pwc-archive/papers-with-abstracts huggingface dataset:
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus
Authors: Jens Forster, Christoph Schmidt, Thomas Hoyoux, Oscar Koller, Uwe Zelle, Justus Piater, Hermann Ney
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Machine Translation, Sentence, Sign Language Recognition, speech-recognition, Speech Recognition, Translation

This paper introduces the RWTH-PHOENIX-Weather corpus, a video-based, large vocabulary corpus of German Sign Language suitable for statistical sign language recognition and translation. In contrastto most available sign language data collections, the RWTH-PHOENIX-Weather corpus has not been recorded for linguistic research but for the use in statistical pattern recognition. The corpus contains weather forecasts recorded from German public TV which are manually annotated using glosses distinguishing sign variants, and time boundaries have been marked on the sentence and the gloss level. Further, the spoken German weather forecast has been transcribed in a semi-automatic fashion using a state-of-the-art automatic speech recognition system. Moreover, an additional translation of the glosses into spoken German has been created to capture allowable translation variability. In addition to the corpus, experimental baseline results for hand and head tracking, statistical sign language recognition and translation are presented.
The KnowledgeStore: an Entity-Based Storage System
Authors: Roldano Cattoni, Francesco Corcoglioniti, Christian Girardi, Bernardo Magnini, Luciano Serafini, Roberto Zanoli
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Entity Extraction using GAN, Entity Linking, valid

This paper describes the KnowledgeStore, a large-scale infrastructure for the combined storage and interlinking of multimedia resources and ontological knowledge. Information in the KnowledgeStore is organized around entities, such as persons, organizations and locations. The system allows (i) to import background knowledge about entities, in form of annotated RDF triples; (ii) to associate resources to entities by automatically recognizing, coreferring and linking mentions of named entities; and (iii) to derive new entities based on knowledge extracted from mentions. The KnowledgeStore builds on state of art technologies for language processing, including document tagging, named entity extraction and cross-document coreference. Its design provides for a tight integration of linguistic and semantic features, and eases the further processing of information by explicitly representing the contexts where knowledge and mentions are valid or relevant. We describe the system and report about the creation of a large-scale KnowledgeStore instance for storing and integrating multimedia contents and background knowledge relevant to the Italian Trentino region.
An Analytical Model of Language Resource Sustainability
Authors: Khalid Choukri, Victoria Arranz
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Descriptive, Information Retrieval, Machine Translation, model

This paper elaborates on a sustainability model for Language Resources, both at a descriptive and analytical level. The first part, devoted to the descriptive model, elaborates on the definition of this concept both from a general point of view and from the Human Language Technology and Language Resources perspective. The paper also intends to list an exhaustive number of factors that have an impact on this sustainability. These factors will be clustered into Pillars so as ease understanding as well as the prediction of LR sustainability itself. Rather than simply identifying a set of LRs that have been in use for a while and that one can consider as sustainable, the paper aims at first clarifying and (re)defining the concept of sustainability by also connecting it to other domains. Then it also presents a detailed decomposition of all dimensions of Language Resource features that can contribute and/or have an impact on such sustainability. Such analysis will also help anticipate and forecast sustainability for a LR before taking any decisions concerning design and production.
CLIMB grammars: three projects using metagrammar engineering
Authors: Antske Fokkens, Tania Avgustinova, Yi Zhang
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Code Generation

This paper introduces the CLIMB (Comparative Libraries of Implementations with Matrix Basis) methodology and grammars. The basic idea behind CLIMB is to use code generation as a general methodology for grammar development in order to create a more systematic approach to grammar development. The particular method used in this paper is closely related to the LinGO Grammar Matrix. Like the Grammar Matrix, resulting grammars are HPSG grammars that can map bidirectionally between strings and MRS representations. The main purpose of this paper is to provide insight into the process of using CLIMB for grammar development. In addition, we describe three projects that make use of this methodology or have concrete plans to adapt CLIMB in the future: CLIMB for Germanic languages, CLIMB for Slavic languages and CLIMB to combine two grammars of Mandarin Chinese. We present the first results that indicate feasibility and development time improvements for creating a medium to large coverage precision grammar.
Annotated Bibliographical Reference Corpora in Digital Humanities
Authors: Young-Min Kim, Patrice Bellot, Elodie Faath, Marin Dacos
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Articles, BIG-bench Machine Learning

