pwc-archive/papers-with-abstracts huggingface dataset:
A Morphological Analyzer For Wolof Using Finite-State Techniques
Authors: Cheikh M. Bamba Dione
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Morphological Analysis

This paper reports on the design and implementation of a morphological analyzer for Wolof. The main motivation for this work is to obtain a linguistically motivated tool using finite-state techniques. The finite-state technology is especially attractive in dealing with human language morphologies. Finite-state transducers (FST) are fast, efficient and can be fully reversible, enabling users to perform analysis as well as generation. Hence, I use this approach to construct a new FST tool for Wolof, as a first step towards a computational grammar for the language in the Lexical Functional Grammar framework. This article focuses on the methods used to model complex morphological issues and on developing strategies to limit ambiguities. It discusses experimental evaluations conducted to assess the performance of the analyzer with respect to various statistical criteria. In particular, I also wanted to create morphosyntactically annotated resources for Wolof, obtained by automatically analyzing text corpora with a computational morphology.
Designing a search interface for a Spanish learner spoken corpus: the end-user's evaluation
Authors: Leonardo Campillos Llanos
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Language Acquisition

This article summarizes the evaluation process of an interface under development to consult an oral corpus of learners of Spanish as a Foreign Language. The databank comprises 40 interviews with students with over 9 different mother tongues collected for Error Analysis. XML mark-up is used to code the information about the learners and their errors (with an explanation), and the search tool makes it is possible to look up these errors and to listen to the utterances where they appear. The formative evaluation was performed to improve the interface during the design stage by means of a questionnaire which addressed issues related to the teachers' beliefs about languages, their opinion about the Error Analysis methodology, and specific points about the interface design and usability. The results unveiled some deficiencies of the current prototype as well as the interests of the teaching professionals which should be considered to bridge the gap between technology development and its pedagogical applications.
Design and compilation of a specialized Spanish-German parallel corpus
Authors: Carla Parra Escart{\'\i}n
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Sentence, Translation

This paper discusses the design and compilation of the TRIS corpus, a specialized parallel corpus of Spanish and German texts. It will be used for phraseological research aimed at improving statistical machine translation. The corpus is based on the European database of Technical Regulations Information System (TRIS), containing 995 original documents written in German and Spanish and their translations into Spanish and German respectively. This parallel corpus is under development and the first version with 97 aligned file pairs was released in the first META-NORD upload of metadata and resources in November 2011. The second version of the corpus, described in the current paper, contains 205 file pairs which have been completely aligned at sentence level, which account for approximately 1,563,000 words and 70,648 aligned sentence pairs.
Detection of Peculiar Word Sense by Distance Metric Learning with Labeled Examples
Authors: Minoru Sasaki, Hiroyuki Shinnou
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: General Classification, Metric Learning, Outlier Detection, Word Sense Disambiguation

For natural language processing on machines, resolving such peculiar usages would be particularly useful in constructing a dictionary and dataset for word sense disambiguation. Hence, it is necessary to develop a method to detect such peculiar examples of a target word from a corpus. Note that, hereinafter, we define a peculiar example as an instance in which the target word or phrase has a new meaning.In this paper, we proposed a new peculiar example detection method using distance metric learning from labeled example pairs. In this method, first, distance metric learning is performed by large margin nearest neighbor classification for the training data, and new training data points are generated using the distance metric in the original space. Then, peculiar examples are extracted using the local outlier factor, which is a density-based outlier detection method, from the updated training and test data. The efficiency of the proposed method was evaluated on an artificial dataset and the Semeval-2010 Japanese WSD task dataset. The results showed that the proposed method has the highest number of properly detected instances and the highest F-measure value. This shows that the label information of training data is effective for density-based peculiar example detection. Moreover, an experiment on outlier detection using a classification method such as SVM showed that it is difficult to apply the classification method to outlier detection.
Conventional Orthography for Dialectal Arabic
Authors: Nizar Habash, Mona Diab, Owen Rambow
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Speech Recognition

