pwc-archive/papers-with-abstracts huggingface dataset:
Arabic Word Generation and Modelling for Spell Checking
Authors: Khaled Shaalan, Mohammed Attia, Pavel Pecina, Younes Samih, Josef van Genabith
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Language Modeling, Language Modelling, Morphological Analysis, Spelling Correction, valid

Arabic is a language known for its rich and complex morphology. Although many research projects have focused on the problem of Arabic morphological analysis using different techniques and approaches, very few have addressed the issue of generation of fully inflected words for the purpose of text authoring. Available open-source spell checking resources for Arabic are too small and inadequate. Ayaspell, for example, the official resource used with OpenOffice applications, contains only 300,000 fully inflected words. We try to bridge this critical gap by creating an adequate, open-source and large-coverage word list for Arabic containing 9,000,000 fully inflected surface words. Furthermore, from a large list of valid forms and invalid forms we create a character-based tri-gram language model to approximate knowledge about permissible character clusters in Arabic, creating a novel method for detecting spelling errors. Testing of this language model gives a precision of 98.2{\%} at a recall of 100{\%}. We take our research a step further by creating a context-independent spelling correction tool using a finite-state automaton that measures the edit distance between input words and candidate corrections, the Noisy Channel Model, and knowledge-based rules. Our system performs significantly better than Hunspell in choosing the best solution, but it is still below the MS Spell Checker.
Annotation of response tokens and their triggering expressions in Japanese multi-party conversations
Authors: Yasuharu Den, Hanae Koiso, Katsuya Takanashi, Nao Yoshida
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper, we propose a new scheme for annotating response tokens (RTs) and their triggering expressions in Japanese multi-party conversations. In the proposed scheme, RTs are first identified and classified according to their forms, and then sub-classified according to their sequential positions in the discourse. To deeply study the contexts in which RTs are used, the scheme also provides procedures for annotating triggering expressions, which are considered to trigger the listener's production of RTs. RTs are classified according to whether or not there is a particular object or proposition in the speaker's turn for which the listener shows a positive or aligned stance. Triggering expressions are then identified in the speaker's turn; they include surprising facts and other newsworthy things, opinions and assessments, focus of a response to a question or repair initiation, keywords in narratives, and embedded propositions quoted from other's statement or thought, which are to be agreed upon, assessed, or noticed. As an illustrative application of our scheme, we present a preliminary analysis on the distribution of the latency of the listener's response to the triggering expression, showing how it differs according to RT's forms and positions.
Automatically Generated Online Dictionaries
Authors: Enik{\H{o}} H{\'e}ja, D{\'a}vid Tak{\'a}cs
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Translation, Word Alignment

The aim of our software presentation is to demonstrate that corpus-driven bilingual dictionaries generated fully by automatic means are suitable for human use. Need for such dictionaries shows up specifically in the case of lesser used languages where due to the low demand it does not pay off for publishers to invest into the production of dictionaries. Previous experiments have proven that bilingual lexicons can be created by applying word alignment on parallel corpora. Such an approach, especially the corpus-driven nature of it, yields several advantages over more traditional approaches. Most importantly, automatically attained translation probabilities are able to guarantee that the most frequently used translations come first within an entry. However, the proposed technique have to face some difficulties, as well. In particular, the scarce availability of parallel texts for medium density languages imposes limitations on the size of the resulting dictionary. Our objective is to design and implement a dictionary building workflow and a query system that is apt to exploit the additional benefits of the method and overcome the disadvantages of it.
Method for Collection of Acted Speech Using Various Situation Scripts
Authors: Takahiro Miyajima, Hideaki Kikuchi, Katsuhiko Shirai, Shigeki Okawa
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Speech Synthesis

This study was carried out to improve the quality of acted emotional speech. In the recent paradigm shift in speech collection techniques, methods for the collection of high-quality and spontaneous speech has been strongly focused on. However, such methods involve various constraints: such as the difficulty in controlling utterances and sound quality. Hence, our study daringly focuses on acted speech because of its high operability. In this paper, we propose a new method for speech collection by refining acting scripts. We compared the speech collected using our proposed method and that collected using an imitation of the legacy method that was implemented with traditional basic emotional words. The results show the advantage of our proposed method, i.e., the possibility of the generating high F0 fluctuations in acoustical expressions, which is one of the important features of the expressive speech, while ensuring that there is no decline in the naturalness and other psychological features.
Citing on-line Language Resources
Authors: Daan Broeder, Dieter van Uytvanck, Gunter Senft
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Data Visualization

