pwc-archive/papers-with-abstracts huggingface dataset:
Designing an Evaluation Framework for Spoken Term Detection and Spoken Document Retrieval at the NTCIR-9 SpokenDoc Task
Authors: Tomoyosi Akiba, Hiromitsu Nishizaki, Kiyoaki Aikawa, Tatsuya Kawahara, Tomoko Matsui
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Retrieval, Speech Recognition

We describe the evaluation framework for spoken document retrieval for the IR for the Spoken Documents Task, conducted in the ninth NTCIR Workshop. The two parts of this task were a spoken term detection (STD) subtask and an ad hoc spoken document retrieval subtask (SDR). Both subtasks target search terms, passages and documents included in academic and simulated lectures of the Corpus of Spontaneous Japanese. Seven teams participated in the STD subtask and five in the SDR subtask. The results obtained through the evaluation in the workshop are discussed.
Spontaneous Speech Corpora for language learners of Spanish, Chinese and Japanese
Authors: Moreno-S, Antonio oval, Leonardo Campillos Llanos, Yang Dong, Emi Takamori, Jos{\'e} M. Guirao, Paula Gozalo, Chieko Kimura, Kengo Matsui, Marta Garrote-Salazar
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper presents a method for designing, compiling and annotating corpora intended for language learners. In particular, we focus on spoken corpora for being used as complementary material in the classroom as well as in examinations. We describe the three corpora (Spanish, Chinese and Japanese) compiled by the Laboratorio de Ling{\"u}{\'\i}stica Inform{\'a}tica at the Autonomous University of Madrid (LLI-UAM). A web-based concordance tool has been used to search for examples in the corpus, and providing the text along with the corresponding audio. Teaching materials from the corpus, consisting the texts, the audio files and exercises on them, are currently on development.
TED-LIUM: an Automatic Speech Recognition dedicated corpus
Authors: Anthony Rousseau, Paul Del{\'e}glise, Yannick Est{\`e}ve
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Language Modelling, speech-recognition, Speech Recognition

This paper presents the corpus developed by the LIUM for Automatic Speech Recognition (ASR), based on the TED Talks. This corpus was built during the IWSLT 2011 Evaluation Campaign, and is composed of 118 hours of speech with its accompanying automatically aligned transcripts. We describe the content of the corpus, how the data was collected and processed, how it will be publicly available and how we built an ASR system using this data leading to a WER score of 17.4 {\%}. The official results we obtained at the IWSLT 2011 evaluation campaign are also discussed.
The SYNC3 Collaborative Annotation Tool
Authors: Georgios Petasis
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The huge amount of the available information in the Web creates the need of effective information extraction systems that are able to produce metadata that satisfy user's information needs. The development of such systems, in the majority of cases, depends on the availability of an appropriately annotated corpus in order to learn or evaluate extraction models. The production of such corpora can be significantly facilitated by annotation tools, that provide user-friendly facilities and enable annotators to annotate documents according to a predefined annotation schema. However, the construction of annotation tools that operate in a distributed environment is a challenging task: the majority of these tools are implemented as Web applications, having to cope with the capabilities offered by browsers. This paper describes the SYNC3 collaborative annotation tool, which implements an alternative architecture: it remains a desktop application, fully exploiting the advantages of desktop applications, but provides collaborative annotation through the use of a centralised server for storing both the documents and their metadata, and instance messaging protocols for communicating events among all annotators. The annotation tool is implemented as a component of the Ellogon language engineering platform, exploiting its extensive annotation engine, its cross-platform abilities and its linguistic processing components, if such a need arises. Finally, the SYNC3 annotation tool is distributed with an open source license, as part of the Ellogon platform.
ELRA in the heart of a cooperative HLT world
Authors: Val{\'e}rie Mapelli, Victoria Arranz, Matthieu Carr{\'e}, H{\'e}l{\`e}ne Mazo, Djamel Mostefa, Khalid Choukri
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper aims at giving an overview of ELRAs recent activities. The first part elaborates on ELRAs means of boosting the sharing Language Resources (LRs) within the HLT community through its catalogues, LRE-Map initiative, as well as its work towards the integration of its LRs within the META-SHARE open infrastructure. The second part shows how ELRA helps in the development and evaluation of HLT, in particular through its numerous participations to collaborative projects for the production of resources and platforms to facilitate their production and exploitation. A third part focuses on ELRAs work for clearing IPR issues in a HLT-oriented context, one of its latest initiative being its involvement in a Fair Research Act proposal to promote the easy access to LRs to the widest community. Finally, the last part elaborates on recent actions for disseminating information and promoting cooperation in the field, e.g. an the Language Library being launched at LREC2012 and the creation of an International Standard LR Number, a LR unique identifier to enable the accurate identification of LRs. Among the other messages ELRA will be conveying the attendees are the announcement of a set of freely available resources, the establishment of a LR and Evaluation forum, etc.
Automatic Translation of Scientific Documents in the HAL Archive
Authors: Patrik Lambert, Holger Schwenk, Fr{\'e}d{\'e}ric Blain
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Domain Adaptation, Machine Translation, Translation

