pwc-archive/papers-with-abstracts huggingface dataset:
Iula2Standoff: a tool for creating standoff documents for the IULACT
Authors: Carlos Morell, Jorge Vivaldi, N{\'u}ria Bel
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Lemmatization, POS, POS Tagging

Due to the increase in the number and depth of analyses required over the text, like entity recognition, POS tagging, syntactic analysis, etc. the annotation in-line has become unpractical. In Natural Language Processing (NLP) some emphasis has been placed in finding an annotation method to solve this problem. A possibility is the standoff annotation. With this annotation style it is possible to add new levels of annotation without disturbing exiting ones, with minimal knock on effects. This annotation will increase the possibility of adding more linguistic information as well as more possibilities for sharing textual resources. In this paper we present a tool developed in the framework of the European Metanet4u (Enhancing the European Linguistic Infrastructure, GA 270893) for creating a multi-layered XML annotation scheme, based on the GrAF proposal for standoff annotations.
Temporal Annotation: A Proposal for Guidelines and an Experiment with Inter-annotator Agreement
Authors: Andr{\'e} Bittar, Caroline Hag{\`e}ge, V{\'e}ronique Moriceau, Xavier Tannier, Charles Teiss{\`e}dre
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This article presents work carried out within the framework of the ongoing ANR (French National Research Agency) project Chronolines, which focuses on the temporal processing of large news-wire corpora in English and French. The aim of the project is to create new and innovative interfaces for visualizing textual content according to temporal criteria. Extracting and normalizing the temporal information in texts through linguistic annotation is an essential step towards attaining this objective. With this goal in mind, we developed a set of guidelines for the annotation of temporal and event expressions that is intended to be compatible with the TimeML markup language, while addressing some of its pitfalls. We provide results of an initial application of these guidelines to real news-wire texts in French over several iterations of the annotation process. These results include inter-annotator agreement figures and an error analysis. Our final inter-annotator agreement figures compare favorably with those reported for the TimeBank 1.2 annotation project.
Introducing the Reference Corpus of Contemporary Portuguese Online
Authors: Michel G{\'e}n{\'e}reux, Iris Hendrickx, Am{\'a}lia Mendes
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Optical Character Recognition (OCR)

We present our work in processing the Reference Corpus of Contemporary Portuguese and its publication online. After discussing how the corpus was built and our choice of meta-data, we turn to the processes and tools involved for the cleaning, preparation and annotation to make the corpus suitable for linguistic inquiries. The Web platform is described, and we show examples of linguistic resources that can be extracted from the platform for use in linguistic studies or in NLP.
A Corpus-based Study of the German Recipient Passive
Authors: Patrick Ziering, Sina Zarrie{\ss}, Jonas Kuhn
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper, we investigate the usage of a non-canonical German passive alternation for ditransitive verbs, the recipient passive, in naturally occuring corpus data. We propose a classifier that predicts the voice of a ditransitive verb based on the contextually determined properties its arguments. As the recipient passive is a low frequent phenomenon, we first create a special data set focussing on German ditransitive verbs which are frequently used in the recipient passive. We use a broad-coverage grammar-based parser, the German LFG parser, to automatically annotate our data set for the morpho-syntactic properties of the involved predicate arguments. We train a Maximum Entropy classifier on the automatically annotated sentences and achieve an accuracy of 98.05{\%}, clearly outperforming the baseline that always predicts active voice baseline (94.6{\%}).
``Vreselijk mooi!'' (terribly beautiful): A Subjectivity Lexicon for Dutch Adjectives.
Authors: Tom De Smedt, Walter Daelemans
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: BIG-bench Machine Learning, Lemmatization, Opinion Mining, Sentiment Analysis, Text Classification

We present a new open source subjectivity lexicon for Dutch adjectives. The lexicon is a dictionary of 1,100 adjectives that occur frequently in online product reviews, manually annotated with polarity strength, subjectivity and intensity, for each word sense. We discuss two machine learning methods (using distributional extraction and synset relations) to automatically expand the lexicon to 5,500 words. We evaluate the lexicon by comparing it to the user-given star rating of online product reviews. We show promising results in both in-domain and cross-domain evaluation. The lexicon is publicly available as part of the PATTERN software package (http://www.clips.ua.ac.be/pages/pattern).
Rule-Based Detection of Clausal Coordinate Ellipsis
Authors: Kristiina Muhonen, Tanja Purtonen
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Morphological Analysis, Sentence

