pwc-archive/papers-with-abstracts huggingface dataset:
Dictionary Look-up with Katakana Variant Recognition
Authors: Satoshi Sato
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Morphological Analysis, Retrieval, Transliteration

The Japanese language has rich variety and quantity of word variant. Since 1980s, it has been recognized that this richness becomes an obstacle against natural language processing. A complete solution, however, has not been presented yet. This paper proposes a method to recognize Katakana variants―a major type of word variant in Japanese―in the process of dictionary look-up. For a given set of variant generation rules, the method executes variant generation and entry retrieval simultaneously and efficiently. We have developed the seven-layered rule set (216 rules in total) according to the specification manual of UniDic-2.1.0 and other sources. An experiment shows that the spelling-variant generator with 102 rules in the first five layers is almost perfect. Another experiment shows that the form-variant generator with all 216 rules is powerful and 77.7{\%} of multiple spellings of Katakana loanwords are unnecessary (i.e., can be removed). This result means that the proposed method can drastically reduce the number of variants that we have to register into a dictionary in advance.
SUTime: A library for recognizing and normalizing time expressions
Authors: Angel X. Chang, Christopher Manning
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Question Answering, Relation Extraction

We describe SUTIME, a temporal tagger for recognizing and normalizing temporal expressions in English text. SUTIME is available as part of the Stanford CoreNLP pipeline and can be used to annotate documents with temporal information. It is a deterministic rule-based system designed for extensibility. Testing on the TempEval-2 evaluation corpus shows that this system outperforms state-of-the-art techniques.
Recognition of Nonmanual Markers in American Sign Language (ASL) Using Non-Parametric Adaptive 2D-3D Face Tracking
Authors: Dimitris Metaxas, Bo Liu, Fei Yang, Peng Yang, Nicholas Michael, Carol Neidle
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Sign Language Recognition

This paper addresses the problem of automatically recognizing linguistically significant nonmanual expressions in American Sign Language from video. We develop a fully automatic system that is able to track facial expressions and head movements, and detect and recognize facial events continuously from video. The main contributions of the proposed framework are the following: (1) We have built a stochastic and adaptive ensemble of face trackers to address factors resulting in lost face track; (2) We combine 2D and 3D deformable face models to warp input frames, thus correcting for any variation in facial appearance resulting from changes in 3D head pose; (3) We use a combination of geometric features and texture features extracted from a canonical frontal representation. The proposed new framework makes it possible to detect grammatically significant nonmanual expressions from continuous signing and to differentiate successfully among linguistically significant expressions that involve subtle differences in appearance. We present results that are based on the use of a dataset containing 330 sentences from videos that were collected and linguistically annotated at Boston University.
Two Database Resources for Processing Social Media English Text
Authors: Eleanor Clark, Kenji Araki
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Information Retrieval, Machine Translation, Translation, Vocal Bursts Valence Prediction, Word Sense Disambiguation

This research focuses on text processing in the sphere of English-language social media. We introduce two database resources. The first, CECS (Casual English Conversion System) database, a lexicon-type resource of 1,255 entries, was constructed for use in our experimental system for the automated normalization of casual, irregularly-formed English used in communications such as Twitter. Our rule-based approach primarily aims to avoid problems caused by user creativity and individuality of language when Twitter-style text is used as input in Machine Translation, and to aid comprehension for non-native speakers of English. Although the database is still under development, we have so far carried out two evaluation experiments using our system which have shown positive results. The second database, CEGS (Casual English Generation System) phoneme database contains sets of alternative spellings for the phonemes in the CMU Pronouncing Dictionary, designed for use in a system for generating phoneme-based casual English text from regular English input; in other words, automatically producing humanlike creative sentences as an AI task. This paper provides an overview of the necessity, method, application and evaluation of both resources.
A Curated Database for Linguistic Research: The Test Case of Cimbrian Varieties
Authors: Maristella Agosti, Birgit Alber, Giorgio Maria Di Nunzio, Marco Dussin, Stefan Rabanus, Aless Tomaselli, ra
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: TAG

In this paper we present the definition of a conceptual approach for the information space entailed by a multidisciplinary and collaborative project, ''''''``Cimbrian as a test case for synchronic and diachronic language variation'', which provides linguists with a test bed for formal hypotheses concerning human language. Aims of the project are to collect, digitize and tag linguistic data from the German variety of Cimbrian - spoken in three areas of northern Italy: Giazza (VR), Luserna (TN), and Roana (VI) - and to make available on-line a valuable and innovative linguistic resource for the in-depth study of Cimbrian. The task is addressed by a multidisciplinary team of linguists and computer scientists who, combining their competence, aim to make available new tools for linguistic analysis
Evaluation of Online Dialogue Policy Learning Techniques
Authors: Alex Papangelis, ros, Vangelis Karkaletsis, Fillia Makedon
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Dialogue Management, Management, Reinforcement Learning (RL), Slot Filling, Text Generation

