pwc-archive/papers-with-abstracts huggingface dataset:
Access control by query rewriting: the case of KorAP
Authors: Piotr Ba{\'n}ski, Nils Diewald, Michael Hanl, Marc Kupietz, Andreas Witt
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

We present an approach to an aspect of managing complex access scenarios to large and heterogeneous corpora that involves handling user queries that, intentionally or due to the complexity of the queried resource, target texts or annotations outside of the given userÂ’s permissions. We first outline the overall architecture of the corpus analysis platform KorAP, devoting some attention to the way in which it handles multiple query languages, by implementing ISO CQLF (Corpus Query Lingua Franca), which in turn constitutes a component crucial for the functionality discussed here. Next, we look at query rewriting as it is used by KorAP and zoom in on one kind of this procedure, namely the rewriting of queries that is forced by data access restrictions.
Basque Speecon-like and Basque SpeechDat MDB-600: speech databases for the development of ASR technology for Basque
Authors: Igor Odriozola, Inma Hernaez, Mar{\'\i}a In{\'e}s Torres, Luis Javier Rodriguez-Fuentes, Mikel Penagarikano, Eva Navas
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: speech-recognition, Speech Recognition

This paper introduces two databases specifically designed for the development of ASR technology for the Basque language: the Basque Speecon-like database and the Basque SpeechDat MDB-600 database. The former was recorded in an office environment according to the Speecon specifications, whereas the later was recorded through mobile telephones according to the SpeechDat specifications. Both databases were created under an initiative that the Basque Government started in 2005, a program called ADITU, which aimed at developing speech technologies for Basque. The databases belong to the Basque Government. A comprehensive description of both databases is provided in this work, highlighting the differences with regard to their corresponding standard specifications. The paper also presents several initial experimental results for both databases with the purpose of validating their usefulness for the development of speech recognition technology. Several applications already developed with the Basque Speecon-like database are also described. Authors aim to make these databases widely known to the community as well, and foster their use by other groups.
DiVE-Arabic: Gulf Arabic Dialogue in a Virtual Environment
Authors: Andrew Gargett, Sam Hellmuth, Ghazi AlGethami
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

Documentation of communicative behaviour across languages seems at a crossroads. While methods for collecting data on spoken or written communication, backed up by computational techniques, are evolving, the actual data being collected remain largely the same. Inspired by the efforts of some innovative researchers who are directly tackling the various obstacles to investigating language in the field (e.g. see various papers collected in Enfield {\&} Stivers 2007), we report here about ongoing work to solve the general problem of collecting in situ data for situated linguistic interaction. The initial stages of this project have involved employing a portable format designed to increase range and flexibility of doing such collections in the field. Our motivation is to combine this with a parallel data set for a typologically distinct language, in order to contribute a parallel corpus of situated language use.
A multimodal interpreter for 3D visualization and animation of verbal concepts
Authors: Coline Claude-Lachenaud, {\'E}ric Charton, Beno{\^\i}t Ozell, Michel Gagnon
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Text Generation

We present an algorithm intended to visually represent the sense of verb related to an object described in a text sequence, as a movement in 3D space. We describe a specific semantic analyzer, based on a standard verbal ontology, dedicated to the interpretation of action verbs as spatial actions. Using this analyzer, our system build a generic 3D graphical path for verbal concepts allowing space representation, listed as SelfMotion concepts in the FrameNet ontology project. The object movement is build by first extracting the words and enriching them with the semantic analyzer. Then, weight tables, necessary to obtain characteristics values (orientation, shape, trajectory...) for the verb are used in order to get a 3D path, as realist as possible. The weight tables were created to make parallel between features defined for SelfMotion verbal concept (some provided by FrameNet, other determined during the project) and values used in the final algorithm used to create 3D moving representations from input text. We evaluate our analyzer on a corpus of short sentences and presents our results.
Erlangen-CLP: A Large Annotated Corpus of Speech from Children with Cleft Lip and Palate
Authors: Tobias Bocklet, Andreas Maier, Korbinian Riedhammer, Ulrich Eysholdt, Elmar N{\"o}th
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

In this paper we describe Erlangen-CLP, a large speech database of children with Cleft Lip and Palate. More than 800 German children with CLP (most of them between 4 and 18 years old) and 380 age matched control speakers spoke the semi-standardized PLAKSS test that consists of words with all German phonemes in different positions. So far 250 CLP speakers were manually transcribed, 120 of these were analyzed by a speech therapist and 27 of them by four additional therapists. The tharapists marked 6 different processes/criteria like pharyngeal backing and hypernasality which typically occur in speech of people with CLP. We present detailed statistics about the the marked processes and the inter-rater agreement.
Classifying Inconsistencies in DBpedia Language Specific Chapters
Authors: Elena Cabrio, Serena Villata, G, Fabien on
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Abstract Argumentation, Question Answering

