pwc-archive/papers-with-abstracts huggingface dataset:
Constructing and exploiting an automatically annotated resource of legislative texts
Authors: Stefan H{\"o}fler, Kyoko Sugisaki
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Translation

In this paper, we report on the construction of a resource of Swiss legislative texts that is automatically annotated with structural, morphosyntactic and content-related information, and we discuss the exploitation of this resource for the purposes of legislative drafting, legal linguistics and translation and for the evaluation of legislation. Our resource is based on the classified compilation of Swiss federal legislation. All texts contained in the classified compilation exist in German, French and Italian, some of them are also available in Romansh and English. Our resource is currently being exploited (a) as a testing environment for developing methods of automated style checking for legislative drafts, (b) as the basis of a statistical multilingual word concordance, and (c) for the empirical evaluation of legislation. The paper describes the domain- and language-specific procedures that we have implemented to provide the automatic annotations needed for these applications.
GenitivDB --- a Corpus-Generated Database for German Genitive Classification
Authors: Roman Schneider
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Classification, General Classification

We present a novel NLP resource for the explanation of linguistic phenomena, built and evaluated exploring very large annotated language corpora. For the compilation, we use the German Reference Corpus (DeReKo) with more than 5 billion word forms, which is the largest linguistic resource worldwide for the study of contemporary written German. The result is a comprehensive database of German genitive formations, enriched with a broad range of intra- und extralinguistic metadata. It can be used for the notoriously controversial classification and prediction of genitive endings (short endings, long endings, zero-marker). We also evaluate the main factors influencing the use of specific endings. To get a general idea about a factorÂ’s influences and its side effects, we calculate chi-square-tests and visualize the residuals with an association plot. The results are evaluated against a gold standard by implementing tree-based machine learning algorithms. For the statistical analysis, we applied the supervised LMT Logistic Model Trees algorithm, using the WEKA software. We intend to use this gold standard to evaluate GenitivDB, as well as to explore methodologies for a predictive genitive model.
Resources in Conflict: A Bilingual Valency Lexicon vs. a Bilingual Treebank vs. a Linguistic Theory
Authors: Jana {\v{S}}indlerov{\'a}, Zde{\v{n}}ka Ure{\v{s}}ov{\'a}, Eva Fucikova
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation

In this paper, we would like to exemplify how a syntactically annotated bilingual treebank can help us in exploring and revising a developed linguistic theory. On the material of the Prague Czech-English Dependency Treebank we observe sentences in which an Addressee argument in one language is linked translationally to a Patient argument in the other one, and make generalizations about the theoretical grounds of the argument non-correspondences and its relations to the valency theory beyond the annotation practice. Exploring verbs of three semantic classes (Judgement verbs, Teaching verbs and Attempt Suasion verbs) we claim that the Functional Generative Description argument labelling is highly dependent on the morphosyntactic realization of the individual participants, which then results in valency frame differences. Nevertheless, most of the differences can be overcome without substantial changes to the linguistic theory itself.
The NewSoMe Corpus: A Unifying Opinion Annotation Framework across Genres and in Multiple Languages
Authors: Roser Saur{\'\i}, Judith Domingo, Toni Badia
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Opinion Mining

We present the NewSoMe (News and Social Media) Corpus, a set of subcorpora with annotations on opinion expressions across genres (news reports, blogs, product reviews and tweets) and covering multiple languages (English, Spanish, Catalan and Portuguese). NewSoMe is the result of an effort to increase the opinion corpus resources available in languages other than English, and to build a unifying annotation framework for analyzing opinion in different genres, including controlled text, such as news reports, as well as different types of user generated contents (UGC). Given the broad design of the resource, most of the annotation effort were carried out resorting to crowdsourcing platforms: Amazon Mechanical Turk and CrowdFlower. This created an excellent opportunity to research on the feasibility of crowdsourcing methods for annotating big amounts of text in different languages.
Buy one get one free: Distant annotation of Chinese tense, event type and modality
Authors: Nianwen Xue, Yuchen Zhang
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, Vocal Bursts Type Prediction, Word Alignment

We describe a {``}distant annotation{''} method where we mark up the semantic tense, event type, and modality of Chinese events via a word-aligned parallel corpus. We first map Chinese verbs to their English counterparts via word alignment, and then annotate the resulting English text spans with coarse-grained categories for semantic tense, event type, and modality that we believe apply to both English and Chinese. Because English has richer morpho-syntactic indicators for semantic tense, event type and modality than Chinese, our intuition is that this distant annotation approach will yield more consistent annotation than if we annotate the Chinese side directly. We report experimental results that show stable annotation agreement statistics and that event type and modality have significant influence on tense prediction. We also report the size of the annotated corpus that we have obtained, and how different domains impact annotation consistency.
Multimodal dialogue segmentation with gesture post-processing
Authors: Kodai Takahashi, Masashi Inoue
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Segmentation