The number of applied Dialogue Systems is ever increasing in several service providing and other applications as a way to efficiently and inexpensively serve large numbers of customers. A DS that employs some form of adaptation to the environment and its users is called an Adaptive Dialogue System (ADS). A significant part of the research community has lately focused on ADS and many existing or novel techniques are being applied to this problem. One of the most promising techniques is Reinforcement Learning (RL) and especially online RL. This paper focuses on online RL techniques used to achieve adaptation in Dialogue Management and provides an evaluation of various such methods in an effort to aid the designers of ADS in deciding which method to use. To the best of our knowledge there is no other work to compare online RL techniques on the dialogue management problem.
Experiences in Resource Generation for Machine Translation through Crowdsourcing
Authors: Anoop Kunchukuttan, Shourya Roy, Pratik Patel, Kushal Ladha, Somya Gupta, Mitesh M. Khapra, Pushpak Bhattacharyya
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Translation

The logistics of collecting resources for Machine Translation (MT) has always been a cause of concern for some of the resource deprived languages of the world. The recent advent of crowdsourcing platforms provides an opportunity to explore the large scale generation of resources for MT. However, before venturing into this mode of resource collection, it is important to understand the various factors such as, task design, crowd motivation, quality control, etc. which can influence the success of such a crowd sourcing venture. In this paper, we present our experiences based on a series of experiments performed. This is an attempt to provide a holistic view of the different facets of translation crowd sourcing and identifying key challenges which need to be addressed for building a practical crowdsourcing solution for MT.
Multilingual Central Repository version 3.0
Authors: Aitor Gonzalez-Agirre, Egoitz Laparra, German Rigau
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper describes the upgrading process of the Multilingual Central Repository (MCR). The new MCR uses WordNet 3.0 as Interlingual-Index (ILI). Now, the current version of the MCR integrates in the same EuroWordNet framework wordnets from five different languages: English, Spanish, Catalan, Basque and Galician. In order to provide ontological coherence to all the integrated wordnets, the MCR has also been enriched with a disparate set of ontologies: Base Concepts, Top Ontology, WordNet Domains and Suggested Upper Merged Ontology. The whole content of the MCR is freely available.
Involving Language Professionals in the Evaluation of Machine Translation
Authors: Eleftherios Avramidis, Aljoscha Burchardt, Christian Federmann, Maja Popovi{\'c}, Cindy Tscherwinka, David Vilar
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Translation

Significant breakthroughs in machine translation only seem possible if human translators are taken into the loop. While automatic evaluation and scoring mechanisms such as BLEU have enabled the fast development of systems, it is not clear how systems can meet real-world (quality) requirements in industrial translation scenarios today. The taraX{\"U} project paves the way for wide usage of hybrid machine translation outputs through various feedback loops in system development. In a consortium of research and industry partners, the project integrates human translators into the development process for rating and post-editing of machine translation outputs thus collecting feedback for possible improvements.
A New Method for Evaluating Automatically Learned Terminological Taxonomies
Authors: Paola Velardi, Roberto Navigli, Stefano Faralli, Juana Maria Ruiz Martinez
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

Abstract Evaluating a taxonomy learned automatically against an existing gold standard is a very complex problem, because differences stem from the number, label, depth and ordering of the taxonomy nodes. In this paper we propose casting the problem as one of comparing two hierarchical clusters. To this end we defined a variation of the Fowlkes and Mallows measure (Fowlkes and Mallows, 1983). Our method assigns a similarity value B{\textasciicircum}i{\_}(l,r) to the learned (l) and reference (r) taxonomy for each cut i of the corresponding anonymised hierarchies, starting from the topmost nodes down to the leaf concepts. For each cut i, the two hierarchies can be seen as two clusterings C{\textasciicircum}i{\_}l , C{\textasciicircum}i{\_}r of the leaf concepts. We assign a prize to early similarity values, i.e. when concepts are clustered in a similar way down to the lowest taxonomy levels (close to the leaf nodes). We apply our method to the evaluation of the taxonomy learning methods put forward by Navigli et al. (2011) and Kozareva and Hovy (2010).
A topologic view of Topic and Focus marking in Italian
Authors: Gloria Gagliardi, Edoardo Lombardi Vallauri, Fabio Tamburini
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

