pwc-archive/papers-with-abstracts huggingface dataset:
Customization of the Europarl Corpus for Translation Studies
Authors: Zahurul Islam, Alex Mehler, er
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Relation, Translation, valid

Currently, the area of translation studies lacks corpora by which translation scholars can validate their theoretical claims, for example, regarding the scope of the characteristics of the translation relation. In this paper, we describe a customized resource in the area of translation studies that mainly addresses research on the properties of the translation relation. Our experimental results show that the Type-Token-Ratio (TTR) is not a universally valid indicator of the simplification of translation.
A Parallel Corpus of Music and Lyrics Annotated with Emotions
Authors: Carlo Strapparava, Rada Mihalcea, Alberto Battocchi
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Emotion Classification, Emotion Recognition, Information Retrieval, Music Information Retrieval

In this paper, we introduce a novel parallel corpus of music and lyrics, annotated with emotions at line level. We first describe the corpus, consisting of 100 popular songs, each of them including a music component, provided in the MIDI format, as well as a lyrics component, made available as raw text. We then describe our work on enhancing this corpus with emotion annotations using crowdsourcing. We also present some initial experiments on emotion classification using the music and the lyrics representations of the songs, which lead to encouraging results, thus demonstrating the promise of using joint music-lyric models for song processing.
Creation of a bottom-up corpus-based ontology for Italian Linguistics
Authors: Elisa Bianchi, Mirko Tavosanis, Emiliano Giovannetti
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Term Extraction

This paper describes the steps of construction of a shallow lexical ontology of Italian Linguistics, set to be used by a meta-search engine for query refinement. The ontology was constructed with the software Prot{\'e}g{\'e} 4.0.2 and is in OWL format; its construction has been carried out following the steps described in the well-known Ontology Learning From Text (OLFT) layer cake. The starting point was the automatic term extraction from a corpus of web documents concerning the domain of interest (304,000 words); as regards corpus construction, we describe the main criteria of the web documents selection and its critical points, concerning the definition of user profile and of degrees of specialisation. We describe then the process of term validation and construction of a glossary of terms of Italian Linguistics; afterwards, we outline the identification of synonymic chains and the main criteria of ontology design: top classes of ontology are Concept (containing taxonomy of concepts) and Terms (containing terms of the glossary as instances), while concepts are linked through part-whole and involved-role relation, both borrowed from Wordnet. Finally, we show some examples of the application of the ontology for query refinement.
Glottolog/Langdoc:Increasing the visibility of grey literature for low-density languages
Authors: Sebastian Nordhoff, Harald Hammarstr{\"o}m
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

Language resources can be divided into structural resources treating phonology, morphosyntax, semantics etc. and resources treating the social, demographic, ethnic, political context. A third type are meta-resources, like bibliographies, which provide access to the resources of the first two kinds. This poster will present the Glottolog/Langdoc project, a comprehensive bibliography providing web access to 180k bibliographical records to (mainly) low visibility resources from low-density languages. The resources are annotated for macro-area, content language, and document type and are available in XHTML and RDF.
Rhetorical Move Detection in English Abstracts: Multi-label Sentence Classifiers and their Annotated Corpora
Authors: Carmen Dayrell, C, Arnaldo ido Jr., Gabriel Lima, Danilo Machado Jr., Ann Copestake, Val{\'e}ria Feltrim, Stella Tagnin, S Aluisio, ra
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Sentence

The relevance of automatically identifying rhetorical moves in scientific texts has been widely acknowledged in the literature. This study focuses on abstracts of standard research papers written in English and aims to tackle a fundamental limitation of current machine-learning classifiers: they are mono-labeled, that is, a sentence can only be assigned one single label. However, such approach does not adequately reflect actual language use since a move can be realized by a clause, a sentence, or even several sentences. Here, we present MAZEA (Multi-label Argumentative Zoning for English Abstracts), a multi-label classifier which automatically identifies rhetorical moves in abstracts but allows for a given sentence to be assigned as many labels as appropriate. We have resorted to various other NLP tools and used two large training corpora: (i) one corpus consists of 645 abstracts from physical sciences and engineering (PE) and (ii) the other corpus is made up of 690 from life and health sciences (LH). This paper presents our preliminary results and also discusses the various challenges involved in multi-label tagging and works towards satisfactory solutions. In addition, we also make our two training corpora publicly available so that they may serve as benchmark for this new task.
NgramQuery - Smart Information Extraction from Google N-gram using External Resources
Authors: Aleks, Martin rov, Carlo Strapparava
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Semantic Similarity, Semantic Textual Similarity