This paper proposes a methodology to identify and classify the semantic relations holding among the possible different answers obtained for a certain query on DBpedia language specific chapters. The goal is to reconcile information provided by language specific DBpedia chapters to obtain a consistent results set. Starting from the identified semantic relations between two pieces of information, we further classify them as positive or negative, and we exploit bipolar abstract argumentation to represent the result set as a unique graph, where using argumentation semantics we are able to detect the (possible multiple) consistent sets of elements of the query result. We experimented with the proposed methodology over a sample of triples extracted from 10 DBpedia ontology properties. We define the LingRel ontology to represent how the extracted information from different chapters is related to each other, and we map the properties of the LingRel ontology to the properties of the SIOC-Argumentation ontology to built argumentation graphs. The result is a pilot resource that can be profitably used both to train and to evaluate NLP applications querying linked data in detecting the semantic relations among the extracted values, in order to output consistent information sets.
TVD: A Reproducible and Multiply Aligned TV Series Dataset
Authors: Anindya Roy, Camille Guinaudeau, Herv{\'e} Bredin, Claude Barras
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Dynamic Time Warping, Information Retrieval, Retrieval, Sentiment Analysis, Word Similarity

We introduce a new dataset built around two TV series from different genres, The Big Bang Theory, a situation comedy and Game of Thrones, a fantasy drama. The dataset has multiple tracks extracted from diverse sources, including dialogue (manual and automatic transcripts, multilingual subtitles), crowd-sourced textual descriptions (brief episode summaries, longer episode outlines) and various metadata (speakers, shots, scenes). The paper describes the dataset and provide tools to reproduce it for research purposes provided one has legally acquired the DVD set of the series. Tools are also provided to temporally align a major subset of dialogue and description tracks, in order to combine complementary information present in these tracks for enhanced accessibility. For alignment, we consider tracks as comparable corpora and first apply an existing algorithm for aligning such corpora based on dynamic time warping and TFIDF-based similarity scores. We improve this baseline algorithm using contextual information, WordNet-based word similarity and scene location information. We report the performance of these algorithms on a manually aligned subset of the data. To highlight the interest of the database, we report a use case involving rich speech retrieval and propose other uses.
Towards Electronic SMS Dictionary Construction: An Alignment-based Approach
Authors: C{\'e}dric Lopez, Best, Reda ji, Mathieu Roche, Rachel Panckhurst
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

In this paper, we propose a method for aligning text messages (entitled AlignSMS) in order to automatically build an SMS dictionary. An extract of 100 text messages from the 88milSMS corpus (Panckhurst el al., 2013, 2014) was used as an initial test. More than 90,000 authentic text messages in French were collected from the general public by a group of academics in the south of France in the context of the sud4science project (http://www.sud4science.org). This project is itself part of a vast international SMS data collection project, entitled sms4science (http://www.sms4science.org, Fairon et al. 2006, Cougnon, 2014). After corpus collation, pre-processing and anonymisation (Accorsi et al., 2012, Patel et al., 2013), we discuss how raw anonymised text messages can be transcoded into normalised text messages, using a statistical alignment method. The future objective is to set up a hybrid (symbolic/statistic) approach based on both grammar rules and our statistical AlignSMS method.
TALC-sef A Manually-Revised POS-TAgged Literary Corpus in Serbian, English and French
Authors: Antonio Balvet, Dejan Stosic, Aleks Miletic, ra
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: POS, POS Tagging

In this paper, we present a parallel literary corpus for Serbian, English and French, the TALC-sef corpus. The corpus includes a manually-revised pos-tagged reference Serbian corpus of over 150,000 words. The initial objective was to devise a reference parallel corpus in the three languages, both for literary and linguistic studies. The French and English sub-corpora had been pos-tagged from the onset, using TreeTagger (Schmid, 1994), but the corpus lacked, until now, a tagged version of the Serbian sub-corpus. Here, we present the original parallel literary corpus, then we address issues related to pos-tagging a large collection of Serbian text: from the conception of an appropriate tagset for Serbian, to the choice of an automatic pos-tagger adapted to the task, and then to some quantitative and qualitative results. We then move on to a discussion of perspectives in the near future for further annotations of the whole parallel corpus.
Crowdsourcing for Evaluating Machine Translation Quality
Authors: Shinsuke Goto, Donghui Lin, Toru Ishida
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, Sentence, Translation

