pwc-archive/papers-with-abstracts huggingface dataset:
Automatic word alignment tools to scale production of manually aligned parallel texts
Authors: Stephen Grimes, Katherine Peterson, Xuansong Li
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Semantic Role Labeling, Sentiment Analysis, Word Alignment

We have been creating large-scale manual word alignment corpora for Arabic-English and Chinese-English language pairs in genres such as newsire, broadcast news and conversation, and web blogs. We are now meeting the challenge of word aligning further varieties of web data for Chinese and Arabic ''''''``dialects''''''''. Human word alignment annotation can be costly and arduous. Alignment guidelines may be imprecise or underspecified in cases where parallel sentences are hard to compare -- due to non-literal translations or differences between language structures. In order to speed annotation, we examine the effect that seeding manual alignments with automatic aligner output has on annotation speed and accuracy. We use automatic alignment methods that produce alignment results which are high precision and low recall to minimize annotator corrections. Results suggest that annotation time can be reduced by up to 20{\%}, but we also found that reviewing and correcting automatic alignments requires more time than anticipated. We discuss throughout the paper crucial decisions on data structures for word alignment that likely have a significant impact on our results.
Developing and evaluating an emergency scenario dialogue corpus
Authors: Jolanta Bachan
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The present paper describes the development and evaluation of the Polish emergency dialogue corpus recorded for studying alignment phenomena in stress scenarios. The challenge is that emergency dialogues are more complex on many levels than standard information negotiation dialogues, different resources are needed for differential investigation, and resources for this kind of corpus are rare. Currently there is no comparable corpus for Polish. In the present context, alignment is meant as adaptation on the syntactic, semantic and pragmatic levels of communication between the two interlocutors, including choice of similar lexical items and speaking style. Four different dialogue scenarios were arranged and prompt speech material was created. Two maps for the map-tasks and one emergency diapix were design to prompt semi-spontaneous dialogues simulating stress and natural communicative situations. The dialogue corpus was recorded taking into account the public character of conversations in the emergency setting. The linguistic study of alignment in this kind of dialogue made it possible to design and implement a prototype of a Polish adaptive dialogue system to support stress scenario communication (not described in this paper).
A Framework for Evaluating Text Correction
Authors: Robert Dale, George Narroway
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Text Generation

Computer-based aids for writing assistance have been around since at least the early 1980s, focussing primarily on aspects such as spelling, grammar and style. The potential audience for such tools is very large indeed, and this is a clear case where we might expect to see language processing applications having a significant real-world impact. However, existing comparative evaluations of applications in this space are often no more than impressionistic and anecdotal reviews of commercial offerings as found in software magazines, making it hard to determine which approaches are superior. More rigorous evaluation in the scholarly literature has been held back in particular by the absence of shared datasets of texts marked-up with errors, and the lack of an agreed evaluation framework. Significant collections of publicly available data are now appearing; this paper describes a complementary evaluation framework, which has been piloted in the Helping Our Own shared task. The approach, which uses stand-off annotations for representing edits to text, can be used in a wide variety of text-correction tasks, and easily accommodates different error tagsets.
Large Scale Lexical Analysis
Authors: Gregor Thurmair, Vera Aleksi{\'c}, Christoph Schwarz
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Language Identification, Lexical Analysis, Machine Translation, POS, Sentence

The following paper presents a lexical analysis component as implemented in the PANACEA project. The goal is to automatically extract lexicon entries from crawled corpora, in an attempt to use corpus-based methods for high-quality linguistic text processing, and to focus on the quality of data without neglecting quantitative aspects. Lexical analysis has the task to assign linguistic information (like: part of speech, inflectional class, gender, subcategorisation frame, semantic properties etc.) to all parts of the input text. If tokens are ambiguous, lexical analysis must provide all possible sets of annotation for later (syntactic) disambiguation, be it tagging, or full parsing. The paper presents an approach for assigning part-of-speech tags for German and English to large input corpora ({\textgreater} 50 mio tokens), providing a workflow which takes as input crawled corpora and provides POS-tagged lemmata ready for lexicon integration. Tools include sentence splitting, lexicon lookup, decomposition, and POS defaulting. Evaluation shows that the overall error rate can be brought down to about 2{\%} if language resources are properly designed. The complete workflow is implemented as a sequence of web services integrated into the PANACEA platform.
NTUSocialRec: An Evaluation Dataset Constructed from Microblogs for Recommendation Applications in Social Networks
Authors: Chieh-Jen Wang, Shuk-Man Cheng, Lung-Hao Lee, Hsin-Hsi Chen, Wen-shen Liu, Pei-Wen Huang, Shih-Peng Lin
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Recommendation Systems, Semantic Textual Similarity

