. Isso se deve ao fato de que a grande maioria das abordagens utilizadas nessas pesquisas são baseadas em aprendizado de máquina e, portanto, requerem uma extensa quantidade de dados anotados