Dialectal Arabic (DA) refers to the day-to-day vernaculars spoken in the Arab world. DA lives side-by-side with the official language, Modern Standard Arabic (MSA). DA differs from MSA on all levels of linguistic representation, from phonology and morphology to lexicon and syntax. Unlike MSA, DA has no standard orthography since there are no Arabic dialect academies, nor is there a large edited body of dialectal literature that follows the same spelling standard. In this paper, we present CODA, a conventional orthography for dialectal Arabic; it is designed primarily for the purpose of developing computational models of Arabic dialects. We explain the design principles of CODA and provide a detailed description of its guidelines as applied to Egyptian Arabic.
Standardizing a Component Metadata Infrastructure
Authors: Daan Broeder, Dieter van Uytvanck, Maria Gavrilidou, Thorsten Trippel, Menzo Windhouwer
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper describes the status of the standardization efforts of a Component Metadata approach for describing Language Resources with metadata. Different linguistic and Language {\&} Technology communities as CLARIN, META-SHARE and NaLiDa use this component approach and see its standardization of as a matter for cooperation that has the possibility to create a large interoperable domain of joint metadata. Starting with an overview of the component metadata approach together with the related semantic interoperability tools and services as the ISOcat data category registry and the relation registry we explain the standardization plan and efforts for component metadata within ISO TC37/SC4. Finally, we present information about uptake and plans of the use of component metadata within the three mentioned linguistic and L{\&}T communities.
Assessing Crowdsourcing Quality through Objective Tasks
Authors: Ahmet Aker, Mahmoud El-Haj, M-Dyaa Albakour, Udo Kruschwitz
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Entity Resolution, Question Answering

The emergence of crowdsourcing as a commonly used approach to collect vast quantities of human assessments on a variety of tasks represents nothing less than a paradigm shift. This is particularly true in academic research where it has suddenly become possible to collect (high-quality) annotations rapidly without the need of an expert. In this paper we investigate factors which can influence the quality of the results obtained through Amazon's Mechanical Turk crowdsourcing platform. We investigated the impact of different presentation methods (free text versus radio buttons), workers' base (USA versus India as the main bases of MTurk workers) and payment scale (about {\$}4, {\$}8 and {\$}10 per hour) on the quality of the results. For each run we assessed the results provided by 25 workers on a set of 10 tasks. We run two different experiments using objective tasks: maths and general text questions. In both tasks the answers are unique, which eliminates the uncertainty usually present in subjective tasks, where it is not clear whether the unexpected answer is caused by a lack of worker's motivation, the worker's interpretation of the task or genuine ambiguity. In this work we present our results comparing the influence of the different factors used. One of the interesting findings is that our results do not confirm previous studies which concluded that an increase in payment attracts more noise. We also find that the country of origin only has an impact in some of the categories and only in general text questions but there is no significant difference at the top pay.
Association Norms of German Noun Compounds
Authors: Sabine Schulte im Walde, Susanne Borgwaldt, Ronny Jauch
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper introduces association norms of German noun compounds as a lexical semantic resource for cognitive and computational linguistics research on compositionality. Based on an existing database of German noun compounds, we collected human associations to the compounds and their constituents within a web experiment. The current study describes the collection process and a part-of-speech analysis of the association resource. In addition, we demonstrate that the associations provide insight into the semantic properties of the compounds, and perform a case study that predicts the degree of compositionality of the experiment compound nouns, as relying on the norms. Applying a comparatively simple measure of association overlap, we reach a Spearman rank correlation coefficient of rs=0.5228; p{\textless}000001, when comparing our predictions with human judgements.
Word Sketches for Turkish
Authors: Bharat Ram Ambati, Siva Reddy, Adam Kilgarriff
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Dependency Parsing, Language Modelling

Word sketches are one-page, automatic, corpus-based summaries of a word's grammatical and collocational behaviour. In this paper we present word sketches for Turkish. Until now, word sketches have been generated using a purpose-built finite-state grammars. Here, we use an existing dependency parser. We describe the process of collecting a 42 million word corpus, parsing it, and generating word sketches from it. We evaluate the word sketches in comparison with word sketches from a language independent sketch grammar on an external evaluation task called topic coherence, using Turkish WordNet to derive an evaluation set of coherent topics.
The annotation of the C-ORAL-BRASIL oral through the implementation of the Palavras Parser
Authors: Eckhard Bick, Heliana Mello, Aless Panunzi, ro, Tommaso Raso
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Lemmatization

This article describes the morphosyntactic annotation of the C-ORAL-BRASIL speech corpus, using an adapted version of the Palavras parser. In order to achieve compatibility with annotation rules designed for standard written Portuguese, transcribed words were orthographically normalized, and the parsing lexicon augmented with speech-specific material, phonetically spelled abbreviations etc. Using a two-level annotation approach, speech flow markers like overlaps, retractions and non-verbal productions were separated from running, annotatable text. In the absence of punctuation, syntactic segmentation was achieved by exploiting prosodic break markers, enhanced by a rule-based distinctions between pause and break functions. Under optimal conditions, the modified parsing system achieved correctness rates (F-scores) of 98.6{\%} for part of speech, 95{\%} for syntactic function and 99{\%} for lemmatization. Especially at the syntactic level, a clear connection between accessibility of prosodic break markers and annotation performance could be documented.
Bulgarian X-language Parallel Corpus
Authors: Svetla Koeva, Ivelina Stoyanova, Rositsa Dekova, Borislav Rizov, Angel Genov
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: named-entity-recognition, Named Entity Recognition, Named Entity Recognition (NER), Sentence, Sentence segmentation, Word Sense Disambiguation