This paper describes the development of a statistical machine translation system between French and English for scientific papers. This system will be closely integrated into the French HAL open archive, a collection of more than 100.000 scientific papers. We describe the creation of in-domain parallel and monolingual corpora, the development of a domain specific translation system with the created resources, and its adaptation using monolingual resources only. These techniques allowed us to improve a generic system by more than 10 BLEU points.
Irregularity Detection in Categorized Document Corpora
Authors: Borut Sluban, Senja Pollak, Roel Coesemans, Nada Lavra{\v{c}}
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Articles, Document Classification, Outlier Detection, Text Categorization

The paper presents an approach to extract irregularities in document corpora, where the documents originate from different sources and the analyst's interest is to find documents which are atypical for the given source. The main contribution of the paper is a voting-based approach to irregularity detection and its evaluation on a collection of newspaper articles from two sources: Western (UK and US) and local (Kenyan) media. The evaluation of a domain expert proves that the method is very effective in uncovering interesting irregularities in categorized document corpora.
The REPERE Corpus : a multimodal corpus for person recognition
Authors: Aude Giraudel, Matthieu Carr{\'e}, Val{\'e}rie Mapelli, Juliette Kahn, Olivier Galibert, Ludovic Quintard
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Person Recognition

The REPERE Challenge aims to support research on people recognition in multimodal conditions. To assess the technology progression, annual evaluation campaigns will be organized from 2012 to 2014. In this context, the REPERE corpus, a French videos corpus with multimodal annotation, has been developed. This paper presents datasets collected for the dry run test that took place at the beginning of 2012. Specific annotation tools and guidelines are mainly described. At the time being, 6 hours of data have been collected and annotated. Last section presents analyses of annotation distribution and interaction between modalities in the corpus.
Lemmatising Serbian as Category Tagging with Bidirectional Sequence Classification
Authors: Andrea Gesmundo, Tanja Samard{\v{z}}i{\'c}
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Classification, General Classification, Information Retrieval, Morphological Analysis, Semantic Parsing

We present a novel tool for morphological analysis of Serbian, which is a low-resource language with rich morphology. Our tool produces lemmatisation and morphological analysis reaching accuracy that is considerably higher compared to the existing alternative tools: 83.6{\%} relative error reduction on lemmatisation and 8.1{\%} relative error reduction on morphological analysis. The system is trained on a small manually annotated corpus with an approach based on Bidirectional Sequence Classification and Guided Learning techniques, which have recently been adapted with success to a broad set of NLP tagging tasks. In the system presented in this paper, this general approach to tagging is applied to the lemmatisation task for the first time thanks to our novel formulation of lemmatisation as a category tagging task. We show that learning lemmatisation rules from annotated corpus and integrating the context information in the process of morphological analysis provides a state-of-the-art performance despite the lack of resources. The proposed system can be used via a web GUI that deploys its best scoring configuration
Efficient Dependency Graph Matching with the IMS Open Corpus Workbench
Authors: Thomas Proisl, Peter Uhrig
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Dependency Parsing, Graph Matching, Information Retrieval, Sentence

