pwc-archive/papers-with-abstracts huggingface dataset:
MAT: a tool for L2 pronunciation errors annotation
Authors: Renlong Ai, Marcela Charfuelan
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Sentence

In the area of Computer Assisted Language Learning(CALL), second language (L2) learners spoken data is an important resource for analysing and annotating typical L2 pronunciation errors. The annotation of L2 pronunciation errors in spoken data is not an easy task though, normally it requires manual annotation from trained linguists or phoneticians. In order to facilitate this task, in this paper, we present the MAT tool, a web-based tool intended to facilitate the annotation of L2 learners{'} pronunciation errors at various levels. The tool has been designed taking into account recent studies on error detection in pronunciation training. It also aims at providing an easy and fast annotation process via a comprehensive and friendly user interface. The tool is based on the MARY TTS open source platform, from which it uses the components: text analyser (tokeniser, syllabifier, phonemiser), phonetic aligner and speech signal processor. Annotation results at sentence, word, syllable and phoneme levels are stored in XML format. The tool is currently under evaluation with a L2 learners spoken corpus recorded in the SPRINTER (Language Technology for Interactive, Multi-Media Online Language Learning) project.
Word Semantic Similarity for Morphologically Rich Languages
Authors: Kalliopi Zervanou, Elias Iosif, Alex Potamianos, ros
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Semantic Similarity, Semantic Textual Similarity

In this work, we investigate the role of morphology on the performance of semantic similarity for morphologically rich languages, such as German and Greek. The challenge in processing languages with richer morphology than English, lies in reducing estimation error while addressing the semantic distortion introduced by a stemmer or a lemmatiser. For this purpose, we propose a methodology for selective stemming, based on a semantic distortion metric. The proposed algorithm is tested on the task of similarity estimation between words using two types of corpus-based similarity metrics: co-occurrence-based and context-based. The performance on morphologically rich languages is boosted by stemming with the context-based metric, unlike English, where the best results are obtained by the co-occurrence-based metric. A key finding is that the estimation error reduction is different when a word is used as a feature, rather than when it is used as a target word.
LexTerm Manager: Design for an Integrated Lexicography and Terminology System
Authors: Joshua Elliot, Logan Kearsley, Jason Housley, Alan Melby
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

We present a design for a multi-modal database system for lexical information that can be accessed in either lexicographical or terminological views. The use of a single merged data model makes it easy to transfer common information between termbases and dictionaries, thus facilitating information sharing and re-use. Our combined model is based on the LMF and TMF metamodels for lexicographical and terminological databases and is compatible with both, thus allowing for the import of information from existing dictionaries and termbases, which may be transferred to the complementary view and re-exported. We also present a new Linguistic Configuration Model, analogous to a TBX XCS file, which can be used to specify multiple language-specific schemata for validating and understanding lexical information in a single database. Linguistic configurations are mutable and can be refined and evolved over time as understanding of documentary needs improves. The system is designed with a client-server architecture using the HTTP protocol, allowing for the independent implementation of multiple clients for specific use cases and easy deployment over the web.
Focusing Annotation for Semantic Role Labeling
Authors: Daniel Peterson, Martha Palmer, Shumin Wu
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Active Learning, Domain Adaptation, Language Modeling, Language Modelling, Semantic Role Labeling, Word Sense Disambiguation

Annotation of data is a time-consuming process, but necessary for many state-of-the-art solutions to NLP tasks, including semantic role labeling (SRL). In this paper, we show that language models may be used to select sentences that are more useful to annotate. We simulate a situation where only a portion of the available data can be annotated, and compare language model based selection against a more typical baseline of randomly selected data. The data is ordered using an off-the-shelf language modeling toolkit. We show that the least probable sentences provide dramatic improved system performance over the baseline, especially when only a small portion of the data is annotated. In fact, the lion{'}s share of the performance can be attained by annotating only 10-20{\%} of the data. This result holds for training a model based on new annotation, as well as when adding domain-specific annotation to a general corpus for domain adaptation.
Off-Road LAF: Encoding and Processing Annotations in NLP Workflows
Authors: Emanuele Lapponi, Erik Velldal, Stephan Oepen, Rune Lain Knudsen
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Part-Of-Speech Tagging