With our experiment, we show how we can detect and annotate clausal coordinate ellipsis with Constraint Grammar rules. We focus on such an elliptical structure in which there are two coordinated clauses, and the latter one lacks a verb. For example, the sentence This belongs to me and that to you demonstrates the ellipsis in question, namely gapping. The Constraint Grammar rules are made for a Finnish parsebank, FinnTreeBank. The FinnTreeBank project is building a parsebank in the dependency syntactic framework in which verbs are central since other sentence elements depend on them. Without correct detection of omitted verbs, the syntactic analysis of the whole sentence fails. In the experiment, we detect gapping based on morphology and linear order of the words without using syntactic or semantic information. The test corpus, Finnish Wikipedia, is morphologically analyzed but not disambiguated. Even with an ambiguous morphological analysis, the results show that 89,9{\%} of the detected sentences are elliptical, making the rules accurate enough to be used in the creation of FinnTreeBank. Once we have a morphologically disambiguated corpus, we can write more accurate rules and expect better results.
Evolution of Event Designation in Media: Preliminary Study
Authors: Xavier Tannier, V{\'e}ronique Moriceau, B{\'e}atrice Arnulphy, Ruixin He
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Descriptive, Information Retrieval, Retrieval

Within the general purpose of information extraction, detection of event descriptions is often an important clue. An important characteristic of event designation in texts, and especially in media, is that it changes over time. Understanding how these designations evolve is important in information retrieval and information extraction. Our first hypothesis is that, when an event first occurs, media relate it in a very descriptive way (using verbal designations) whereas after some time, they use shorter nominal designations instead. Our second hypothesis is that the number of different nominal designations for an event tends to stabilize itself over time. In this article, we present our methodology concerning the study of the evolution of event designations in French documents from the news agency AFP. For this preliminary study, we focused on 7 topics which have been relatively important in France. Verbal and nominal designations of events have been manually annotated in manually selected topic-related passages. This French corpus contains a total of 2064 annotations. We then provide preliminary interesting statistical results and observations concerning these evolutions.
Evaluating Machine Reading Systems through Comprehension Tests
Authors: Anselmo Pe{\~n}as, Eduard Hovy, Pamela Forner, {\'A}lvaro Rodrigo, Richard Sutcliffe, Corina Forascu, Caroline Sporleder
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Answer Selection, Multiple-choice, Question Answering, Reading Comprehension

This paper describes a methodology for testing and evaluating the performance of Machine Reading systems through Question Answering and Reading Comprehension Tests. The methodology is being used in QA4MRE (QA for Machine Reading Evaluation), one of the labs of CLEF. The task was to answer a series of multiple choice tests, each based on a single document. This allows complex questions to be asked but makes evaluation simple and completely automatic. The evaluation architecture is completely multilingual: test documents, questions, and their answers are identical in all the supported languages. Background text collections are comparable collections harvested from the web for a set of predefined topics. Each test received an evaluation score between 0 and 1 using c@1. This measure encourages systems to reduce the number of incorrect answers while maintaining the number of correct ones by leaving some questions unanswered. 12 groups participated in the task, submitting 62 runs in 3 different languages (German, English, and Romanian). All runs were monolingual; no team attempted a cross-language task. We report here the conclusions and lessons learned after the first campaign in 2011.
Biomedical Chinese-English CLIR Using an Extended CMeSH Resource to Expand Queries
Authors: Xinkai Wang, Paul Thompson, Jun{'}ichi Tsujii, Sophia Ananiadou
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Cross-Lingual Information Retrieval, Document Translation, Information Retrieval, Language Modelling, Retrieval

Cross-lingual information retrieval (CLIR) involving the Chinese language has been thoroughly studied in the general language domain, but rarely in the biomedical domain, due to the lack of suitable linguistic resources and parsing tools. In this paper, we describe a Chinese-English CLIR system for biomedical literature, which exploits a bilingual ontology, the ``eCMeSH Tree''''''''. This is an extension of the Chinese Medical Subject Headings (CMeSH) Tree, based on Medical Subject Headings (MeSH). Using the 2006 and 2007 TREC Genomics track data, we have evaluated the performance of the eCMeSH Tree in expanding queries. We have compared our results to those obtained using two other approaches, i.e. pseudo-relevance feedback (PRF) and document translation (DT). Subsequently, we evaluate the performance of different combinations of these three retrieval methods. Our results show that our method of expanding queries using the eCMeSH Tree can outperform the PRF method. Furthermore, combining this method with PRF and DT helps to smooth the differences in query expansion, and consequently results in the best performance amongst all experiments reported. All experiments compare the use of two different retrieval models, i.e. Okapi BM25 and a query likelihood language model. In general, the former performs slightly better.
A proposal for improving WordNet Domains
Authors: Aitor Gonz{\'a}lez-Agirre, Mauro Castillo, German Rigau
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