State-of-the-art dependency representations such as the Stanford Typed Dependencies may represent the grammatical relations in a sentence as directed, possibly cyclic graphs. Querying a syntactically annotated corpus for grammatical structures that are represented as graphs requires graph matching, which is a non-trivial task. In this paper, we present an algorithm for graph matching that is tailored to the properties of large, syntactically annotated corpora. The implementation of the algorithm is built on top of the popular IMS Open Corpus Workbench, allowing corpus linguists to re-use existing infrastructure. An evaluation of the resulting software, CWB-treebank, shows that its performance in real world applications, such as a web query interface, compares favourably to implementations that rely on a relational database or a dedicated graph database while at the same time offering a greater expressive power for queries. An intuitive graphical interface for building the query graphs is available via the Treebank.info project.
Strategies to Improve a Speaker Diarisation Tool
Authors: David Tavarez, Eva Navas, Daniel Erro, Ibon Saratxaga
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

This paper describes the different strategies used to improve the results obtained by an off-line speaker diarisation tool with the Albayzin 2010 diarisation database. The errors made by the system have been analyzed and different strategies have been proposed to reduce each kind of error. Very short segments incorrectly labelled and different appearances of one speaker labelled with different identifiers are the most common errors. A post-processing module that refines the segmentation by retraining the GMM models of the speakers involved has been built to cope with these errors. This post-processing module has been tuned with the training dataset and improves the result of the diarisation system by 16.4{\%} in the test dataset.
Effects of Document Clustering in Modeling Wikipedia-style Term Descriptions
Authors: Atsushi Fujii, Yuya Fujii, Takenobu Tokunaga
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Articles, Clustering, Cultural Vocal Bursts Intensity Prediction

Reflecting the rapid growth of science, technology, and culture, it has become common practice to consult tools on the World Wide Web for various terms. Existing search engines provide an enormous volume of information, but retrieved information is not organized. Hand-compiled encyclopedias provide organized information, but the quantity of information is limited. In this paper, aiming to integrate the advantages of both tools, we propose a method to organize a search result based on multiple viewpoints as in Wikipedia. Because viewpoints required for explanation are different depending on the type of a term, such as animal and disease, we model articles in Wikipedia to extract a viewpoint structure for each term type. To identify a set of term types, we independently use manual annotation and automatic document clustering for Wikipedia articles. We also propose an effective feature for clustering of Wikipedia articles. We experimentally show that the document clustering reduces the cost for the manual annotation while maintaining the accuracy for modeling Wikipedia articles.
MaltOptimizer: A System for MaltParser Optimization
Authors: Miguel Ballesteros, Joakim Nivre
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Dependency Parsing

Freely available statistical parsers often require careful optimization to produce state-of-the-art results, which can be a non-trivial task especially for application developers who are not interested in parsing research for its own sake. We present MaltOptimizer, a freely available tool developed to facilitate parser optimization using the open-source system MaltParser, a data-driven parser-generator that can be used to train dependency parsers given treebank data. MaltParser offers a wide range of parameters for optimization, including nine different parsing algorithms, two different machine learning libraries (each with a number of different learners), and an expressive specification language that can be used to define arbitrarily rich feature models. MaltOptimizer is an interactive system that first performs an analysis of the training set in order to select a suitable starting point for optimization and then guides the user through the optimization of parsing algorithm, feature model, and learning algorithm. Empirical evaluation on data from the CoNLL 2006 and 2007 shared tasks on dependency parsing shows that MaltOptimizer consistently improves over the baseline of default settings and sometimes even surpasses the result of manual optimization.
Building Text-To-Speech Voices in the Cloud
Authors: Alistair Conkie, Thomas Okken, Yeon-Jun Kim, Giuseppe Di Fabbrizio
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Speech Recognition, Speech Synthesis, text-to-speech, Text to Speech