We investigate an automatic dialogue segmentation method using both verbal and non-verbal modalities. Dialogue contents are used for the initial segmentation of dialogue; then, gesture occurrences are used to remove the incorrect segment boundaries. A unique characteristic of our method is to use verbal and non-verbal information separately. We use a three-party dialogue that is rich in gesture as data. The transcription of the dialogue is segmented into topics without prior training by using the TextTiling and U00 algorithm. Some candidates for segment boundaries - where the topic continues - are irrelevant. Those boundaries can be found and removed by locating gestures that stretch over the boundary candidates. This ltering improves the segmentation accuracy of text-only segmentation.
The Dangerous Myth of the Star System
Authors: Andr{\'e} Bittar, Luca Dini, Sigrid Maurel, Mathieu Ruhlmann
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Named Entity Recognition (NER), Opinion Mining, Sentiment Analysis

In recent years we have observed two parallel trends in computational linguistics research and e-commerce development. On the research side, there has been an increasing interest in algorithms and approaches that are able to capture the polarity of opinions expressed by users on products, institutions and services. On the other hand, almost all big e-commerce and aggregator sites are by now providing users the possibility of writing comments and expressing their appreciation with a numeric score (usually represented as a number of stars). This generates the impression that the work carried out in the research community is made partially useless (at least for economic exploitation) by an evolution in web practices. In this paper we describe an experiment on a large corpus which shows that the score judgments provided by users are often conflicting with the text contained in the opinion, and to such a point that a rule-based opinion mining system can be demonstrated to perform better than the users themselves in ranking their opinions.
Comparison of the Impact of Word Segmentation on Name Tagging for Chinese and Japanese
Authors: Hai-Bo Li, Masato Hagiwara, Qi Li, Heng Ji
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Chinese Word Segmentation, Segmentation

Word Segmentation is usually considered an essential step for many Chinese and Japanese Natural Language Processing tasks, such as name tagging. This paper presents several new observations and analysis on the impact of word segmentation on name tagging; (1). Due to the limitation of current state-of-the-art Chinese word segmentation performance, a character-based name tagger can outperform its word-based counterparts for Chinese but not for Japanese; (2). It is crucial to keep segmentation settings (e.g. definitions, specifications, methods) consistent between training and testing for name tagging; (3). As long as (2) is ensured, the performance of word segmentation does not have appreciable impact on Chinese and Japanese name tagging.
CoRoLa --- The Reference Corpus of Contemporary Romanian Language
Authors: Verginica Barbu Mititelu, Elena Irimia, Dan Tufi{\textcommabelow{s}}
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Lemmatization, Sentence

We present the project of creating CoRoLa, a reference corpus of contemporary Romanian (from 1945 onwards). In the international context, the project finds its place among the initiatives of gathering huge collections of texts, of pre-processing and annotating them at several levels, and also of documenting them with metadata (CMDI). Our project is a joined effort of two institutes of the Romanian Academy. We foresee a corpus of more than 500 million word forms, covering all functional styles of the language. Although the vast majority of texts will be in written form, we target about 300 hours of oral texts, too, obligatorily with associated transcripts. Most of the texts will be from books, while the rest will be harvested from newspapers, booklets, technical reports, etc. The pre-processing includes cleaning the data and harmonising the diacritics, sentence splitting and tokenization. Annotation will be done at a morphological level in a first stage, followed by lemmatization, with the possibility of adding syntactic, semantic and discourse annotation in a later stage. A core of CoRoLa is described in the article. The target users of our corpus will be researchers in linguistics and language processing, teachers of Romanian, students.
Building a reference lexicon for countability in English
Authors: Tibor Kiss, Francis Jeffry Pelletier, Tobias Stadtfeld
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

The present paper describes the construction of a resource to determine the lexical preference class of a large number of English noun-senses ({\$}{\textbackslash}approx{\$} 14,000) with respect to the distinction between mass and count interpretations. In constructing the lexicon, we have employed a questionnaire-based approach based on existing resources such as the Open ANC ({\textbackslash}url{http://www.anc.org}) and WordNet {\textbackslash}cite{Miller95}. The questionnaire requires annotators to answer six questions about a noun-sense pair. Depending on the answers, a given noun-sense pair can be assigned to fine-grained noun classes, spanning the area between count and mass. The reference lexicon contains almost 14,000 noun-sense pairs. An initial data set of 1,000 has been annotated together by four native speakers, while the remaining 12,800 noun-sense pairs have been annotated in parallel by two annotators each. We can confirm the general feasibility of the approach by reporting satisfactory values between 0.694 and 0.755 in inter-annotator agreement using Krippendorff{'}s {\$}{\textbackslash}alpha{\$}.
The LIMA Multilingual Analyzer Made Free: FLOSS Resources Adaptation and Correction
Authors: Ga{\"e}l de Chalendar
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Morphological Analysis, Part-Of-Speech Tagging