The Linguistic Annotation Framework (LAF) provides an abstract data model for specifying interchange representations to ensure interoperability among different annotation formats. This paper describes an ongoing effort to adapt the LAF data model as the interchange representation in complex workflows as used in the Language Analysis Portal (LAP), an on-line and large-scale processing service that is developed as part of the Norwegian branch of the Common Language Resources and Technology Infrastructure (CLARIN) initiative. Unlike several related on-line processing environments, which predominantly instantiate a distributed architecture of web services, LAP achives scalability to potentially very large data volumes through integration with the Norwegian national e-Infrastructure, and in particular job sumission to a capacity compute cluster. This setup leads to tighter integration requirements and also calls for efficient, low-overhead communication of (intermediate) processing results with workflows. We meet these demands by coupling the LAF data model with a lean, non-redundant JSON-based interchange format and integration of an agile and performant NoSQL database, allowing parallel access from cluster nodes, as the central repository of linguistic annotation.
Developing a Framework for Describing Relations among Language Resources
Authors: Penny Labropoulou, Christopher Cieri, Maria Gavrilidou
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

In this paper, we study relations holding between language resources as implemented in activities concerned with their documentation. We envision the term language resources with an inclusive definition covering datasets (corpora, lexica, ontologies, grammars, etc.), tools (including web services, workflows, platforms etc.), related publications and documentation, specifications and guidelines. However, the scope of the paper is limited to relations holding for datasets and tools. The study fosuses on the META-SHARE infrastructure and the Linguistic Data Consortium and takes into account the ISOcat DCR relations. Based on this study, we propose a taxonomy of relations, discuss their semantics and provide specifications for their use in order to cater for semantic interoperability. Issues of granularity, redundancy in codification, naming conventions and semantics of the relations are presented.
Evaluating Web-as-corpus Topical Document Retrieval with an Index of the OpenDirectory
Authors: Cl{\'e}ment de Groc, Xavier Tannier
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Machine Translation, Retrieval

This article introduces a novel protocol and resource to evaluate Web-as-corpus topical document retrieval. To the contrary of previous work, our goal is to provide an automatic, reproducible and robust evaluation for this task. We rely on the OpenDirectory (DMOZ) as a source of topically annotated webpages and index them in a search engine. With this OpenDirectory search engine, we can then easily evaluate the impact of various parameters such as the number of seed terms, queries or documents, or the usefulness of various term selection algorithms. A first fully automatic evaluation is described and provides baseline performances for this task. The article concludes with practical information regarding the availability of the index and resource files.
Word Alignment-Based Reordering of Source Chunks in PB-SMT
Authors: Santanu Pal, Sudip Kumar Naskar, B, Sivaji yopadhyay
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, Translation, Word Alignment

Reordering poses a big challenge in statistical machine translation between distant language pairs. The paper presents how reordering between distant language pairs can be handled efficiently in phrase-based statistical machine translation. The problem of reordering between distant languages has been approached with prior reordering of the source text at chunk level to simulate the target language ordering. Prior reordering of the source chunks is performed in the present work by following the target word order suggested by word alignment. The testset is reordered using monolingual MT trained on source and reordered source. This approach of prior reordering of the source chunks was compared with pre-ordering of source words based on word alignments and the traditional approach of prior source reordering based on language-pair specific reordering rules. The effects of these reordering approaches were studied on an English--Bengali translation task, a language pair with different word order. From the experimental results it was found that word alignment based reordering of the source chunks is more effective than the other reordering approaches, and it produces statistically significant improvements over the baseline system on BLEU. On manual inspection we found significant improvements in terms of word alignments.
Taalportaal: an online grammar of Dutch and Frisian
Authors: L, Frank sbergen, Carole Tiberius, Roderik Dernison
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Management

In this paper, we present the Taalportaal project. Taalportaal will create an online portal containing an exhaustive and fully searchable electronic reference of Dutch and Frisian phonology, morphology and syntax. Its content will be in English. The main aim of the project is to serve the scientific community by organizing, integrating and completing the grammatical knowledge of both languages, and to make this data accessible in an innovative way. The project is carried out by a consortium of four universities and research institutions. Content is generated in two ways: (1) by a group of authors who, starting from existing grammatical resources, write text directly in XML, and (2) by integrating the full Syntax of Dutch into the portal, after an automatic conversion from Word to XML. We discuss the projects workflow, content creation and management, the actual web application, and the way in which we plan to enrich the portals content, such as by crosslinking between topics and linking to external resources.
A Framework for Public Health Surveillance
Authors: Andrew Yates, Jon Parker, Nazli Goharian, Ophir Frieder
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval

