Multilingual Part-of-Speech Tagging: Two Unsupervised Approaches

We demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech tagging. The central assumption of our work is that by combining cues from multiple languages, the structure of each becomes more apparent. We consider two ways of applying this intuition to the problem of unsupervised part-of-speech tagging: a model that directly merges tag structures for a pair of languages into a single sequence and a second model which instead incorporates multilingual context using latent variables. Both approaches are formulated as hierarchical Bayesian models, using Markov Chain Monte Carlo sampling techniques for inference. Our results demonstrate that by incorporating multilingual evidence we can achieve impressive performance gains across a range of scenarios. We also found that performance improves steadily as the number of available languages increases

Predicting Linguistic Structure with Incomplete and Cross-Lingual Supervision

Contemporary approaches to natural language processing are predominantly based on statistical machine learning from large amounts of text, which has been manually annotated with the linguistic structure of interest. However, such complete supervision is currently only available for the world's major languages, in a limited number of domains and for a limited range of tasks. As an alternative, this dissertation considers methods for linguistic structure prediction that can make use of incomplete and cross-lingual supervision, with the prospect of making linguistic processing tools more widely available at a lower cost. An overarching theme of this work is the use of structured discriminative latent variable models for learning with indirect and ambiguous supervision; as instantiated, these models admit rich model features while retaining efficient learning and inference properties. The first contribution to this end is a latent-variable model for fine-grained sentiment analysis with coarse-grained indirect supervision. The second is a model for cross-lingual word-cluster induction and the application thereof to cross-lingual model transfer. The third is a method for adapting multi-source discriminative cross-lingual transfer models to target languages, by means of typologically informed selective parameter sharing. The fourth is an ambiguity-aware self- and ensemble-training algorithm, which is applied to target language adaptation and relexicalization of delexicalized cross-lingual transfer parsers. The fifth is a set of sequence-labeling models that combine constraints at the level of tokens and types, and an instantiation of these models for part-of-speech tagging with incomplete cross-lingual and crowdsourced supervision. In addition to these contributions, comprehensive overviews are provided of structured prediction with no or incomplete supervision, as well as of learning in the multilingual and cross-lingual settings. Through careful empirical evaluation, it is established that the proposed methods can be used to create substantially more accurate tools for linguistic processing, compared to both unsupervised methods and to recently proposed cross-lingual methods. The empirical support for this claim is particularly strong in the latter case; our models for syntactic dependency parsing and part-of-speech tagging achieve the hitherto best published results for a wide number of target languages, in the setting where no annotated training data is available in the target language

Unsupervised multilingual learning

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 241-254).For centuries, scholars have explored the deep links among human languages. In this thesis, we present a class of probabilistic models that exploit these links as a form of naturally occurring supervision. These models allow us to substantially improve performance for core text processing tasks, such as morphological segmentation, part-of-speech tagging, and syntactic parsing. Besides these traditional NLP tasks, we also present a multilingual model for lost language deciphersment. We test this model on the ancient Ugaritic language. Our results show that we can automatically uncover much of the historical relationship between Ugaritic and Biblical Hebrew, a known related language.by Benjamin Snyder.Ph.D

Rapid Resource Transfer for Multilingual Natural Language Processing

Until recently the focus of the Natural Language Processing (NLP) community has been on a handful of mostly European languages. However, the rapid changes taking place in the economic and political climate of the world precipitate a similar change to the relative importance given to various languages. The importance of rapidly acquiring NLP resources and computational capabilities in new languages is widely accepted. Statistical NLP models have a distinct advantage over rule-based methods in achieving this goal since they require far less manual labor. However, statistical methods require two fundamental resources for training: (1) online corpora (2) manual annotations. Creating these two resources can be as difficult as porting rule-based methods. This thesis demonstrates the feasibility of acquiring both corpora and annotations by exploiting existing resources for well-studied languages. Basic resources for new languages can be acquired in a rapid and cost-effective manner by utilizing existing resources cross-lingually. Currently, the most viable method of obtaining online corpora is converting existing printed text into electronic form using Optical Character Recognition (OCR). Unfortunately, a language that lacks online corpora most likely lacks OCR as well. We tackle this problem by taking an existing OCR system that was desgined for a specific language and using that OCR system for a language with a similar script. We present a generative OCR model that allows us to post-process output from a non-native OCR system to achieve accuracy close to, or better than, a native one. Furthermore, we show that the performance of a native or trained OCR system can be improved by the same method. Next, we demonstrate cross-utilization of annotations on treebanks. We present an algorithm that projects dependency trees across parallel corpora. We also show that a reasonable quality treebank can be generated by combining projection with a small amount of language-specific post-processing. The projected treebank allows us to train a parser that performs comparably to a parser trained on manually generated data