At CEA LIST, we have decided to release our multilingual analyzer LIMA as Free software. As we were not proprietary of all the language resources used we had to select and adapt free ones in order to attain results good enough and equivalent to those obtained with our previous ones. For English and French, we found and adapted a full-form dictionary and an annotated corpus for learning part-of-speech tagging models.
A SICK cure for the evaluation of compositional distributional semantic models
Authors: Marco Marelli, Stefano Menini, Marco Baroni, Luisa Bentivogli, Raffaella Bernardi, Roberto Zamparelli
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Natural Language Inference, Sentence

Shared and internationally recognized benchmarks are fundamental for the development of any computational system. We aim to help the research community working on compositional distributional semantic models (CDSMs) by providing SICK (Sentences Involving Compositional Knowldedge), a large size English benchmark tailored for them. SICK consists of about 10,000 English sentence pairs that include many examples of the lexical, syntactic and semantic phenomena that CDSMs are expected to account for, but do not require dealing with other aspects of existing sentential data sets (idiomatic multiword expressions, named entities, telegraphic language) that are not within the scope of CDSMs. By means of crowdsourcing techniques, each pair was annotated for two crucial semantic tasks: relatedness in meaning (with a 5-point rating scale as gold score) and entailment relation between the two elements (with three possible gold labels: entailment, contradiction, and neutral). The SICK data set was used in SemEval-2014 Task 1, and it freely available for research purposes.
Twente Debate Corpus --- A Multimodal Corpus for Head Movement Analysis
Authors: Bayu Rahayudi, Ronald Poppe, Dirk Heylen
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

This paper introduces a multimodal discussion corpus for the study into head movement and turn-taking patterns in debates. Given that participants either acted alone or in a pair, cooperation and competition and their nonverbal correlates can be analyzed. In addition to the video and audio of the recordings, the corpus contains automatically estimated head movements, and manual annotations of who is speaking and who is looking where. The corpus consists of over 2 hours of debates, in 6 groups with 18 participants in total. We describe the recording setup and present initial analyses of the recorded data. We found that the person who acted as single debater speaks more and also receives more attention compared to the other debaters, also when corrected for the time speaking. We also found that a single debater was more likely to speak after a team debater. Future work will be aimed at further analysis of the relation between speaking and looking patterns, the outcome of the debate and perceived dominance of the debaters.
The EASR Corpora of European Portuguese, French, Hungarian and Polish Elderly Speech
Authors: Annika H{\"a}m{\"a}l{\"a}inen, Jairo Avelar, Silvia Rodrigues, Miguel Sales Dias, Artur Kolesi{\'n}ski, Tibor Fegy{\'o}, G{\'e}za N{\'e}meth, Petra Csob{\'a}nka, Karine Lan, David Hewson
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Speech Recognition

Currently available speech recognisers do not usually work well with elderly speech. This is because several characteristics of speech (e.g. fundamental frequency, jitter, shimmer and harmonic noise ratio) change with age and because the acoustic models used by speech recognisers are typically trained with speech collected from younger adults only. To develop speech-driven applications capable of successfully recognising elderly speech, this type of speech data is needed for training acoustic models from scratch or for adapting acoustic models trained with younger adultsÂ’ speech. However, the availability of suitable elderly speech corpora is still very limited. This paper describes an ongoing project to design, collect, transcribe and annotate large elderly speech corpora for four European languages: Portuguese, French, Hungarian and Polish. The Portuguese, French and Polish corpora contain read speech only, whereas the Hungarian corpus also contains spontaneous command and control type of speech. Depending on the language in question, the corpora contain 76 to 205 hours of speech collected from 328 to 986 speakers aged 60 and over. The final corpora will come with manually verified orthographic transcriptions, as well as annotations for filled pauses, noises and damaged words.
Sharing Cultural Heritage: the Clavius on the Web Project
Authors: Matteo Abrate, Angelo Mario Del Grosso, Emiliano Giovannetti, Angelica Lo Duca, Damiana Luzzi, Lorenzo Mancini, Andrea Marchetti, Irene Pedretti, Silvia Piccini
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: LEMMA, Lemmatization, Morphological Tagging