WordNet Domains (WND) is a lexical resource where synsets have been semi-automatically annotated with one or more domain labels from a set of 165 hierarchically organized domains. The uses of WND include the power to reduce the polysemy degree of the words, grouping those senses that belong to the same domain. But the semi-automatic method used to develop this resource was far from being perfect. By cross-checking the content of the Multilingual Central Repository (MCR) it is possible to find some errors and inconsistencies. Many are very subtle. Others, however, leave no doubt. Moreover, it is very difficult to quantify the number of errors in the original version of WND. This paper presents a novel semi-automatic method to propagate domain information through the MCR. We also compare both labellings (the original and the new one) allowing us to detect anomalies in the original WND labels.
An Oral History Annotation Tool for INTER-VIEWs
Authors: Henk van den Heuvel, S, Eric ers, Robin Rutten, Stef Scagliola, Paula Witkamp
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Retrieval, Speech Recognition

We present a web-based tool for retrieving and annotating audio fragments of e.g. interviews. Our collection contains 250 interviews with veterans of Dutch conflicts and military missions. The audio files of the interviews were disclosed using ASR technology focussed at keyword retrieval. Resulting transcripts were stored in a MySQL database together with metadata, summary texts, and keywords, and carefully indexed. Retrieved fragments can be made audible and annotated. Annotations can be kept personal or be shared with other users. The tool and formats comply with CLARIN standards. A demo version of the tool is available at http://wwwlands2.let.kun.nl/spex/annotationtooldemo.
Comparing computer vision analysis of signed language video with motion capture recordings
Authors: Matti Karppa, Tommi Jantunen, Ville Viitaniemi, Jorma Laaksonen, Birgitta Burger, Danny De Weerdt
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

We consider a non-intrusive computer-vision method for measuring the motion of a person performing natural signing in video recordings. The quality and usefulness of the method is compared to a traditional marker-based motion capture set-up. The accuracy of descriptors extracted from video footage is assessed qualitatively in the context of sign language analysis by examining if the shape of the curves produced by the different means resemble one another in sequences where the shape could be a source of valuable linguistic information. Then, quantitative comparison is performed first by correlating the computer-vision-based descriptors with the variables gathered with the motion capture equipment. Finally, multivariate linear and non-linar regression methods are applied for predicting the motion capture variables based on combinations of computer vision descriptors. The results show that even the simple computer vision method evaluated in this paper can produce promisingly good results for assisting researchers working on sign language analysis.
Free/Open Source Shallow-Transfer Based Machine Translation for Spanish and Aragonese
Authors: Juan Pablo Mart{\'\i}nez Cort{\'e}s, Jim O{'}Regan, Francis Tyers
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Morphological Analysis, Translation

This article describes the development of a bidirectional shallow-transfer based machine translation system for Spanish and Aragonese, based on the Apertium platform, reusing the resources provided by other translators built for the platform. The system, and the morphological analyser built for it, are both the first resources of their kind for Aragonese. The morphological analyser has coverage of over 80{\textbackslash}{\%}, and is being reused to create a spelling checker for Aragonese. The translator is bidirectional: the Word Error Rate for Spanish to Aragonese is 16.83{\%}, while Aragonese to Spanish is 11.61{\%}.
Building Large Monolingual Dictionaries at the Leipzig Corpora Collection: From 100 to 200 Languages
Authors: Dirk Goldhahn, Thomas Eckart, Uwe Quasthoff
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Lemmatization

The Leipzig Corpora Collection offers free online access to 136 monolingual dictionaries enriched with statistical information. In this paper we describe current advances of the project in collecting and processing text data automatically for a large number of languages. Our main interest lies in languages of low density, where only few text data exists online. The aim of this approach is to create monolingual dictionaries and statistical information for a high number of new languages and to expand the existing dictionaries, opening up new possibilities for linguistic typology and other research. Focus of this paper will be set on the infrastructure for the automatic acquisition of large amounts of monolingual text in many languages from various sources. Preliminary results of the collection of text data will be presented. The mainly language-independent framework for preprocessing, cleaning and creating the corpora and computing the necessary statistics will also be depicted.
Sense Meets Nonsense - Sense Meets Nonsense - a dual-layer Danish speech corpus for perception studies
Authors: Thomas Ulrich Christiansen, Peter Juel Henrichsen
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper, we present the newly established Danish speech corpus PiTu. The corpus consists of recordings of 28 native Danish talkers (14 female and 14 male) each reproducing (i) a series of nonsense syllables, and (ii) a set of authentic natural language sentences. The speech corpus is tailored for investigating the relationship between early stages of the speech perceptual process and later stages. We present our considerations involved in preparing the experimental set-up, producing the anechoic recordings, compiling the data, and exploring the materials in linguistic research. We report on a small pilot experiment demonstrating how PiTu and similar speech corpora can be used in studies of prosody as a function of semantic content. The experiment addresses the issue of whether the governing principles of Danish prosody assignment is mainly talker-specific or mainly content-typical (under the specific experimental conditions). The corpus is available in its entirety for download at http://amtoolbox.sourceforge.net/pitu/.
The acquisition and dialog act labeling of the EDECAN-SPORTS corpus
Authors: Llu{\'\i}s-F. Hurtado, Fern Garc{\'\i}a, o, Emilio Sanchis, Encarna Segarra
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Speech Recognition