The paper presents the methodology and the outcome of the compilation and the processing of the Bulgarian X-language Parallel Corpus (Bul-X-Cor) which was integrated as part of the Bulgarian National Corpus (BulNC). We focus on building representative parallel corpora which include a diversity of domains and genres, reflect the relations between Bulgarian and other languages and are consistent in terms of compilation methodology, text representation, metadata description and annotation conventions. The approaches implemented in the construction of Bul-X-Cor include using readily available text collections on the web, manual compilation (by means of Internet browsing) and preferably automatic compilation (by means of web crawling â€• general and focused). Certain levels of annotation applied to Bul-X-Cor are taken as obligatory (sentence segmentation and sentence alignment), while others depend on the availability of tools for a particular language (morpho-syntactic tagging, lemmatisation, syntactic parsing, named entity recognition, word sense disambiguation, etc.) or for a particular task (word and clause alignment). To achieve uniformity of the annotation we have either annotated raw data from scratch or transformed the already existing annotation to follow the conventions accepted for BulNC. Finally, actual uses of the corpora are presented and conclusions are drawn with respect to future work.
The MASC Word Sense Corpus
Authors: Rebecca J. Passonneau, Collin F. Baker, Christiane Fellbaum, Nancy Ide
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Sentence

The MASC project has produced a multi-genre corpus with multiple layers of linguistic annotation, together with a sentence corpus containing WordNet 3.1 sense tags for 1000 occurrences of each of 100 words produced by multiple annotators, accompanied by indepth inter-annotator agreement data. Here we give an overview of the contents of MASC and then focus on the word sense sentence corpus, describing the characteristics that differentiate it from other word sense corpora and detailing the inter-annotator agreement studies that have been performed on the annotations. Finally, we discuss the potential to grow the word sense sentence corpus through crowdsourcing and the plan to enhance the content and annotations of MASC through a community-based collaborative effort.
P\'agico: Evaluating Wikipedia-based information retrieval in Portuguese
Authors: Cristina Mota, Alberto Sim{\~o}es, Cl{\'a}udia Freitas, Lu{\'\i}s Costa, Diana Santos
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Cultural Vocal Bursts Intensity Prediction, Information Retrieval, Question Answering, Retrieval

How do people behave in their everyday information seeking tasks, which often involve Wikipedia? Are there systems which can help them, or do a similar job? In this paper we describe P{\'a}gico, an evaluation contest with the main purpose of fostering research in these topics. We describe its motivation, the collection of documents created, the evaluation setup, the topics chosen and their choice, the participation, as well as the measures used for evaluation and the gathered resources. The task―between information retrieval and question answering―can be further described as answering questions related to Portuguese-speaking culture in the Portuguese Wikipedia, in a number of different themes and geographic and temporal angles. This initiative allowed us to create interesting datasets and perform some assessment of Wikipedia, while also improving a public-domain open-source system for further wikipedia-based evaluations. In the paper, we provide examples of questions, we report the results obtained by the participants, and provide some discussion on complex issues.
Representation of linguistic and domain knowledge for second language learning in virtual worlds
Authors: Alex Denis, re, Ingrid Falk, Claire Gardent, Laura Perez-Beltrachini
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Text Generation

There has been much debate, both theoretical and practical, on how to link ontologies and lexicons in natural language processing (NLP) applications. In this paper, we focus on an application in which lexicon and ontology are used to generate teaching material. We briefly describe the application (a serious game for language learning). We then zoom in on the representation and interlinking of the lexicon and of the ontology. We show how the use of existing standards and of good practice principles facilitates the design of our resources while satisfying the expressivity requirements set by natural language generation.
A Multilingual Natural Stress Emotion Database
Authors: Xin Zuo, Tian Li, Pascale Fung
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Emotion Recognition, Speech Synthesis

In this paper, we describe an ongoing effort in collecting and annotating a multilingual speech database of natural stress emotion from university students. The goal is to detect natural stress emotions and study the stress expression differences in different languages, which may help psychologists in the future. We designed a common questionnaire of stress-inducing and non-stress-inducing questions in English, Mandarin and Cantonese and collected a first ever, multilingual corpus of natural stress emotion. All of the students are native speakers of the corresponding language. We asked native language speakers to annotate recordings according to the participants' self-label states and obtained a very good kappa inter labeler agreement. We carried out human perception tests where listeners who do not understand Chinese were asked to detect stress emotion from the Mandarin Chinese database. Compared to the annotation labels, these human perceived emotions are of low accuracy, which shows a great necessity for natural stress detection research.
The Twins Corpus of Museum Visitor Questions
Authors: Priti Aggarwal, Ron artstein, Jillian Gerten, Athanasios Katsamanis, Shrikanth Narayanan, Angela Nazarian, David Traum
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Dialogue Management, Natural Language Understanding, speech-recognition, Speech Recognition, Text Classification