This paper proposes a method to construct an evaluation dataset from microblogs for the development of recommendation systems. We extract the relationships among three main entities in a recommendation event, i.e., who recommends what to whom. User-to-user friend relationships and user-to-resource interesting relationships in social media and resource-to-metadata descriptions in an external ontology are employed. In the experiments, the resources are restricted to visual entertainment media, movies in particular. A sequence of ground truths varying with time is generated. That reflects the dynamic of real world.
The ETAPE corpus for the evaluation of speech-based TV content processing in the French language
Authors: Guillaume Gravier, Gilles Adda, Niklas Paulsson, Matthieu Carr{\'e}, Aude Giraudel, Olivier Galibert
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Speech Recognition

The paper presents a comprehensive overview of existing data for the evaluation of spoken content processing in a multimedia framework for the French language. We focus on the ETAPE corpus which will be made publicly available by ELDA mid 2012, after completion of the evaluation campaign, and recall existing resources resulting from previous evaluation campaigns. The ETAPE corpus consists of 30 hours of TV and radio broadcasts, selected to cover a wide variety of topics and speaking styles, emphasizing spontaneous speech and multiple speaker areas.
Automatic lexical semantic classification of nouns
Authors: N{\'u}ria Bel, Lauren Romeo, Muntsa Padr{\'o}
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Classification, Entity Typing, General Classification, Machine Translation, Named Entity Recognition (NER), Question Answering

The work we present here addresses cue-based noun classification in English and Spanish. Its main objective is to automatically acquire lexical semantic information by classifying nouns into previously known noun lexical classes. This is achieved by using particular aspects of linguistic contexts as cues that identify a specific lexical class. Here we concentrate on the task of identifying such cues and the theoretical background that allows for an assessment of the complexity of the task. The results show that, despite of the a-priori complexity of the task, cue-based classification is a useful tool in the automatic acquisition of lexical semantic classes.
Is it Useful to Support Users with Lexical Resources? A User Study.
Authors: Ernesto William De Luca
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Information Retrieval, Text Categorization, Word Sense Disambiguation

Current search engines are used for retrieving relevant documents from the huge amount of data available and have become an essential tool for the majority of Web users. Standard search engines do not consider semantic information that can help in recognizing the relevance of a document with respect to the meaning of a query. In this paper, we present our system architecture and a first user study, where we show that the use of semantics can help users in finding relevant information, filtering it ad facilitating quicker access to data.
In the same boat and other idiomatic seafaring expressions
Authors: Rita Marinelli, Laura Cignoni
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper reports on a research carried out at the Institute for Computational Linguistics (ILC) on a set of idiomatic nautical expressions in Italian and English. A total of 200 Italian expressions were first selected and examined, using both monolingual and bilingual dictionaries, as well as specific lexicographical works dealing with the subject of idiomaticity, especially of the maritime type, and a similar undertaking was then conducted for the English expressions. We discuss the possibility of including both the Italian and English idiomatic expressions in the semantic database Mariterm, which contains terms belonging to the maritime domain. We describe the terminological database and the way in which the idiomatic expressions can be organised within the system, so that, similarly to the other synsets, they are connected to other concepts represented in the database, but at the same time continue to belong to a group of particular linguistic expressions. Furthermore, we study similarities and differences in meaning and usage of some idiomatic expressions in the two languages.
Creation and use of Language Resources in a Question-Answering eHealth System
Authors: Ulrich Andersen, Anna Braasch, Lina Henriksen, Csaba Huszka, Anders Johannsen, Lars Kayser, Bente Maegaard, Ole Norgaard, Stefan Schulz, J{\"u}rgen Wedekind
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Document Summarization, Epidemiology, Multi-Document Summarization, Open-Domain Question Answering, Question Answering

ESICT (Experience-oriented Sharing of health knowledge via Information and Communication Technology) is an ongoing research project funded by the Danish Council for Strategic Research. It aims at developing a health/disease related information system based on information technology, language technology, and formalized medical knowledge. The formalized medical knowledge consists partly of the terminology database SNOMED CT and partly of authorized medical texts on the domain. The system will allow users to ask questions in Danish and will provide natural language answers. Currently, the project is pursuing three basically different methods for question answering, and they are all described to some extent in this paper. A system prototype will handle questions related to diabetes and heart diseases. This paper concentrates on the methods employed for question answering and the language resources that are utilized. Some resources were existing, such as SNOMED CT, others, such as a corpus of sample questions, have had to be created or constructed.
Building and Exploiting a Corpus of Dialog Interactions between French Speaking Virtual and Human Agents
Authors: Lina M. Rojas-Barahona, Alej Lorenzo, ra, Claire Gardent
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