In this paper, we present the acquisition and labeling processes of the EDECAN-SPORTS corpus, which is a corpus that is oriented to the development of multimodal dialog systems acquired in Spanish and Catalan. Two Wizards of Oz were used in order to better simulate the behavior of an actual system in terms of both the information used by the different modules and the communication mechanisms between these modules. User and system dialog-act labeling, as well as other information, have been obtained automatically using this acquisition method Some preliminary experimental results with the acquired corpus show the appropriateness of the proposed acquisition method for the development of dialog systems
A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let's Go Bus Information System
Authors: Alex Schmitt, er, Stefan Ultes, Wolfgang Minker
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Emotion Recognition, speech-recognition, Speech Recognition, Spoken Language Understanding

Standardized corpora are the foundation for spoken language research. In this work, we introduce an annotated and standardized corpus in the Spoken Dialog Systems (SDS) domain. Data from the Let's Go Bus Information System from the Carnegie Mellon University in Pittsburgh has been formatted, parameterized and annotated with quality, emotion, and task success labels containing 347 dialogs with 9,083 system-user exchanges. A total of 46 parameters have been derived automatically and semi-automatically from Automatic Speech Recognition (ASR), Spoken Language Understanding (SLU) and Dialog Manager (DM) properties. To each spoken user utterance an emotion label from the set garbage, non-angry, slightly angry, very angry has been assigned. In addition, a manual annotation of Interaction Quality (IQ) on the exchange level has been performed with three raters achieving a Kappa value of 0.54. The IQ score expresses the quality of the interaction up to each system-user exchange on a score from 1-5. The presented corpus is intended as a standardized basis for classification and evaluation tasks regarding task success prediction, dialog quality estimation or emotion recognition to foster comparability between different approaches on these fields.
Pragmatic identification of the witness sets
Authors: Livio Robaldo, Jakub Szymanik
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

Among the readings available for NL sentences, those where two or more sets of entities are independent of one another are particularly challenging from both a theoretical and an empirical point of view. Those readings are termed here as Â‘Independent Set (IS) readings'. Standard examples of such readings are the well-known Collective and Cumulative Readings. (Robaldo, 2011) proposes a logical framework that can properly represent the meaning of IS readings in terms of a set-Skolemization of the witness sets. One of the main assumptions of Robaldo's logical framework, drawn from (Schwarzschild, 1996), is that pragmatics plays a crucial role in the identification of such witness sets. Those are firstly identified on pragmatic grounds, then logical clauses are asserted on them in order to trigger the appropriate inferences. In this paper, we present the results of an experimental analysis that appears to confirm Robaldo's hypotheses concerning the pragmatic identification of the witness sets.
A good space: Lexical predictors in word space evaluation
Authors: Christian Smith, Henrik Danielsson, Arne J{\"o}nsson
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Text Categorization, Word Sense Disambiguation

Vector space models benefit from using an outside corpus to train the model. It is, however, unclear what constitutes a good training corpus. We have investigated the effect on summary quality when using various language resources to train a vector space based extraction summarizer. This is done by evaluating the performance of the summarizer utilizing vector spaces built from corpora from different genres, partitioned from the Swedish SUC-corpus. The corpora are also characterized using a variety of lexical measures commonly used in readability studies. The performance of the summarizer is measured by comparing automatically produced summaries to human created gold standard summaries using the ROUGE F-score. Our results show that the genre of the training corpus does not have a significant effect on summary quality. However, evaluating the variance in the F-score between the genres based on lexical measures as independent variables in a linear regression model, shows that vector spaces created from texts with high syntactic complexity, high word variation, short sentences and few long words produce better summaries.
Automatic MT Error Analysis: Hjerson Helping Addicter
Authors: Jan Berka, Ond{\v{r}}ej Bojar, Mark Fishel, Maja Popovi{\'c}, Daniel Zeman
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: General Classification, Machine Translation, Translation

We present a complex, open source tool for detailed machine translation error analysis providing the user with automatic error detection and classification, several monolingual alignment algorithms as well as with training and test corpus browsing. The tool is the result of a merge of automatic error detection and classification of Hjerson (Popovi{\'c}, 2011) and Addicter (Zeman et al., 2011) into the pipeline and web visualization of Addicter. It classifies errors into categories similar to those of Vilar et al. (2006), such as: morphological, reordering, missing words, extra words and lexical errors. The graphical user interface shows alignments in both training corpus and test data; the different classes of errors are colored. Also, the summary of errors can be displayed to provide an overall view of the MT system's weaknesses. The tool was developed in Linux, but it was tested on Windows too.