Computational Etymology: Word Formation and Origins

While there are over seven thousand languages in the world, substantial language technologies exist only for a small percentage of these. The large majority of world languages do not have enough bilingual or even monolingual data for developing technologies like machine translation using current approaches. The computational study and modeling of word origins and word formation is a key step in developing comprehensive translation dictionaries for low-resource languages. This dissertation presents novel foundational work in computational etymology, a promising field which this work is pioneering. The dissertation also includes novel models of core vocabulary, dictionary information distillation, and of the diverse linguistic processes of word formation and concept realization between languages, including compounding, derivation, sense-extension, borrowing, and historical cognate relationships, utilizing statistical and neural models trained on the unprecedented scale of thousands of languages. Collectively these are important components in tackling the grand challenges of universal translation, endangered language documentation and revitalization, and supporting technologies for speakers of thousands of underserved languages

Advertising in translation: the translation of cosmetics and perfume advertisements into Portuguese

Cross-cultural communication has acquired particular significance in contemporary societies, where the world-wide traffic of people, goods and ideas, which has impacted upon social and cultural values, raises debates over globalisation issues. Translation plays a crucial role in these interchanges, by mediating the socio-cultural contacts between different language communities. The present study aims to look into the translation of advertisements that cross borders, and that are part of the cross-cultural flow. It will attempt to describe and discuss the translation strategies employed in the translation of perfume and cosmetics print advertisements in to Portuguese.F or this purpose, a selection of English and Portuguese advertisements of the major brands of these products has been made, so as to (a) outline the main translation approaches adopted in the translation into Portuguese, (b) compare them to the major approaches adopted in English advertisements of the same type, (c) discuss major issues in translation studies raised by the specificity of international advertising, and (d) infer some of the (cultural) factors conditioning these options. This analysis will consider the different constitutive dimensions of these multimodal messages, namely pictorial and verbal elements, the combination of which is believed to influence the translational approaches and processes. This study also seeks to demonstrate that discursive features and translation strategies a re-connected with the societies they are part of and hence both affect and reflect the existing cultural conditions and power relations. This view of discursive practices, particularly translation, as part of the wide cultural system, has required an approach that draws on different disciplines, namely discourse and serniotic analysis, media studies in advertising and international marketing, as well as studies in translation

Advertising in translation : the translation of cosmetics and perfume advertisements into Portuguese

Cross-cultural communication has acquired particular significance in contemporary societies, where the world-wide traffic of people, goods and ideas, which has impacted upon social and cultural values, raises debates over globalisation issues. Translation plays a crucial role in these interchanges, by mediating the socio-cultural contacts between different language communities. The present study aims to look into the translation of advertisements that cross borders, and that are part of the cross-cultural flow. It will attempt to describe and discuss the translation strategies employed in the translation of perfume and cosmetics print advertisements in to Portuguese.F or this purpose, a selection of English and Portuguese advertisements of the major brands of these products has been made, so as to (a) outline the main translation approaches adopted in the translation into Portuguese, (b) compare them to the major approaches adopted in English advertisements of the same type, (c) discuss major issues in translation studies raised by the specificity of international advertising, and (d) infer some of the (cultural) factors conditioning these options. This analysis will consider the different constitutive dimensions of these multimodal messages, namely pictorial and verbal elements, the combination of which is believed to influence the translational approaches and processes. This study also seeks to demonstrate that discursive features and translation strategies a re-connected with the societies they are part of and hence both affect and reflect the existing cultural conditions and power relations. This view of discursive practices, particularly translation, as part of the wide cultural system, has required an approach that draws on different disciplines, namely discourse and serniotic analysis, media studies in advertising and international marketing, as well as studies in translation.EThOS - Electronic Theses Online ServiceUniversidade Fernando Pessoa (UFP)GBUnited Kingdo

Proceedings

Proceedings of the Ninth International Workshop on Treebanks and Linguistic Theories. Editors: Markus Dickinson, Kaili Müürisep and Marco Passarotti. NEALT Proceedings Series, Vol. 9 (2010), 268 pages. © 2010 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/10062/15891

Feasibility of using citations as document summaries

The purpose of this research is to establish whether it is feasible to use citations as document summaries. People are good at creating and selecting summaries and are generally the standard for evaluating computer generated summaries. Citations can be characterized as concept symbols or short summaries of the document they are citing. Similarity metrics have been used in retrieval and text summarization to determine how alike two documents are. Similarity metrics have never been compared to what human subjects think are similar between two documents. If similarity metrics reflect human judgment, then we can mechanize the selection of citations that act as short summaries of the document they are citing. The research approach was to gather rater data comparing document abstracts to citations about the same document and then to statistically compare those results to several document metrics; frequency count, similarity metric, citation location and type of citation. There were two groups of raters, subject experts and non-experts. Both groups of raters were asked to evaluate seven parameters between abstract and citations: purpose, subject matter, methods, conclusions, findings, implications, readability, andunderstandability. The rater was to identify how strongly the citation represented the content of the abstract, on a five point likert scale. Document metrics were collected for frequency count, cosine, and similarity metric between abstracts and associated citations. In addition, data was collected on the location of the citations and the type of citation. Location was identified and dummy coded for introduction, method, discussion, review of the literature and conclusion. Citations were categorized and dummy coded for whether they refuted, noted, supported, reviewed, or applied information about the cited document. The results show there is a relationship between some similarity metrics and human judgment of similarity.Ph.D., Information Studies -- Drexel University, 200