This paper describes the implementation of a generalized query language on Google Ngram database. This language allows for very expressive queries that exploit semantic similarity acquired both from corpora (e.g. LSA) and from WordNet, and phonetic similarity available from the CMU Pronouncing Dictionary. It contains a large number of new operators, which combined in a proper query can help users to extract n-grams having similarly close syntactic and semantic relational properties. We also characterize the operators with respect to their corpus affiliation and their functionality. The query syntax is considered next given in terms of Backus-Naur rules followed by a few interesting examples of how the tool can be used. We also describe the command-line arguments the user could input comparing them with the ones for retrieving n-grams through the interface of Google Ngram database. Finally we discuss possible improvements on the extraction process and some relevant query completeness issues.
Error profiling for evaluation of machine-translated text: a Polish-English case study
Authors: S Weiss, ra, Lars Ahrenberg
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Translation

We present a study of Polish-English machine translation, where the impact of various types of errors on cohesion and comprehensibility of the translations were investigated. The following phenomena are in focus: (i) The most common errors produced by current state-of-the-art MT systems for Polish-English MT. (ii) The effect of different types of errors on text cohesion. (iii) The effect of different types of errors on readers' understanding of the translation. We found that errors of incorrect and missing translations are the most common for current systems, while the category of non-translated words had the most negative impact on comprehension. All three of these categories contributed to the breaking of cohesive chains. The correlation between number of errors found in a translation and number of wrong answers in the comprehension tests was low. Another result was that non-native speakers of English performed at least as good as native speakers on the comprehension tests.
Polish Multimodal Corpus --- a collection of referential gestures
Authors: Magdalena Lis
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In face to face interaction, people refer to objects and events not only by means of speech but also by means of gesture. The present paper describes building a corpus of referential gestures. The aim is to investigate gestural reference by incorporating insights from semantic ontologies and by employing a more holistic view on referential gestures. The paper's focus is on presenting the data collection procedure and discussing the corpus' design; additionally the first insights from constructing the annotation scheme are described.
DEGELS1: A comparable corpus of French Sign Language and co-speech gestures
Authors: Annelies Braffort, Le{\"\i}la Boutora
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper, we describe DEGELS1, a comparable corpus of French Sign Language and co-speech gestures that has been created to serve as a testbed corpus for the DEGELS workshops. These workshop series were initiated in France for researchers studying French Sign Language and co-speech gestures in French, with the aim of comparing methodologies for corpus annotation. An extract was used for the first event DEGELS2011 dedicated to the annotation of pointing, and the same extract will be used for DEGELS2012, dedicated to segmentation.
Semi-Automatic Sign Language Corpora Annotation using Lexical Representations of Signs
Authors: Matilde Gonzalez, Michael Filhol, Christophe Collet
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Hand Segmentation, Machine Translation

Nowadays many researches focus on the automatic recognition of sign language. High recognition rates are achieved using lot of training data. This data is, generally, collected by manual annotating SL video corpus. However this is time consuming and the results depend on the annotators knowledge. In this work we intend to assist the annotation in terms of glosses which consist on writing down the sign meaning sign for sign thanks to automatic video processing techniques. In this case using learning data is not suitable since at the first step it will be needed to manually annotate the corpus. Also the context dependency of signs and the co-articulation effect in continuous SL make the collection of learning data very difficult. Here we present a novel approach which uses lexical representations of sign to overcome these problems and image processing techniques to match sign performances to sign representations. Signs are described using Zeebede (ZBD) which is a descriptor of signs that considers the high variability of signs. A ZBD database is used to stock signs and can be queried using several characteristics. From a video corpus sequence features are extracted using a robust body part tracking approach and a semi-automatic sign segmentation algorithm. Evaluation has shown the performances and limitation of the proposed approach.
Expanding Parallel Resources for Medium-Density Languages for Free
Authors: Georgi Iliev, Angel Genov
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Morphological Analysis, Translation