In this paper, we present new bibliographical reference corpora in digital humanities (DH) that have been developed under a research project, Robust and Language Independent Machine Learning Approaches for Automatic Annotation of Bibliographical References in DH Books supported by Google Digital Humanities Research Awards. The main target is the bibliographical references in the articles of Revues.org site, an oldest French online journal platform in DH field. Since the final object is to provide automatic links between related references and articles, the automatic recognition of reference fields like author and title is essential. These fields are therefore manually annotated using a set of carefully defined tags. After providing a full description of three corpora, which are separately constructed according to the difficulty level of annotation, we briefly introduce our experimental results on the first two corpora. A popular machine learning technique, Conditional Random Field (CRF) is used to build a model, which automatically annotates the fields of new references. In the experiments, we first establish a standard for defining features and labels adapted to our DH reference data. Then we show our new methodology against less structured references gives a meaningful result.
Corpus of Children Voices for Mid-level Markers and Affect Bursts Analysis
Authors: Marie Tahon, Agnes Delaborde, Laurence Devillers
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This article presents a corpus featuring children playing games in interaction with the humanoid robot Nao: children have to express emotions in the course of a storytelling by the robot. This corpus was collected to design an affective interactive system driven by an interactional and emotional representation of the user. We evaluate here some mid-level markers used in our system: reaction time, speech duration and intensity level. We also question the presence of affect bursts, which are quite numerous in our corpus, probably because of the young age of the children and the absence of predefined lexical content.
Joint Segmentation and POS Tagging for Arabic Using a CRF-based Classifier
Authors: Souhir Gahbiche-Braham, H{\'e}l{\`e}ne Bonneau-Maynard, Thomas Lavergne, Fran{\c{c}}ois Yvon
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Articles, BIG-bench Machine Learning, Machine Translation, Morphological Analysis, Part-Of-Speech Tagging, POS, POS Tagging, Translation

Arabic is a morphologically rich language, and Arabic texts abound of complex word forms built by concatenation of multiple subparts, corresponding for instance to prepositions, articles, roots prefixes, or suffixes. The development of Arabic Natural Language Processing applications, such as Machine Translation (MT) tools, thus requires some kind of morphological analysis. In this paper, we compare various strategies for performing such preprocessing, using generic machine learning techniques. The resulting tool is compared with two open domain alternatives in the context of a statistical MT task and is shown to be faster than its competitors, with no significant difference in MT quality.
Fivehundredmillionandone Tokens. Loading the AAC Container with Text Resources for Text Studies.
Authors: Hanno Biber, Evelyn Breiteneder
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The ''''''``AAC - Austrian Academy Corpus'''''''' is a diachronic German language digital text corpus of more than 500 million tokens. The text corpus has collected several thousands of texts representing a wide range of different text types. The primary research aim is to develop text language resources for the study of texts. For corpus linguistics and corpus based language research large text corpora need to be structured in a systematic way. For this structural purpose the AAC is making use of the notion of container. By container in the context of corpus research we understand a flexible system of pragmatic representation, manipulation, modification and structured storage of annotated items of text. The issue of representing a large corpus in formats that offer only limited space is paradigmatic for the general task of representing a language by just a small collection of text or a small sample of the language. Methods based upon structural normalization and standardization have to be developed in order to provide useful instruments for text studies.
Annotation of anaphoric relations and topic continuity in Japanese conversation
Authors: Natsuko Nakagawa, Yasuharu Den
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper proposes a basic scheme for annotating anaphoric relations in Japanese conversations. More specifically, we propose methods of (i) dividing discourse segments into meaningful units, (ii) identifying zero pronouns and other overt anaphors, (iii) classifying zero pronouns, and (iv) identifying anaphoric relations. We discuss various kinds of problems involved in the annotation mainly caused by on-line processing of discourse and/or interactions between the participants. These problems do not arise in annotating written languages. This paper also proposes a method to compute topic continuity based on anaphoric relations. The topic continuity involves the information status of the noun in question (given, accessible, and new) and persistence (whether the noun is mentioned multiple times or not). We show that the topic continuity correlates with short-utterance units, which are determined prosodically through the previous annotations; nouns of high topic continuity tend to be prosodically separated from the predicates. This result indicates the validity of our annotations of anaphoric relations and topic continuity and the usefulness for further studies on discourse and interaction.
Classifying Standard Linguistic Processing Functionalities based on Fundamental Data Operation Types
Authors: Yoshihiko Hayashi, Chiharu Narawa
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

iIt is often argued that a set of standard linguistic processing functionalities should be identified,with each of them given a formal specification. We would benefit from the formal specifications; for example, the semi-automated composition of a complex language processing workflow could be enabled in due time. This paper extracts a standard set of linguistic processing functionalities and tries to classify them formally. To do this, we first investigated prominent types of language Web services/linguistic processors by surveying a Web-based language service infrastructure and published NLP toolkits. We next induced a set of standard linguistic processing functionalities by carefully investigating each of the linguistic processor types. The standard linguistic processing functionalities was then characterized by the input/output data types, as well as the required data operation types, which were also derived from the investigation. As a result, we came up with an ontological depiction that classifies linguistic processors and linguistic processing functionalities with respect to the fundamental data operation types. We argue that such an ontological depiction can explicitly describe the functional aspects of a linguistic processing functionality.
Evaluating expressive speech synthesis from audiobook corpora for conversational phrases
Authors: {\'E}va Sz{\'e}kely, Joao Paulo Cabral, Mohamed Abou-Zleikha, Peter Cahill, Julie Carson-Berndsen
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Clustering, Expressive Speech Synthesis, Speech Synthesis