Although the possibility of referring or citing on-line data from publications is seen at least theoretically as an important means to provide immediate testable proof or simple illustration of a line of reasoning, the practice has not been wide-spread yet and no extensive experience has been gained about the possibilities and problems of referring to raw data-sets. This paper makes a case to investigate the possibility and need of persistent data visualization services that facilitate the inspection and evaluation of the cited data.
Automatic Extraction and Evaluation of Arabic LFG Resources
Authors: Mohammed Attia, Khaled Shaalan, Lamia Tounsi, Josef van Genabith
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: POS

This paper presents the results of an approach to automatically acquire large-scale, probabilistic Lexical-Functional Grammar (LFG) resources for Arabic from the Penn Arabic Treebank (ATB). Our starting point is the earlier, work of (Tounsi et al., 2009) on automatic LFG f(eature)-structure annotation for Arabic using the ATB. They exploit tree configuration, POS categories, functional tags, local heads and trace information to annotate nodes with LFG feature-structure equations. We utilize this annotation to automatically acquire grammatical function (dependency) based subcategorization frames and paths linking long-distance dependencies (LDDs). Many state-of-the-art treebank-based probabilistic parsing approaches are scalable and robust but often also shallow: they do not capture LDDs and represent only local information. Subcategorization frames and LDD paths can be used to recover LDDs from such parser output to capture deep linguistic information. Automatic acquisition of language resources from existing treebanks saves time and effort involved in creating such resources by hand. Moreover, data-driven automatic acquisition naturally associates probabilistic information with subcategorization frames and LDD paths. Finally, based on the statistical distribution of LDD path types, we propose empirical bounds on traditional regular expression based functional uncertainty equations used to handle LDDs in LFG.
Evaluating the Impact of External Lexical Resources into a CRF-based Multiword Segmenter and Part-of-Speech Tagger
Authors: Matthieu Constant, Isabelle Tellier
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Named Entity Recognition (NER), Part-Of-Speech Tagging

This paper evaluates the impact of external lexical resources into a CRF-based joint Multiword Segmenter and Part-of-Speech Tagger. We especially show different ways of integrating lexicon-based features in the tagging model. We display an absolute gain of 0.5{\%} in terms of f-measure. Moreover, we show that the integration of lexicon-based features significantly compensates the use of a small training corpus.
The Minho Quotation Resource
Authors: Brett Drury, Jos{\'e} Jo{\~a}o Almeida
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Entity Extraction using GAN

Direct quotations from business leaders can provide a rich sample of language which is in common use in the world of commerce. This language used by business leaders often uses: metaphors, euphemisms, slang, obscenities and invented words. In addition the business lexicon is dynamic because new words or terms will gain popularity with businessmen whilst obsolete words will exit their common vocabulary. In addition to being a rich source of language direct quotations from business leaders can have ''real world'' consequences. For example, Gerald Ratner nearly bankrupted his company with an infamous candid comment at an Institute of Directors meeting in 1993. Currently, there is no ''direct quotations from business leaders'' resource freely available to the research community. The ''Minho Quotation Resource'' captures the business lexicon with in excess of 500,000 quotations from individuals from the business world. The quotations were captured from October 2009 and April 2011. The resource is available in a searchable Lucene index and will be available for download in May 2012
Translog-II: a Program for Recording User Activity Data for Empirical Reading and Writing Research
Authors: Michael Carl
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Data Visualization, Machine Translation, Translation

This paper presents a novel implementation of Translog-II. Translog-II is a Windows-oriented program to record and study reading and writing processes on a computer. In our research, it is an instrument to acquire objective, digital data of human translation processes. As their predecessors, Translog 2000 and Translog 2006, also Translog-II consists of two main components: Translog-II Supervisor and Translog-II User, which are used to create a project file, to run a text production experiments (a user reads, writes or translates a text) and to replay the session. Translog produces a log files which contains all user activity data of the reading, writing, or translation session, and which can be evaluated by external tools. While there is a large body of translation process research based on Translog, this paper gives an overview of the Translog-II functions and its data visualization options.
Morphosyntactic Analysis of the CHILDES and TalkBank Corpora
Authors: Brian MacWhinney
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Language Acquisition, Morphological Analysis, Part-Of-Speech Tagging