We discuss a previously proposed method for augmenting parallel corpora of limited size for the purposes of machine translation through monolingual paraphrasing of the source language. We develop a three-stage shallow paraphrasing procedure to be applied to the Swedish-Bulgarian language pair for which limited parallel resources exist. The source language exhibits specifics not typical of high-density languages already studied in a similar setting. Paraphrases of a highly productive type of compound nouns in Swedish are generated by a corpus-based technique. Certain Swedish noun-phrase types are paraphrased using basic heuristics. Further we introduce noun-phrase morphological variations for better wordform coverage. We evaluate the performance of a phrase-based statistical machine translation system trained on a baseline parallel corpus and on three stages of artificial enlargement of the source-language training data. Paraphrasing is shown to have no effect on performance for the Swedish-English translation task. We show a small, yet consistent, increase in the BLEU score of Swedish-Bulgarian translations of larger token spans on the first enlargement stage. A small improvement in the overall BLEU score of Swedish-Bulgarian translation is achieved on the second enlargement stage. We find that both improvements justify further research into the method for the Swedish-Bulgarian translation task.
Creation of an Open Shared Language Resource Repository in the Nordic and Baltic Countries
Authors: Andrejs Vasi{\c{l}}jevs, Markus Forsberg, Tatiana Gornostay, Dorte Haltrup Hansen, Krist{\'\i}n J{\'o}hannsd{\'o}ttir, Gunn Lyse, Krister Lind{\'e}n, Lene Offersgaard, Sussi Olsen, Bolette Pedersen, Eir{\'\i}kur R{\"o}gnvaldsson, Inguna Skadi{\c{n}}a, Koenraad De Smedt, Ville Oksanen, Roberts Rozis
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The META-NORD project has contributed to an open infrastructure for language resources (data and tools) under the META-NET umbrella. This paper presents the key objectives of META-NORD and reports on the results achieved in the first year of the project. META-NORD has mapped and described the national language technology landscape in the Nordic and Baltic countries in terms of language use, language technology and resources, main actors in the academy, industry, government and society; identified and collected the first batch of language resources in the Nordic and Baltic countries; documented, processed, linked, and upgraded the identified language resources to agreed standards and guidelines. The three horizontal multilingual actions in META-NORD are overviewed in this paper: linking and validating Nordic and Baltic wordnets, the harmonisation of multilingual Nordic and Baltic treebanks, and consolidating multilingual terminology resources across European countries. This paper also touches upon intellectual property rights for the sharing of language resources.
Adapting and evaluating a generic term extraction tool
Authors: Anita Gojun, Ulrich Heid, Bernd Wei{\ss}bach, Carola Loth, Insa Mingers
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Lemmatization, Term Extraction

We present techniques for monolingual term candidate extraction which are being developed in the EU project TTC. We designed an application for German and English data that serves as a first evaluation of the methods for terminology extraction used in the project. The application situation highlighted the need for tools to handle lemmatization errors and to remove incomplete word sequences from multi-word term candidate lists, as well as the fact that the provision of German citation forms requires more morphological knowledge than TTC's slim approach can provide. We show a detailed evaluation of our extraction results and discuss the method for the evaluation of terminology extraction systems.
Beyond SoNaR: towards the facilitation of large corpus building efforts
Authors: Martin Reynaert, Ineke Schuurman, V{\'e}ronique Hoste, Nelleke Oostdijk, Maarten van Gompel
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper we report on the experiences gained in the recent construction of the SoNaR corpus, a 500 MW reference corpus of contemporary, written Dutch. It shows what can realistically be done within the confines of a project setting where there are limitations to the duration in time as well to the budget, employing current state-of-the-art tools, standards and best practices. By doing so we aim to pass on insights that may be beneficial for anyone considering to undertake an effort towards building a large, varied yet balanced corpus for use by the wider research community. Various issues are discussed that come into play while compiling a large corpus, including approaches to acquiring texts, the arrangement of IPR, the choice of text formats, and steps to be taken in the preprocessing of data from widely different origins. We describe FoLiA, a new XML format geared at rich linguistic annotations. We also explain the rationale behind the investment in the high-quali ty semi-automatic enrichment of a relatively small (1 MW) subset with very rich syntactic and semantic annotations. Finally, we present some ideas about future developments and the direction corpus development may take, such as setting up an integrated work flow between web services and the potential role for ISOcat. We list tips for potential corpus builders, tricks they may want to try and further recommendations regarding technical developments future corpus builders may wish to hope for.
Leveraging study of robustness and portability of spoken language understanding systems across languages and domains: the PORTMEDIA corpora
Authors: Fabrice Lef{\`e}vre, Djamel Mostefa, Laurent Besacier, Yannick Est{\`e}ve, Matthieu Quignard, Nathalie Camelin, Benoit Favre, Bassam Jabaian, Lina M. Rojas-Barahona
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Semantic Composition, Speech Recognition, Spoken Language Understanding