The recent popularity of machine translation has increased the demand for the evaluation of translations. However, the traditional evaluation approach, manual checking by a bilingual professional, is too expensive and too slow. In this study, we confirm the feasibility of crowdsourcing by analyzing the accuracy of crowdsourcing translation evaluations. We compare crowdsourcing scores to professional scores with regard to three metrics: translation-score, sentence-score, and system-score. A Chinese to English translation evaluation task was designed using around the NTCIR-9 PATENT parallel corpus with the goal being 5-range evaluations of adequacy and fluency. The experiment shows that the average score of crowdsource workers well matches professional evaluation results. The system-score comparison strongly indicates that crowdsourcing can be used to find the best translation system given the input of 10 source sentence.
The Halliday Centre Tagger: An Online Platform for Semi-automatic Text Annotation and Analysis
Authors: Billy T. M. Wong, Ian C. Chow, Jonathan J. Webster, Hengbin Yan
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: text annotation

This paper reports the latest development of The Halliday Centre Tagger (the Tagger), an online platform provided with semi-automatic features to facilitate text annotation and analysis. The Tagger is featured for its web-based architecture with all functionalities and file storage space provided online, and a theory-neutral design where users can define their own labels for annotating various kinds of linguistic information. The Tagger is currently optimized for text annotation of Systemic Functional Grammar (SFG), providing by default a pre-defined set of SFG grammatical features, and the function of automatic identification of process types for English verbs. Apart from annotation, the Tagger also offers the features of visualization and summarization to aid text analysis. The visualization feature combines and illustrates multi-dimensional layers of annotation in a unified way of presentation, while the summarization feature categorizes annotated entries according to different SFG systems, i.e., transitivity, theme, logical-semantic relations, etc. Such features help users identify grammatical patterns in an annotated text.
Flow Graph Corpus from Recipe Texts
Authors: Shinsuke Mori, Hirokuni Maeta, Yoko Yamakata, Tetsuro Sasada
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: ARC, coreference-resolution, Coreference Resolution, Domain Adaptation, named-entity-recognition, Named Entity Recognition, Named Entity Recognition (NER)

In this paper, we present our attempt at annotating procedural texts with a flow graph as a representation of understanding. The domain we focus on is cooking recipe. The flow graphs are directed acyclic graphs with a special root node corresponding to the final dish. The vertex labels are recipe named entities, such as foods, tools, cooking actions, etc. The arc labels denote relationships among them. We converted 266 Japanese recipe texts into flow graphs manually. 200 recipes are randomly selected from a web site and 66 are of the same dish. We detail the annotation framework and report some statistics on our corpus. The most typical usage of our corpus may be automatic conversion from texts to flow graphs which can be seen as an entire understanding of procedural texts. With our corpus, one can also try word segmentation, named entity recognition, predicate-argument structure analysis, and coreference resolution.
Freepal: A Large Collection of Deep Lexico-Syntactic Patterns for Relation Extraction
Authors: Johannes Kirschnick, Alan Akbik, Holmer Hemsen
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Entity Linking, Relation, Relation Extraction

The increasing availability and maturity of both scalable computing architectures and deep syntactic parsers is opening up new possibilities for Relation Extraction (RE) on large corpora of natural language text. In this paper, we present Freepal, a resource designed to assist with the creation of relation extractors for more than 5,000 relations defined in the Freebase knowledge base (KB). The resource consists of over 10 million distinct lexico-syntactic patterns extracted from dependency trees, each of which is assigned to one or more Freebase relations with different confidence strengths. We generate the resource by executing a large-scale distant supervision approach on the ClueWeb09 corpus to extract and parse over 260 million sentences labeled with Freebase entities and relations. We make Freepal freely available to the research community, and present a web demonstrator to the dataset, accessible from free-pal.appspot.com.
Correcting and Validating Syntactic Dependency in the Spoken French Treebank Rhapsodie
Authors: Rachel Bawden, Marie-Am{\'e}lie Botalla, Kim Gerdes, Sylvain Kahane
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

This article presents the methods, results, and precision of the syntactic annotation process of the Rhapsodie Treebank of spoken French. The Rhapsodie Treebank is an 33,000 word corpus annotated for prosody and syntax, licensed in its entirety under Creative Commons. The syntactic annotation contains two levels: a macro-syntactic level, containing a segmentation into illocutionary units (including discourse markers, parentheses {\^a}¦) and a micro-syntactic level including dependency relations and various paradigmatic structures, called pile constructions, the latter being particularly frequent and diverse in spoken language. The micro-syntactic annotation process, presented in this paper, includes a semi-automatic preparation of the transcription, the application of a syntactic dependency parser, transcoding of the parsing results to the Rhapsodie annotation scheme, manual correction by multiple annotators followed by a validation process, and finally the application of coherence rules that check common errors. The good inter-annotator agreement scores are presented and analyzed in greater detail. The article also includes the list of functions used in the dependency annotation and for the distinction of various pile constructions and presents the ideas underlying these choices.
Morfeusz Reloaded
Authors: Marcin Woli{\'n}ski
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Morphological Analysis, Morphological Tagging