Regularities in position and level of prosodic prominences associated to patterns of Information Structure are identified for some Italian varieties. The experiments' results suggest a possibly new structural hypothesis on the role and function of the main prominence in marking information patterns. (1) An abstract and merely structural, ''''''``topologic'''''''' concept of Prominence location can be conceived of, as endowed with the function of demarcation between units, before their culmination and ''''''``description''''''''. This may suffice to explain much of the process by which speakers interpret the IS of utterances in discourse. Further features, such as the specific intonational contours of the different IS units, may thus represent a certain amount of redundancy. (2) Real utterances do not always signal the distribution of Topic and Focus clearly. Acoustically, many remain underspecified in this respect. This is especially true for the distinction between Topic-Focus and Broad Focus, which indeed often has no serious effects on the progression of communicative dynamism in the subsequent discourse. (3) The consistency of such results with the law of least effort, and the very high percent of matching between perceptual evaluations and automatic measurement, seem to validate the used algorithm.
Improving the Recall of a Discourse Parser by Constraint-based Postprocessing
Authors: Sucheta Ghosh, Richard Johansson, Giuseppe Riccardi, Sara Tonelli
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Chunking, Semantic Role Labeling

We describe two constraint-based methods that can be used to improve the recall of a shallow discourse parser based on conditional random field chunking. These method uses a set of natural structural constraints as well as others that follow from the annotation guidelines of the Penn Discourse Treebank. We evaluated the resulting systems on the standard test set of the PDTB and achieved a rebalancing of precision and recall with improved F-measures across the board. This was especially notable when we used evaluation metrics taking partial matches into account; for these measures, we achieved F-measure improvements of several points.
Adding Morpho-semantic Relations to the Romanian Wordnet
Authors: Verginica Barbu Mititelu
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Information Retrieval, Question Answering

Keeping pace with other wordnets development, we present the challenges raised by the Romanian derivational system and our methodology for identifying derived words and their stems in the Romanian Wordnet. To attain this aim we rely only on the list of literals in the wordnet and on a list of Romanian affixes; the automatically obtained pairs require automatic and manual validation, based on a few heuristics. The correct members of the pairs are linked together and the relation is associated a semantic label whenever necessary. This label is proved to have cross-language validity. The work reported here contributes to the increase of the number of relations both between literals and between synsets, especially the cross-part-of-speech links. Words belonging to the same lexical family are identified easily. The benefits of thus improving a language resource such as wordnet become self-evident. The paper also contains an overview of the current status of the Romanian wordnet and an envisaged plan for continuing the research.
Cross-lingual studies of ASR errors: paradigms for perceptual evaluations
Authors: Ioana Vasilescu, Martine Adda-Decker, Lori Lamel
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Information Retrieval, speech-recognition, Speech Recognition

It is well-known that human listeners significantly outperform machines when it comes to transcribing speech. This paper presents a progress report of the joint research in the automatic vs human speech transcription and of the perceptual experiments developed at LIMSI that aims to increase our understanding of automatic speech recognition errors. Two paradigms are described here in which human listeners are asked to transcribe speech segments containing words that are frequently misrecognized by the system. In particular, we sought to gain information about the impact of increased context to help humans disambiguate problematic lexical items, typically homophone or near-homophone words. The long-term aim of this research is to improve the modeling of ambiguous contexts so as to reduce automatic transcription errors.
The Rocky Road towards a Swedish FrameNet - Creating SweFN
Authors: Karin Friberg Heppin, Maria Toporowska Gronostaj
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Text Generation

The Swedish FrameNet project, SweFN, is a lexical resource under development, designed to support both humans and different applications within language technology, such as text generation, text understanding and information extraction. SweFN is constructed in line with the Berkeley FrameNet and the project is aiming to make it a free, full-scale, multi-functional lexical resource covering morphological, syntactic, and semantic descriptions of 50,000 entries. Frames populated by lexical units belonging to the general vocabulary dominate in SweFN, but there are also frames from the medical and the art domain. As Swedish is a language with very productive compounding, special attention is paid to semantic relations within the one word compounds which populate the frames. This is of relevance for understanding the meaning of the compounds and for capturing the semantic and syntactic alternations which are brought about in the course of compounding. SweFN is a component within a complex of modern and historical lexicon resources named SweFN++, available at .
Building a synchronous corpus of acoustic and 3D facial marker data for adaptive audio-visual speech synthesis
Authors: Dietmar Schabus, Michael Pucher, Gregor Hofer
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Audio-Visual Speech Recognition, Speech Recognition, Speech Synthesis, text-to-speech, Text to Speech, Text-To-Speech Synthesis, Visual Speech Recognition