We describe the acquisition of a dialog corpus for French based on multi-task human-machine interactions in a serious game setting. We present a tool for data collection that is configurable for multiple games; describe the data collected using this tool and the annotation schema used to annotate it; and report on the results obtained when training a classifier on the annotated data to associate each player turn with a dialog move usable by a rule based dialog manager. The collected data consists of approximately 1250 dialogs, 10454 utterances and 168509 words and will be made freely available to academic and nonprofit research.
Collection of a Large Database of French-English SMT Output Corrections
Authors: Marion Potet, Emmanuelle Esperan{\c{c}}a-Rodier, Laurent Besacier, Herv{\'e} Blanchon
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Sentence, Translation

Corpus-based approaches to machine translation (MT) rely on the availability of parallel corpora. To produce user-acceptable translation outputs, such systems need high quality data to be efficiency trained, optimized and evaluated. However, building high quality dataset is a relatively expensive task. In this paper, we describe the data collection and analysis of a large database of 10.881 SMT translation output hypotheses manually corrected. These post-editions were collected using Amazon's Mechanical Turk, following some ethical guidelines. A complete analysis of the collected data pointed out a high quality of the corrections with more than 87 {\%} of the collected post-editions that improve hypotheses and more than 94 {\%} of the crowdsourced post-editions which are at least of professional quality. We also post-edited 1,500 gold-standard reference translations (of bilingual parallel corpora generated by professional) and noticed that 72 {\%} of these translations needed to be corrected during post-edition. We computed a proximity measure between the differents kind of translations and pointed out that reference translations are as far from the hypotheses than from the corrected hypotheses (i.e. the post-editions). In light of these last findings, we discuss the adequation of text-based generated reference translations to train setence-to-sentence based SMT systems.
German \textitnach-Particle Verbs in Semantic Theory and Corpus Data
Authors: Boris Haselbach, Wolfgang Seeker, Kerstin Eckart
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Management

In this paper, we present a database-supported corpus study where we combine automatically obtained linguistic information from a statistical dependency parser, namely the occurrence of a dative argument, with predictions from a theory on the argument structure of German particle verbs with ''''''``nach''''''''. The theory predicts five readings of ''''''``nach'''''''' which behave differently with respect to dative licensing in their argument structure. From a huge German web corpus, we extracted sentences for a subset of ''''''``nach''''''''-particle verbs for which no dative is expected by the theory. Making use of a relational database management system, we bring together the corpus sentences and the lemmas manually annotated along the lines of the theory. We validate the theoretical predictions against the syntactic structure of the corpus sentences, which we obtained from a statistical dependency parser. We find that, in principle, the theory is borne out by the data, however, manual error analysis reveals cases for which the theory needs to be extended.
Discovering Missing Wikipedia Inter-language Links by means of Cross-lingual Word Sense Disambiguation
Authors: Els Lefever, V{\'e}ronique Hoste, Martine De Cock
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Text Summarization, Word Sense Disambiguation

Wikipedia pages typically contain inter-language links to the corresponding pages in other languages. These links, however, are often incomplete. This paper describes a set of experiments in which the viability of discovering such missing inter-language links for ambiguous nouns by means of a cross-lingual Word Sense Disambiguation approach is investigated. The input for the inter-language link detection system is a set of Dutch pages for a given ambiguous noun and the output of the system is a set of links to the corresponding pages in three target languages (viz. French, Spanish and Italian). The experimental results show that although it is a very challenging task, the system succeeds to detect missing inter-language links between Wikipedia documents for a manually labeled test set. The final goal of the system is to provide a human editor with a list of possible missing links that should be manually verified.
Arabic-Segmentation Combination Strategies for Statistical Machine Translation
Authors: Saab Mansour, Hermann Ney
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Segmentation, Translation