With the rapid growth of social media, there is increasing potential to augment traditional public health surveillance methods with data from social media. We describe a framework for performing public health surveillance on Twitter data. Our framework, which is publicly available, consists of three components that work together to detect health-related trends in social media: a concept extraction component for identifying health-related concepts, a concept aggregation component for identifying how the extracted health-related concepts relate to each other, and a trend detection component for determining when the aggregated health-related concepts are trending. We describe the architecture of the framework and several components that have been implemented in the framework, identify other components that could be used with the framework, and evaluate our framework on approximately 1.5 years of tweets. While it is difficult to determine how accurately a Twitter trend reflects a trend in the real world, we discuss the differences in trends detected by several different methods and compare flu trends detected by our framework to data from Google Flu Trends.
Multilingual Test Sets for Machine Translation of Search Queries for Cross-Lingual Information Retrieval in the Medical Domain
Authors: Zde{\v{n}}ka Ure{\v{s}}ov{\'a}, Jan Haji{\v{c}}, Pavel Pecina, Ond{\v{r}}ej Du{\v{s}}ek
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Cross-Lingual Information Retrieval, Domain Adaptation, Information Retrieval, Language Modelling, Machine Translation, Retrieval, Translation

This paper presents development and test sets for machine translation of search queries in cross-lingual information retrieval in the medical domain. The data consists of the total of 1,508 real user queries in English translated to Czech, German, and French. We describe the translation and review process involving medical professionals and present a baseline experiment where our data sets are used for tuning and evaluation of a machine translation system.
A tool suite for creating question answering benchmarks
Authors: Axel-Cyrille Ngonga Ngomo, Norman Heino, Ren{\'e} Speck, Prodromos Malakasiotis
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Question Answering, Retrieval

We introduce the BIOASQ suite, a set of open-source Web tools for the creation, assessment and community-driven improvement of question answering benchmarks. The suite comprises three main tools: (1) the annotation tool supports the creation of benchmarks per se. In particular, this tool allows a team of experts to create questions and answers as well as to annotate the latter with documents, document snippets, RDF triples and ontology concepts. While the creation of questions is supported by different views and contextual information pertaining to the same question, the creation of answers is supported by the integration of several search engines and context information to facilitate the retrieval of the said answers as well as their annotation. (2) The assessment tool allows comparing several answers to the same question. Therewith, it can be used to assess the inter-annotator agreement as well as to manually evaluate automatically generated answers. (3) The third tool in the suite, the social network, aims to ensure the sustainability and iterative improvement of the benchmark by empowering communities of experts to provide insights on the questions in the benchmark. The BIOASQ suite has already been used successfully to create the 311 questions comprised in the BIOASQ question answering benchmark. It has also been evaluated by the experts who used it to create the BIOASQ benchmark.
Thematic Cohesion: measuring terms discriminatory power toward themes
Authors: Cl{\'e}ment de Groc, Xavier Tannier, Claude de Loupy
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Opinion Mining, Retrieval, Text Clustering, Translation

We present a new measure of thematic cohesion. This measure associates each term with a weight representing its discriminatory power toward a theme, this theme being itself expressed by a list of terms (a thematic lexicon). This thematic cohesion criterion can be used in many applications, such as query expansion, computer-assisted translation, or iterative construction of domain-specific lexicons and corpora. The measure is computed in two steps. First, a set of documents related to the terms is gathered from the Web by querying a Web search engine. Then, we produce an oriented co-occurrence graph, where vertices are the terms and edges represent the fact that two terms co-occur in a document. This graph can be interpreted as a recommendation graph, where two terms occurring in a same document means that they recommend each other. This leads to using a random walk algorithm that assigns a global importance value to each vertex of the graph. After observing the impact of various parameters on those importance values, we evaluate their correlation with retrieval effectiveness.
Terminology Resources and Terminology Work Benefit from Cloud Services
Authors: Tatiana Gornostay, Andrejs Vasi{\c{l}}jevs
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, Management, Translation

This paper presents the concept of the innovative platform TaaS Terminology as a Service. TaaS brings the benefits of cloud services to the user, in order to foster the creation of terminology resources and to maintain their up-to-datedness by integrating automated data extraction and user-supported clean-up of raw terminological data and sharing user-validated terminology. The platform is based on cutting-edge technologies, provides single-access-point terminology services, and facilitates the establishment of emerging trends beyond conventional praxis and static models in terminology work. A cloud-based, user-oriented, collaborative, portable, interoperable, and multilingual platform offers such terminology services as terminology project creation and sharing, data collection for translation lookup, user document upload and management, terminology extraction customisation and execution, raw terminological data management, validated terminological data export and reuse, and other terminology services.
Bidirectionnal converter between syntactic annotations : from French Treebank Dependencies to PASSAGE annotations, and back
Authors: Munshi Asadullah, Patrick Paroubek, Anne Vilnat
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