We have created a synchronous corpus of acoustic and 3D facial marker data from multiple speakers for adaptive audio-visual text-to-speech synthesis. The corpus contains data from one female and two male speakers and amounts to 223 Austrian German sentences each. In this paper, we first describe the recording process, using professional audio equipment and a marker-based 3D facial motion capturing system for the audio-visual recordings. We then turn to post-processing, which incorporates forced alignment, principal component analysis (PCA) on the visual data, and some manual checking and corrections. Finally, we describe the resulting corpus, which will be released under a research license at the end of our project. We show that the standard PCA based feature extraction approach also works on a multi-speaker database in the adaptation scenario, where there is no data from the target speaker available in the PCA step.
AVATecH --- automated annotation through audio and video analysis
Authors: Przemyslaw Lenkiewicz, Binyam Gebrekidan Gebre, Oliver Schreer, Stefano Masneri, Daniel Schneider, Sebastian Tsch{\"o}pel
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In different fields of the humanities annotations of multimodal resources are a necessary component of the research workflow. Examples include linguistics, psychology, anthropology, etc. However, creation of those annotations is a very laborious task, which can take 50 to 100 times the length of the annotated media, or more. This can be significantly improved by applying innovative audio and video processing algorithms, which analyze the recordings and provide automated annotations. This is the aim of the AVATecH project, which is a collaboration of the Max Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS. In this paper we present a set of results of automated annotation together with an evaluation of their quality.
Acquisition of Syntactic Simplification Rules for French
Authors: Violeta Seretan
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Information Retrieval, Machine Translation, Sentence Compression, Text Simplification, Text Summarization

Text simplification is the process of reducing the lexical and syntactic complexity of a text while attempting to preserve (most of) its information content. It has recently emerged as an important research area, which holds promise for enhancing the text readability for the benefit of a broader audience as well as for increasing the performance of other applications. Our work focuses on syntactic complexity reduction and deals with the task of corpus-based acquisition of syntactic simplification rules for the French language. We show that the data-driven manual acquisition of simplification rules can be complemented by the semi-automatic detection of syntactic constructions requiring simplification. We provide the first comprehensive set of syntactic simplification rules for French, whose size is comparable to similar resources that exist for English and Brazilian Portuguese. Unlike these manually-built resources, our resource integrates larger lists of lexical cues signaling simplifiable constructions, that are useful for informing practical systems.
An Empirical Study of the Occurrence and Co-Occurrence of Named Entities in Natural Language Corpora
Authors: K Saravanan, Monojit Choudhury, Raghavendra Udupa, A. Kumaran
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Information Retrieval, Transliteration

Named Entities (NEs) that occur in natural language text are important especially due to the advent of social media, and they play a critical role in the development of many natural language technologies. In this paper, we systematically analyze the patterns of occurrence and co-occurrence of NEs in standard large English news corpora - providing valuable insight for the understanding of the corpus, and subsequently paving way for the development of technologies that rely critically on handling NEs. We use two distinctive approaches: normal statistical analysis that measure and report the occurrence patterns of NEs in terms of frequency, growth, etc., and a complex networks based analysis that measures the co-occurrence pattern in terms of connectivity, degree-distribution, small-world phenomenon, etc. Our analysis indicates that: (i) NEs form an open-set in corpora and grow linearly, (ii) presence of a kernel and peripheral NE's, with the large periphery occurring rarely, and (iii) a strong evidence of small-world phenomenon. Our findings may suggest effective ways for construction of NE lexicons to aid efficient development of several natural language technologies.
Chinese Characters Mapping Table of Japanese, Traditional Chinese and Simplified Chinese
Authors: Chenhui Chu, Toshiaki Nakazawa, Sadao Kurohashi
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Cross-Lingual Information Retrieval, Information Retrieval, Machine Translation, Relation, Retrieval, Translation

Chinese characters are used both in Japanese and Chinese, which are called Kanji and Hanzi respectively. Chinese characters contain significant semantic information, a mapping table between Kanji and Hanzi can be very useful for many Japanese-Chinese bilingual applications, such as machine translation and cross-lingual information retrieval. Because Kanji characters are originated from ancient China, most Kanji have corresponding Chinese characters in Hanzi. However, the relation between Kanji and Hanzi is quite complicated. In this paper, we propose a method of making a Chinese characters mapping table of Japanese, Traditional Chinese and Simplified Chinese automatically by means of freely available resources. We define seven categories for Kanji based on the relation between Kanji and Hanzi, and classify mappings of Chinese characters into these categories. We use a resource from Wiktionary to show the completeness of the mapping table we made. Statistical comparison shows that our proposed method makes a more complete mapping table than the current version of Wiktionary.