In the last few years the amount of manuscripts digitized and made available on the Web has been constantly increasing. However, there is still a considarable lack of results concerning both the explicitation of their content and the tools developed to make it available. The objective of the Clavius on the Web project is to develop a Web platform exposing a selection of Christophorus Clavius letters along with three different levels of analysis: linguistic, lexical and semantic. The multilayered annotation of the corpus involves a XML-TEI encoding followed by a tokenization step where each token is univocally identified through a CTS urn notation and then associated to a part-of-speech and a lemma. The text is lexically and semantically annotated on the basis of a lexicon and a domain ontology, the former structuring the most relevant terms occurring in the text and the latter representing the domain entities of interest (e.g. people, places, etc.). Moreover, each entity is connected to linked and non linked resources, including DBpedia and VIAF. Finally, the results of the three layers of analysis are gathered and shown through interactive visualization and storytelling techniques. A demo version of the integrated architecture was developed.
3D Face Tracking and Multi-Scale, Spatio-temporal Analysis of Linguistically Significant Facial Expressions and Head Positions in ASL
Authors: Bo Liu, Jingjing Liu, Xiang Yu, Dimitris Metaxas, Carol Neidle
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Sign Language Recognition

Essential grammatical information is conveyed in signed languages by clusters of events involving facial expressions and movements of the head and upper body. This poses a significant challenge for computer-based sign language recognition. Here, we present new methods for the recognition of nonmanual grammatical markers in American Sign Language (ASL) based on: (1) new 3D tracking methods for the estimation of 3D head pose and facial expressions to determine the relevant low-level features; (2) methods for higher-level analysis of component events (raised/lowered eyebrows, periodic head nods and head shakes) used in grammatical markingsâ€•with differentiation of temporal phases (onset, core, offset, where appropriate), analysis of their characteristic properties, and extraction of corresponding features; (3) a 2-level learning framework to combine low- and high-level features of differing spatio-temporal scales. This new approach achieves significantly better tracking and recognition results than our previous methods.
Exploring factors that contribute to successful fingerspelling comprehension
Authors: Leah Geer, Jonathan Keane
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

Using a novel approach, we examine which cues in a fingerspelling stream, namely holds or transitions, allow for more successful comprehension by students learning American Sign Language (ASL). Sixteen university-level ASL students participated in this study. They were shown video clips of a native signer fingerspelling common English words. Clips were modified in the following ways: all were slowed down to half speed, one-third of the clips were modified to black out the transition portion of the fingerspelling stream, and one-third modified to have holds blacked out. The remaining third of clips were free of blacked out portions, which we used to establish a baseline of comprehension. Research by Wilcox (1992), among others, suggested that transitions provide more rich information, and thus items with the holds blacked out should be easier to comprehend than items with the transitions blacked out. This was not found to be the case here. Students achieved higher comprehension scores when hold information was provided. Data from this project can be used to design training tools to help students become more proficient at fingerspelling comprehension, a skill with which most students struggle.
The DARE Corpus: A Resource for Anaphora Resolution in Dialogue Based Intelligent Tutoring Systems
Authors: Nobal Niraula, Vasile Rus, Rajendra Banjade, Dan Stefanescu, William Baggett, Brent Morgan
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

We describe the DARE corpus, an annotated data set focusing on pronoun resolution in tutorial dialogue. Although data sets for general purpose anaphora resolution exist, they are not suitable for dialogue based Intelligent Tutoring Systems. To the best of our knowledge, no data set is currently available for pronoun resolution in dialogue based intelligent tutoring systems. The described DARE corpus consists of 1,000 annotated pronoun instances collected from conversations between high-school students and the intelligent tutoring system DeepTutor. The data set is publicly available.
On the annotation of TMX translation memories for advanced leveraging in computer-aided translation
Authors: Mikel Forcada
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, Translation

The term advanced leveraging refers to extensions beyond the current usage of translation memory (TM) in computer-aided translation (CAT). One of these extensions is the ability to identify and use matches on the sub-segment level ― for instance, using sub-sentential elements when segments are sentences― to help the translator when a reasonable fuzzy-matched proposal is not available; some such functionalities have started to become available in commercial CAT tools. Resources such as statistical word aligners, external machine translation systems, glossaries and term bases could be used to identify and annotate segment-level translation units at the sub-segment level, but there is currently no single, agreed standard supporting the interchange of sub-segmental annotation of translation memories to create a richer translation resource. This paper discusses the capabilities and limitations of some current standards, envisages possible alternatives, and ends with a tentative proposal which slightly abuses (repurposes) the usage of existing elements in the TMX standard.