This paper describes the construction and usage of the MOR and GRASP programs for part of speech tagging and syntactic dependency analysis of the corpora in the CHILDES and TalkBank databases. We have written MOR grammars for 11 languages and GRASP analyses for three. For English data, the MOR tagger reaches 98{\%} accuracy on adult corpora and 97{\%} accuracy on child language corpora. The paper discusses the construction of MOR lexicons with an emphasis on compounds and special conversational forms. The shape of rules for controlling allomorphy and morpheme concatenation are discussed. The analysis of bilingual corpora is illustrated in the context of the Cantonese-English bilingual corpora. Methods for preparing data for MOR analysis and for developing MOR grammars are discussed. We believe that recent computational work using this system is leading to significant advances in child language acquisition theory and theories of grammar identification more generally.
Similarity Ranking as Attribute for Machine Learning Approach to Authorship Identification
Authors: Jan Rygl, Ale{\v{s}} Hor{\'a}k
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Attribute, BIG-bench Machine Learning, Information Retrieval

In the authorship identification task, examples of short writings of N authors and an anonymous document written by one of these N authors are given. The task is to determine the authorship of the anonymous text. Practically all approaches solved this problem with machine learning methods. The input attributes for the machine learning process are usually formed by stylistic or grammatical properties of individual documents or a defined similarity between a document and an author. In this paper, we present the results of an experiment to extend the machine learning attributes by ranking the similarity between a document and an author: we transform the similarity between an unknown document and one of the N authors to the order in which the author is the most similar to the document in the set of N authors. The comparison of similarity probability and similarity ranking was made using the Support Vector Machines algorithm. The results show that machine learning methods perform slightly better with attributes based on the ranking of similarity than with previously used similarity between an author and a document.
Challenges in the development of annotated corpora of computer-mediated communication in Indian Languages: A Case of Hindi
Authors: Ritesh Kumar
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: POS, Sentiment Analysis

The present paper describes an ongoing effort to compile and annotate a large corpus of computer-mediated communication (CMC) in Hindi. It describes the process of the compilation of the corpus, the basic structure of the corpus and the annotation of the corpus and the challenges faced in the creation of such a corpus. It also gives a description of the technologies developed for the processing of the data, addition of the metadata and annotation of the corpus. Since it is a corpus of written communication, it provides quite a distinctive challenge for the annotation process. Besides POS annotation, it will also be annotated at higher levels of representation. Once completely developed it will be a very useful resource of Hindi for research in the areas of linguistics, NLP and other social sciences research related to communication, particularly computer-mediated communication..Besides this the challenges discussed here and the way they are tackled could be taken as the model for developing the corpus of computer-mediated communication in other Indian languages. Furthermore the technologies developed for the construction of this corpus will also be made available publicly.
LexIt: A Computational Resource on Italian Argument Structure
Authors: Aless Lenci, ro, Gabriella Lapesa, Giulia Bonansinga
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The aim of this paper is to introduce LexIt, a computational framework for the automatic acquisition and exploration of distributional information about Italian verbs, nouns and adjectives, freely available through a web interface at the address http://sesia.humnet.unipi.it/lexit. LexIt is the first large-scale resource for Italian in which subcategorization and semantic selection properties are characterized fully on distributional ground: in the paper we describe both the process of data extraction and the evaluation of the subcategorization frames extracted with LexIt.
Annotating Football Matches: Influence of the Source Medium on Manual Annotation
Authors: Kar{\"e}n Fort, Vincent Claveau
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper, we present an annotation campaign of football (soccer) matches, from a heterogeneous text corpus of both match minutes and video commentary transcripts, in French. The data, annotations and evaluation process are detailed, and the quality of the annotated corpus is discussed. In particular, we propose a new technique to better estimate the annotator agreement when few elements of a text are to be annotated. Based on that, we show how the source medium influenced the process and the quality.
The C-ORAL-BRASIL I: Reference Corpus for Spoken Brazilian Portuguese
Authors: Tommaso Raso, Heliana Mello, Maryual{\^e} Malvessi Mittmann
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: text-to-speech, Text to Speech

C-ORAL-BRASIL I is a Brazilian Portuguese spontaneous speech corpus compiled following the same architecture adopted by the C-ORAL-ROM resource. The main goal is the documentation of the diaphasic and diastratic variations in Brazilian Portuguese. The diatopic variety represented is that of the metropolitan area of Belo Horizonte, capital city of Minas Gerais. Even though it was not a primary goal, a nice balance was achieved in terms of speakers' diastratic features (sex, age and school level). The corpus is entirely dedicated to informal spontaneous speech and comprises 139 informal speech texts, 208,130 words and 21:08:52 hours of recording, distributed into family/private (80{\%}) and public (20{\%}) contexts. The LR includes audio files, transcripts in text format and text-to-speech alignment (accessible with WinPitch Pro software). C-ORAL-BRASIL I also provides transcripts with Part-of-Speech annotation implemented through the parser system Palavras. Transcripts were validated regarding the proper application of transcription criteria and also for the annotation of prosodic boundaries. Some quantitative features of C-ORAL-BRASIL I in comparison with the informal C-ORAL-ROM are reported.
A light way to collect comparable corpora from the Web
Authors: Ahmet Aker, Evangelos Kanoulas, Robert Gaizauskas
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Information Retrieval, Machine Translation, Translation