Audiobooks are a rich resource of large quantities of natural sounding, highly expressive speech. In our previous research we have shown that it is possible to detect different expressive voice styles represented in a particular audiobook, using unsupervised clustering to group the speech corpus of the audiobook into smaller subsets representing the detected voice styles. These subsets of corpora of different voice styles reflect the various ways a speaker uses their voice to express involvement and affect, or imitate characters. This study is an evaluation of the detection of voice styles in an audiobook in the application of expressive speech synthesis. A further aim of this study is to investigate the usability of audiobooks as a language resource for expressive speech synthesis of utterances of conversational speech. Two evaluations have been carried out to assess the effect of the genre transfer: transmitting expressive speech from read aloud literature to conversational phrases with the application of speech synthesis. The first evaluation revealed that listeners have different voice style preferences for a particular conversational phrase. The second evaluation showed that it is possible for users of speech synthesis systems to learn the characteristics of a voice style well enough to make reliable predictions about what a certain utterance will sound like when synthesised using that voice style.
The I3MEDIA speech database: a trilingual annotated corpus for the analysis and synthesis of emotional speech
Authors: Juan Mar{\'\i}a Garrido, Yesika Laplaza, Montse Marquina, Andrea Pearman, Jos{\'e} Gregorio Escalada, Miguel {\'A}ngel Rodr{\'\i}guez, Ana Armenta
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this article the I3Media corpus is presented, a trilingual (Catalan, English, Spanish) speech database of neutral and emotional material collected for analysis and synthesis purposes. The corpus is actually made up of six different subsets of material: a neutral subcorpus, containing emotionless utterances; a dialog' subcorpus, containing typical call center utterances; an emotional' corpus, a set of sentences representative of pure emotional states; a football' subcorpus, including utterances imitating a football broadcasting situation; a SMS' subcorpus, including readings of SMS texts; and a paralinguistic elements' corpus, including recordings of interjections and paralinguistic sounds uttered in isolation. The corpus was read by professional speakers (male, in the case of Spanish and Catalan; female, in the case of the English corpus), carefully selected to meet criteria of language competence, voice quality and acting conditions. It is the result of a collaboration between the Speech Technology Group at Telef{\'o}nica Investigaci{\'o}n y Desarrollo (TID) and the Speech and Language Group at Barcelona Media Centre d'Innovaci{\'o} (BM), as part of the I3Media project.
DramaBank: Annotating Agency in Narrative Discourse
Authors: David Elson
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

We describe the Story Intention Graph, a set of discourse relations designed to represent aspects of narrative. Compared to prior models, ours is a novel synthesis of the notions of goal, plan, intention, outcome, affect and time that is amenable to corpus annotation. We describe a collection project, DramaBank, which includes encodings of texts ranging from small fables to epic poetry and contemporary nonfiction.
Linguagrid: a network of Linguistic and Semantic Services for the Italian Language.
Authors: Alessio Bosca, Luca Dini, Milen Kouylekov, Marco Trevisan
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Clustering, Dependency Parsing, Entity Extraction using GAN, Keyword Extraction, Language Identification, Machine Translation, Morphological Analysis, Question Answering, Sentiment Analysis, Word Sense Disambiguation

In order to handle the increasing amount of textual information today available on the web and exploit the knowledge latent in this mass of unstructured data, a wide variety of linguistic knowledge and resources (Language Identification, Morphological Analysis, Entity Extraction, etc.). is crucial. In the last decade LRaas (Language Resource as a Service) emerged as a novel paradigm for publishing and sharing these heterogeneous software resources over the Web. In this paper we present an overview of Linguagrid, a recent initiative that implements an open network of linguistic and semantic Web Services for the Italian language, as well as a new approach for enabling customizable corpus-based linguistic services on Linguagrid LRaaS infrastructure. A corpus ingestion service in fact allows users to upload corpora of documents and to generate classification/clustering models tailored to their needs by means of standard machine learning techniques applied to the textual contents and metadata from the corpora. The models so generated can then be accessed through proper Web Services and exploited to process and classify new textual contents.
Using Noun Similarity to Adapt an Acceptability Measure for Persian Light Verb Constructions
Authors: Shiva Taslimipoor, Afsaneh Fazly, Ali Hamzeh
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation

Light verb constructions (LVCs), such as take a walk and make a decision, are a common subclass of multiword expressions (MWEs), whose distinct syntactic and semantic properties call for a special treatment within a computational system. In particular, LVCs are formed semi-productively: often a semantically-general verb (such as take) combines with a number of semantically-similar nouns to form semantically-related LVCs, as in make a decision/choice/commitment. Nonetheless, there are restrictions as to which verbs combine with which class of nouns. A proper computational account of LVCs is even more important for languages such as Persian, in which most verbs are of the form of LVCs. Recently, there has been some work on the automatic identification of MWEs (including LVCs) in resource-rich languages, such as English and Dutch. We adapt such existing techniques for the automatic identification of LVCs in Persian, an under-resourced language. Specifically, we extend an existing statistical measure of the acceptability of English LVCs (Fazly et al., 2007) to make explicit use of semantic classes of noun, and show that such classes are in particular useful for determining the LVC acceptability of new combinations.
On the Way to a Legal Sharing of Web Applications in NLP
Authors: Victoria Arranz, Olivier Hamon
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

For some years now, web services have been employed in Natural Language Processing (NLP) for a number of uses and within a number of sub-areas. Web services allow users to gain access to distant applications without having the need to install them on their local machines. A large paradigm of advantages can be obtained from a practical and development point of view. However, the legal aspects behind this sharing should not be neglected and should be openly discussed so as to understand the implications behind such data exchanges and tool uses. In the framework of PANACEA, this paper highlights the different points involved and describes the work done in order to handle all the legal aspects behind those points.
Designing French Tale Corpora for Entertaining Text To Speech Synthesis
Authors: David Doukhan, Sophie Rosset, Albert Rilliard, D{'}Aless, Christophe ro, Martine Adda-Decker
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Sentence, Speech Synthesis, text-to-speech, Text to Speech, Text-To-Speech Synthesis

Text and speech corpora for training a tale telling robot have been designed, recorded and annotated. The aim of these corpora is to study expressive storytelling behaviour, and to help in designing expressive prosodic and co-verbal variations for the artificial storyteller). A set of 89 children tales in French serves as a basis for this work. The tales annotation principles and scheme are described, together with the corpus description in terms of coverage and inter-annotator agreement. Automatic analysis of a new tale with the help of this corpus and machine learning is discussed. Metrics for evaluation of automatic annotation methods are discussed. A speech corpus of about 1 hour, with 12 tales has been recorded and aligned and annotated. This corpus is used for predicting expressive prosody in children tales, above the level of the sentence.
``Rendering Endangered Lexicons Interoperable through Standards Harmonization'': the RELISH project
Authors: Helen Aristar-Dry, Sebastian Drude, Menzo Windhouwer, Jost Gippert, Irina Nevskaya
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The RELISH project promotes language-oriented research by addressing a two-pronged problem: (1) the lack of harmonization between digital standards for lexical information in Europe and America, and (2) the lack of interoperability among existing lexicons of endangered languages, in particular those created with the Shoebox/Toolbox lexicon building software. The cooperation partners in the RELISH project are the University of Frankfurt (FRA), the Max Planck Institute for Psycholinguistics (MPI Nijmegen), and Eastern Michigan University, the host of the Linguist List (ILIT). The project aims at harmonizing key European and American digital standards whose divergence has hitherto impeded international collaboration on language technology for resource creation and analysis, as well as web services for archive access. Focusing on several lexicons of endangered languages, the project will establish a unified way of referencing lexicon structure and linguistic concepts, and develop a procedure for migrating these heterogeneous lexicons to a standards-compliant format. Once developed, the procedure will be generalizable to the large store of lexical resources involved in the LEGO and DoBeS projects.
Le Petit Prince in UNL
Authors: Ronaldo Martins
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Information Retrieval, Machine Translation, Text Generation

The present paper addresses the process and the results of the interpretation of the integral text of Le Petit Prince (Little Prince), the famous novel by Antoine de Saint-Exup{\'e}ry, from French into UNL. The original text comprised 1,684 interpretation units (15,513 words), which were sorted according to their similarity, from the shortest to the longest ones, and which were then projected into a UNL graph structure, composed of semantic directed binary relations linking nodes associated to the synsets of the corresponding original lexical items. The whole UNL-ization process was carried-out manually and the results have been used as the main resource in a natural language generation project involving already 27 languages.