Arabic segmentation was already applied successfully for the task of statistical machine translation (SMT). Yet, there is no consistent comparison of the effect of different techniques and methods over the final translation quality. In this work, we use existing tools and further re-implement and develop new methods for segmentation. We compare the resulting SMT systems based on the different segmentation methods over the small IWSLT 2010 BTEC and the large NIST 2009 Arabic-to-English translation tasks. Our results show that for both small and large training data, segmentation yields strong improvements, but, the differences between the top ranked segmenters are statistically insignificant. Due to the different methodologies that we apply for segmentation, we expect a complimentary variation in the results achieved by each method. As done in previous work, we combine several segmentation schemes of the same model but achieve modest improvements. Next, we try a different strategy, where we combine the different segmentation methods rather than the different segmentation schemes. In this case, we achieve stronger improvements over the best single system. Finally, combining schemes and methods has another slight gain over the best combination strategy.
Announcing Prague Czech-English Dependency Treebank 2.0
Authors: Jan Haji{\v{c}}, Eva Haji{\v{c}}ov{\'a}, Jarmila Panevov{\'a}, Petr Sgall, Ond{\v{r}}ej Bojar, Silvie Cinkov{\'a}, Eva Fu{\v{c}}{\'\i}kov{\'a}, Marie Mikulov{\'a}, Petr Pajas, Jan Popelka, Ji{\v{r}}{\'\i} Semeck{\'y}, Jana {\v{S}}indlerov{\'a}, Jan {\v{S}}t{\v{e}}p{\'a}nek, Josef Toman, Zde{\v{n}}ka Ure{\v{s}}ov{\'a}, Zden{\v{e}}k {\v{Z}}abokrtsk{\'y}
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Coreference Resolution, Sentence

We introduce a substantial update of the Prague Czech-English Dependency Treebank, a parallel corpus manually annotated at the deep syntactic layer of linguistic representation. The English part consists of the Wall Street Journal (WSJ) section of the Penn Treebank. The Czech part was translated from the English source sentence by sentence. This paper gives a high level overview of the underlying linguistic theory (the so-called tectogrammatical annotation) with some details of the most important features like valency annotation, ellipsis reconstruction or coreference.
First Results in a Study Evaluating Pre-annotation and Correction Propagation for Machine-Assisted Syriac Morphological Analysis
Authors: Paul Felt, Eric Ringger, Kevin Seppi, Kristian Heal, Robbie Haertel, Deryle Lonsdale
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Morphological Analysis, Sentence

Manual annotation of large textual corpora can be cost-prohibitive, especially for rare and under-resourced languages. One potential solution is pre-annotation: asking human annotators to correct sentences that have already been annotated, usually by a machine. Another potential solution is correction propagation: using annotator corrections to bad pre-annotations to dynamically improve to the remaining pre-annotations within the current sentence. The research presented in this paper employs a controlled user study to discover under what conditions these two machine-assisted annotation techniques are effective in increasing annotator speed and accuracy and thereby reducing the cost for the task of morphologically annotating texts written in classical Syriac. A preliminary analysis of the data indicates that pre-annotations improve annotator accuracy when they are at least 60{\%} accurate, and annotator speed when they are at least 80{\%} accurate. This research constitutes the first systematic evaluation of pre-annotation and correction propagation together in a controlled user study.
A Corpus of Spontaneous Multi-party Conversation in Bosnian Serbo-Croatian and British English
Authors: Emina Kurti{\'c}, Bill Wells, Guy J. Brown, Timothy Kempton, Ahmet Aker
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper we present a corpus of audio and video recordings of spontaneous, face-to-face multi-party conversation in two languages. Freely available high quality recordings of mundane, non-institutional, multi-party talk are still sparse, and this corpus aims to contribute valuable data suitable for study of multiple aspects of spoken interaction. In particular, it constitutes a unique resource for spoken Bosnian Serbo-Croatian (BSC), an under-resourced language with no spoken resources available at present. The corpus consists of just over 3 hours of free conversation in each of the target languages, BSC and British English (BE). The audio recordings have been made on separate channels using head-set microphones, as well as using a microphone array, containing 8 omni-directional microphones. The data has been segmented and transcribed using segmentation notions and transcription conventions developed from those of the conversation analysis research tradition. Furthermore, the transcriptions have been automatically aligned with the audio at the word and phone level, using the method of forced alignment. In this paper we describe the procedures behind the corpus creation and present the main features of the corpus for the study of conversation.
Measuring the compositionality of NV expressions in Basque by means of distributional similarity techniques
Authors: Antton Gurrutxaga, I{\~n}aki Alegria
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

We present several experiments aiming at measuring the semantic compositionality of NV expressions in Basque. Our approach is based on the hypothesis that compositionality can be related to distributional similarity. The contexts of each NV expression are compared with the contexts of its corresponding components, by means of different techniques, as similarity measures usually used with the Vector Space Model (VSM), Latent Semantic Analysis (LSA) and some measures implemented in the Lemur Toolkit, as Indri index, tf-idf, Okapi index and Kullback-Leibler divergence. Using our previous work with cooccurrence techniques as a baseline, the results point to improvements using the Indri index or Kullback-Leibler divergence, and a slight further improvement when used in combination with cooccurrence measures such as {\$}t{\$}-score, via rank-aggregation. This work is part of a project for MWE extraction and characterization using different techniques aiming at measuring the properties related to idiomaticity, as institutionalization, non-compositionality and lexico-syntactic fixedness.