The Twins corpus is a collection of utterances spoken in interactions with two virtual characters who serve as guides at the Museum of Science in Boston. The corpus contains about 200,000 spoken utterances from museum visitors (primarily children) as well as from trained handlers who work at the museum. In addition to speech recordings, the corpus contains the outputs of speech recognition performed at the time of utterance as well as the system interpretation of the utterances. Parts of the corpus have been manually transcribed and annotated for question interpretation. The corpus has been used for improving performance of the museum characters and for a variety of research projects, such as phonetic-based Natural Language Understanding, creation of conversational characters from text resources, dialogue policy learning, and research on patterns of user interaction. It has the potential to be used for research on children's speech and on language used when talking to a virtual human.
Development of a Web-Scale Chinese Word N-gram Corpus with Parts of Speech Information
Authors: Chi-Hsin Yu, Yi-jie Tang, Hsin-Hsi Chen
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Information Retrieval, Language Modelling

Web provides a large-scale corpus for researchers to study the language usages in real world. Developing a web-scale corpus needs not only a lot of computation resources, but also great efforts to handle the large variations in the web texts, such as character encoding in processing Chinese web texts. In this paper, we aim to develop a web-scale Chinese word N-gram corpus with parts of speech information called NTU PN-Gram corpus using the ClueWeb09 dataset. We focus on the character encoding and some Chinese-specific issues. The statistics about the dataset is reported. We will make the resulting corpus a public available resource to boost the Chinese language processing.
Medical Term Extraction in an Arabic Medical Corpus
Authors: Doaa Samy, Moreno-S, Antonio oval, Conchi Bueno-D{\'\i}az, Marta Garrote-Salazar, Jos{\'e} M. Guirao
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Term Extraction

This paper tests two different strategies for medical term extraction in an Arabic Medical Corpus. The experiments and the corpus are developed within the framework of Multimedica project funded by the Spanish Ministry of Science and Innovation and aiming at developing multilingual resources and tools for processing of newswire texts in the Health domain. The first experiment uses a fixed list of medical terms, the second experiment uses a list of Arabic equivalents of very limited list of common Latin prefix and suffix used in medical terms. Results show that using equivalents of Latin suffix and prefix outperforms the fixed list. The paper starts with an introduction, followed by a description of the state-of-art in the field of Arabic Medical Language Resources (LRs). The third section describes the corpus and its characteristics. The fourth and the fifth sections explain the lists used and the results of the experiments carried out on a sub-corpus for evaluation. The last section analyzes the results outlining the conclusions and future work.
Annotation Facilities for the Reliable Analysis of Human Motion
Authors: Michael Kipp
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

Human motion is challenging to analyze due to the many degrees of freedom of the human body. While the qualitative analysis of human motion lies at the core of many research fields, including multimodal communication, it is still hard to achieve reliable results when human coders transcribe motion with abstract categories. In this paper we tackle this problem in two respects. First, we provide facilities for qualitative and quantitative comparison of annotations. Second, we provide facilities for exploring highly precise recordings of human motion (motion capture) using a low-cost consumer device (Kinect). We present visualization and analysis methods, integrated in the existing ANVIL video annotation tool (Kipp 2001), and provide both a precision analysis and a ''''''``cookbook'''''''' for Kinect-based motion analysis.
Addressing polysemy in bilingual lexicon extraction from comparable corpora
Authors: Darja Fi{\v{s}}er, Nikola Ljube{\v{s}}i{\'c}, Ozren Kubelka
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Translation, Word Sense Disambiguation

This paper presents an approach to extract translation equivalents from comparable corpora for polysemous nouns. As opposed to the standard approaches that build a single context vector for all occurrences of a given headword, we first disambiguate the headword with third-party sense taggers and then build a separate context vector for each sense of the headword. Since state-of-the-art word sense disambiguation tools are still far from perfect, we also tried to improve the results by combining the sense assignments provided by two different sense taggers. Evaluation of the results shows that we outperform the baseline (0.473) in all the settings we experimented with, even when using only one sense tagger, and that the best-performing results are indeed obtained by taking into account the intersection of both sense taggers (0.720).