The paper presents recent developments in Morfeusz â€• a morphological analyser for Polish. The program, being already a fundamental resource for processing Polish, has been reimplemented with some important changes in the tagset, some new options, added information on proper names, and ability to perform simple prefix derivation. The present version of Morfeusz (including its dictionaries) is made available under the very liberal 2-clause BSD license. The program can be downloaded from http://sgjp.pl/morfeusz/.
Modeling, Managing, Exposing, and Linking Ontologies with a Wiki-based Tool
Authors: Mauro Dragoni, Alessio Bosca, Matteo Casu, Andi Rexha
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Decision Making, Information Retrieval, Management

In the last decade, the need of having effective and useful tools for the creation and the management of linguistic resources significantly increased. One of the main reasons is the necessity of building linguistic resources (LRs) that, besides the goal of expressing effectively the domain that users want to model, may be exploited in several ways. In this paper we present a wiki-based collaborative tool for modeling ontologies, and more in general any kind of linguistic resources, called MoKi. This tool has been customized in the context of an EU-funded project for addressing three important aspects of LRs modeling: (i) the exposure of the created LRs, (ii) for providing features for linking the created resources to external ones, and (iii) for producing multilingual LRs in a safe manner.
A Model for Processing Illocutionary Structures and Argumentation in Debates
Authors: Kasia Budzynska, Mathilde Janier, Chris Reed, Patrick Saint-Dizier, Manfred Stede, Olena Yakorska
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

In this paper, we briefly present the objectives of Inference Anchoring Theory (IAT) and the formal structure which is proposed for dialogues. Then, we introduce our development corpus, and a computational model designed for the identification of discourse minimal units in the context of argumentation and the illocutionary force associated with each unit. We show the categories of resources which are needed and how they can be reused in different contexts.
Student achievement and French sentence repetition test scores
Authors: Deryle Lonsdale, Benjamin Millard
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Sentence, speech-recognition, Speech Recognition

Sentence repetition (SR) tests are one way of probing a language learner{'}s oral proficiency. Test-takers listen to a set of carefully engineered sentences of varying complexity one-by-one, and then try to repeat them back as exactly as possible. In this paper we explore how well an SR test that we have developed for French corresponds with the test-taker{'}s achievement levels, represented by proficiency interview scores and by college class enrollment. We describe how we developed our SR test items using various language resources, and present pertinent facts about the test administration. The responses were scored by humans and also by a specially designed automatic speech recognition (ASR) engine; we sketch both scoring approaches. Results are evaluated in several ways: correlations between human and ASR scores, item response analysis to quantify the relative difficulty of the items, and criterion-referenced analysis setting thresholds of consistency across proficiency levels. We discuss several observations and conclusions prompted by the analyses, and suggestions for future work.
Human annotation of ASR error regions: Is ``gravity'' a sharable concept for human annotators?
Authors: Daniel Luzzati, Cyril Grouin, Ioana Vasilescu, Martine Adda-Decker, Eric Bilinski, Nathalie Camelin, Juliette Kahn, Carole Lailler, Lori Lamel, Sophie Rosset
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Named Entity Recognition (NER), Speech Recognition

This paper is concerned with human assessments of the severity of errors in ASR outputs. We did not design any guidelines so that each annotator involved in the study could consider the {``}seriousness{''} of an ASR error using their own scientific background. Eight human annotators were involved in an annotation task on three distinct corpora, one of the corpora being annotated twice, hiding this annotation in duplicate to the annotators. None of the computed results (inter-annotator agreement, edit distance, majority annotation) allow any strong correlation between the considered criteria and the level of seriousness to be shown, which underlines the difficulty for a human to determine whether a ASR error is serious or not.
SwissAdmin: A multilingual tagged parallel corpus of press releases
Authors: Yves Scherrer, Luka Nerima, Lorenza Russo, Maria Ivanova, Eric Wehrli
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Language Identification, Sentence

SwissAdmin is a new multilingual corpus of press releases from the Swiss Federal Administration, available in German, French, Italian and English. We provide SwissAdmin in three versions: (i) plain texts of approximately 6 to 8 million words per language; (ii) sentence-aligned bilingual texts for each language pair; (iii) a part-of-speech-tagged version consisting of annotations in both the Universal tagset and the richer Fips tagset, along with grammatical functions, verb valencies and collocations. The SwissAdmin corpus is freely available at www.latl.unige.ch/swissadmin.