Statistical Machine Translation (SMT) relies on the availability of rich parallel corpora. However, in the case of under-resourced languages, parallel corpora are not readily available. To overcome this problem previous work has recognized the potential of using comparable corpora as training data. The process of obtaining such data usually involves (1) downloading a separate list of documents for each language, (2) matching the documents between two languages usually by comparing the document contents, and finally (3) extracting useful data for SMT from the matched document pairs. This process requires a large amount of time and resources since a huge volume of documents needs to be downloaded to increase the chances of finding good document pairs. In this work we aim to reduce the amount of time and resources spent for tasks 1 and 2. Instead of obtaining full documents we first obtain just titles along with some meta-data such as time and date of publication. Titles can be obtained through Web Search and RSS News feed collections so that download of the full documents is not needed. We show experimentally that titles can be used to approximate the comparison between documents using full document contents.
Holaaa!! writin like u talk is kewl but kinda hard 4 NLP
Authors: Maite Melero, Marta R. Costa-juss{\`a}, Judith Domingo, Montse Marquina, Mart{\'\i} Quixal
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Domain Adaptation, Language Modelling, Lemmatization, Machine Translation, Opinion Mining, Speech Recognition, Text Normalization

We present work in progress aiming to build tools for the normalization of User-Generated Content (UGC). As we will see, the task requires the revisiting of the initial steps of NLP processing, since UGC (micro-blog, blog, and, generally, Web 2.0 user texts) presents a number of non-standard communicative and linguistic characteristics, and is in fact much closer to oral and colloquial language than to edited text. We present and characterize a corpus of UGC text in Spanish from three different sources: Twitter, consumer reviews and blogs. We motivate the need for UGC text normalization by analyzing the problems found when processing this type of text through a conventional language processing pipeline, particularly in the tasks of lemmatization and morphosyntactic tagging, and finally we propose a strategy for automatically normalizing UGC using a selector of correct forms on top of a pre-existing spell-checker.
Applying Random Indexing to Structured Data to Find Contextually Similar Words
Authors: Danica Damljanovi{\'c}, Udo Kruschwitz, M-Dyaa Albakour, Johann Petrak, Mihai Lupu
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Question Answering

Language resources extracted from structured data (e.g. Linked Open Data) have already been used in various scenarios to improve conventional Natural Language Processing techniques. The meanings of words and the relations between them are made more explicit in RDF graphs, in comparison to human-readable text, and hence have a great potential to improve legacy applications. In this paper, we describe an approach that can be used to extend or clarify the semantic meaning of a word by constructing a list of contextually related terms. Our approach is based on exploiting the structure inherent in an RDF graph and then applying the methods from statistical semantics, and in particular, Random Indexing, in order to discover contextually related terms. We evaluate our approach in the domain of life science using the dataset generated with the help of domain experts from a large pharmaceutical company (AstraZeneca). They were involved in two phases: firstly, to generate a set of keywords of interest to them, and secondly to judge the set of generated contextually similar words for each keyword of interest. We compare our proposed approach, exploiting the semantic graph, with the same method applied on the human readable text extracted from the graph.
Coreference in Spoken vs. Written Texts: a Corpus-based Analysis
Authors: Marilisa Amoia, Kerstin Kunz, Ekaterina Lapshinova-Koltunski
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: coreference-resolution, Coreference Resolution, Diversity

This paper describes an empirical study of coreference in spoken vs. written text. We focus on the comparison of two particular text types, interviews and popular science texts, as instances of spoken and written texts since they display quite different discourse structures. We believe in fact, that the correlation of difficulties in coreference resolution and varying discourse structures requires a deeper analysis that accounts for the diversity of coreference strategies or their sub-phenomena as indicators of text type or genre. In this work, we therefore aim at defining specific parameters that classify differences in genres of spoken and written texts such as the preferred segmentation strategy, the maximal allowed distance in or the length and size of coreference chains as well as the correlation of structural and syntactic features of coreferring expressions. We argue that a characterization of such genre dependent parameters might improve the performance of current state-of-art coreference resolution technology.