We present here part of a bidirectional converter between the French Tree-bank Dependency (FTB - DEP) annotations into the PASSAGE format. FTB - DEP is the representation used by several freely available parsers and the PASSAGE annotation was used to hand-annotate a relatively large sized corpus, used as gold-standard in the PASSAGE evaluation campaigns. Our converter will give the means to evaluate these parsers on the PASSAGE corpus. We shall illustrate the mapping of important syntactic phenomena using the corpus made of the examples of the FTB - DEP annotation guidelines, which we have hand-annotated with PASSAGE annotations and used to compute quantitative performance measures on the FTB - DEP guidelines.n this paper we will briefly introduce the two annotation formats. Then, we detail the two converters, and the rules which have been written. The last part will detail the results we obtained on the phenomenon we mostly study, the passive forms. We evaluate the converters by a double conversion, from PASSAGE to CoN LL and back to PASSAGE. We will detailed in this paper the linguistic phenomenon we detail here, the passive form.
VarClass: An Open-source Language Identification Tool for Language Varieties
Authors: Marcos Zampieri, Binyam Gebre
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Information Retrieval, Language Identification, Machine Translation, Text Categorization

This paper presents VarClass, an open-source tool for language identification available both to be downloaded as well as through a graphical user-friendly interface. The main difference of VarClass in comparison to other state-of-the-art language identification tools is its focus on language varieties. General purpose language identification tools do not take language varieties into account and our work aims to fill this gap. VarClass currently contains language models for over 27 languages in which 10 of them are language varieties. We report an average performance of over 90.5{\%} accuracy in a challenging dataset. More language models will be included in the upcoming months.
RECSA: Resource for Evaluating Cross-lingual Semantic Annotation
Authors: Achim Rettinger, Lei Zhang, Da{\v{s}}a Berovi{\'c}, Danijela Merkler, Matea Sreba{\v{c}}i{\'c}, Marko Tadi{\'c}
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Articles, Machine Translation

In recent years large repositories of structured knowledge (DBpedia, Freebase, YAGO) have become a valuable resource for language technologies, especially for the automatic aggregation of knowledge from textual data. One essential component of language technologies, which leverage such knowledge bases, is the linking of words or phrases in specific text documents with elements from the knowledge base (KB). We call this semantic annotation. In the same time, initiatives like Wikidata try to make those knowledge bases less language dependent in order to allow cross-lingual or language independent knowledge access. This poses a new challenge to semantic annotation tools which typically are language dependent and link documents in one language to a structured knowledge base grounded in the same language. Ultimately, the goal is to construct cross-lingual semantic annotation tools that can link words or phrases in one language to a structured knowledge database in any other language or to a language independent representation. To support this line of research we developed what we believe could serve as a gold standard Resource for Evaluating Cross-lingual Semantic Annotation (RECSA). We compiled a hand-annotated parallel corpus of 300 news articles in three languages with cross-lingual semantic groundings to the English Wikipedia and DBPedia. We hope that this new language resource, which is freely available, will help to establish a standard test set and methodology to comparatively evaluate cross-lingual semantic annotation technologies.
Investigating Engagement - intercultural and technological aspects of the collection, analysis, and use of the Estonian Multiparty Conversational video data
Authors: Kristiina Jokinen, Silvi Tenjes
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper we describe the goals of the Estonian corpus collection and analysis activities, and introduce the recent collection of Estonian First Encounters data. The MINT project aims at deepening our understanding of the conversational properties and practices in human interactions. We especially investigate conversational engagement and cooperation, and discuss some observations on the participants' views concerning the interaction they have been engaged.
``You Seem Aggressive!'' Monitoring Anger in a Practical Application
Authors: Felix Burkhardt
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Emotion Classification, Emotion Recognition

A monitoring system to detect emotional outbursts in day-to-day communication is presented. The anger monitor was tested in a household and in parallel in an office surrounding. Although the state of the art of emotion recognition seems sufficient for practical applications, the acquisition of good training material remains a difficult task, as cross database performance is too low to be used in this context. A solution will probably consist of the combination of carefully drafted general training databases and the development of usability concepts to (re-) train the monitor in the field.