The PORTMEDIA project is intended to develop new corpora for the evaluation of spoken language understanding systems. The newly collected data are in the field of human-machine dialogue systems for tourist information in French in line with the MEDIA corpus. Transcriptions and semantic annotations, obtained by low-cost procedures, are provided to allow a thorough evaluation of the systems' capabilities in terms of robustness and portability across languages and domains. A new test set with some adaptation data is prepared for each case: in Italian as an example of a new language, for ticket reservation as an example of a new domain. Finally the work is complemented by the proposition of a new high level semantic annotation scheme well-suited to dialogue data.
A GUI to Detect and Correct Errors in Hindi Dependency Treebank
Authors: Rahul Agarwal, Bharat Ram Ambati, Anil Kumar Singh
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation

A treebank is an important resource for developing many NLP based tools. Errors in the treebank may lead to error in the tools that use it. It is essential to ensure the quality of a treebank before it can be deployed for other purposes. Automatic (or semi-automatic) detection of errors in the treebank can reduce the manual work required to find and remove errors. Usually, the errors found automatically are manually corrected by the annotators. There is not much work reported so far on error correction tools which helps the annotators in correcting errors efficiently. In this paper, we present such an error correction tool that is an extension of the error detection method described earlier (Ambati et al., 2010; Ambati et al., 2011; Agarwal et al., 2012).
Spell Checking in Spanish: The Case of Diacritic Accents
Authors: Jordi Atserias, Maria Fuentes, Rogelio Nazar, Irene Renau
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This article presents the problem of diacritic restoration (or diacritization) in the context of spell-checking, with the focus on an orthographically rich language such as Spanish. We argue that despite the large volume of work published on the topic of diacritization, currently available spell-checking tools have still not found a proper solution to the problem in those cases where both forms of a word are listed in the checker's dictionary. This is the case, for instance, when a word form exists with and without diacritics, such as continuo continuous' and continu{\'o} he/she/it continued', or when different diacritics make other word distinctions, as in contin{\'u}o I continue'. We propose a very simple solution based on a word bigram model derived from correctly typed Spanish texts and evaluate the ability of this model to restore diacritics in artificial as well as real errors. The case of diacritics is only meant to be an example of the possible applications for this idea, yet we believe that the same method could be applied to other kinds of orthographic or even grammatical errors. Moreover, given that no explicit linguistic knowledge is required, the proposed model can be used with other languages provided that a large normative corpus is available.
Iterative Refinement and Quality Checking of Annotation Guidelines --- How to Deal Effectively with Semantically Sloppy Named Entity Types, such as Pathological Phenomena
Authors: Udo Hahn, Elena Beisswanger, Ekaterina Buyko, Erik Faessler, Jenny Traum{\"u}ller, Susann Schr{\"o}der, Kerstin Hornbostel
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Descriptive, Named Entity Recognition (NER)

We here discuss a methodology for dealing with the annotation of semantically hard to delineate, i.e., sloppy, named entity types. To illustrate sloppiness of entities, we treat an example from the medical domain, namely pathological phenomena. Based on our experience with iterative guideline refinement we propose to carefully characterize the thematic scope of the annotation by positive and negative coding lists and allow for alternative, short vs. long mention span annotations. Short spans account for canonical entity mentions (e.g., standardized disease names), while long spans cover descriptive text snippets which contain entity-specific elaborations (e.g., anatomical locations, observational details, etc.). Using this stratified approach, evidence for increasing annotation performance is provided by kappa-based inter-annotator agreement measurements over several, iterative annotation rounds using continuously refined guidelines. The latter reflects the increasing understanding of the sloppy entity class both from the perspective of guideline writers and users (annotators). Given our data, we have gathered evidence that we can deal with sloppiness in a controlled manner and expect inter-annotator agreement values around 80{\%} for PathoJen, the pathological phenomena corpus currently under development in our lab.
Example-Based Treebank Querying
Authors: Liesbeth Augustinus, V, Vincent eghinste, Frank Van Eynde
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The recent construction of large linguistic treebanks for spoken and written Dutch (e.g. CGN, LASSY, Alpino) has created new and exciting opportunities for the empirical investigation of Dutch syntax and semantics. However, the exploitation of those treebanks requires knowledge of specific data structures and query languages such as XPath. Linguists who are unfamiliar with formal languages are often reluctant towards learning such a language. In order to make treebank querying more attractive for non-technical users we developed GrETEL (Greedy Extraction of Trees for Empirical Linguistics), a query engine in which linguists can use natural language examples as a starting point for searching the Lassy treebank without knowledge about tree representations nor formal query languages. By allowing linguists to search for similar constructions as the example they provide, we hope to bridge the gap between traditional and computational linguistics. Two case studies are conducted to provide a concrete demonstration of the tool. The architecture of the tool is optimised for searching the LASSY treebank, but the approach can be adapted to other treebank lay-outs.