The AT{\&}T VoiceBuilder provides a new tool to researchers and practitioners who want to have their voices synthesized by a high-quality commercial-grade text-to-speech system without the need to install, configure, or manage speech processing software and equipment.It is implemented as a web service on the AT{\&}T Speech Mashup Portal.The system records and validates users' utterances, processes them to build a synthetic voice and provides a web service API to make the voice available to real-time applications through a scalable cloud-based processing platform. All the procedures are automated to avoid human intervention. We present experimental comparisons of voices built using the system.
On the practice of error analysis for machine translation evaluation
Authors: Sara Stymne, Lars Ahrenberg
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, Translation

Error analysis is a means to assess machine translation output in qualitative terms, which can be used as a basis for the generation of error profiles for different systems. As for other subjective approaches to evaluation it runs the risk of low inter-annotator agreement, but very often in papers applying error analysis to MT, this aspect is not even discussed. In this paper, we report results from a comparative evaluation of two systems where agreement initially was low, and discuss the different ways we used to improve it. We compared the effects of using more or less fine-grained taxonomies, and the possibility to restrict analysis to short sentences only. We report results on inter-annotator agreement before and after measures were taken, on error categories that are most likely to be confused, and on the possibility to establish error profiles also in the absence of a high inter-annotator agreement.
Croatian Dependency Treebank: Recent Development and Initial Experiments
Authors: Da{\v{s}}a Berovi{\'c}, {\v{Z}}eljko Agi{\'c}, Marko Tadi{\'c}
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Dependency Parsing, Language Modelling

We present the current state of development of the Croatian Dependency Treebank ― with special empahsis on adapting the Prague Dependency Treebank formalism to Croatian language specifics ― and illustrate its possible applications in an experiment with dependency parsing using MaltParser. The treebank currently contains approximately 2870 sentences, out of which the 2699 sentences and 66930 tokens were used in this experiment. Three linear-time projective algorithms implemented by the MaltParser system ― Nivre eager, Nivre standard and stack projective ― running on default settings were used in the experiment. The highest performing system, implementing the Nivre eager algorithm, scored (LAS 71.31 UAS 80.93 LA 83.87) within our experiment setup. The results obtained serve as an illustration of treebank's usefulness in natural language processing research and as a baseline for further research in dependency parsing of Croatian.
Evaluation of the KomParse Conversational Non-Player Characters in a Commercial Virtual World
Authors: Tina Kluewer, Feiyu Xu, Peter Adolphs, Hans Uszkoreit
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Natural Language Understanding, Question Answering

The paper describes the evaluation of the KomParse system. KomParse is a dialogue system embedded in a 3-D massive multiplayer online game, allowing conversations between non player characters (NPCs) and game users. In a field test with game users, the system was evaluated with respect to acceptability and usability of the overall system as well as task completion, dialogue control and efficiency of three conversational tasks. Furthermore, subjective feedback has been collected for evaluating the single communication components of the system such as natural language understanding. The results are very satisfying and promising. In general, both the usability and acceptability tests show that the tested NPC is useful and well-accepted by the users. Even if the NPC does not always understand the users well and expresses things unexpected, he could still provide appropriate responses to help users to solve their problems or entertain them.
Using Language Resources in Humanities research
Authors: Marta Villegas, Nuria Bel, Carlos Gonzalo, Amparo Moreno, Nuria Simelio
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

In this paper we present two real cases, in the fields of discourse analysis of newspapers and communication research which demonstrate the impact of Language Resources (LR) and NLP in the humanities. We describe our collaboration with (i) the Feminario research group from the UAB which has been investigating androcentric practices in Spanish general press since the 80s and whose research suggests that Spanish general press has undergone a dehumanization process that excludes women and men and (ii) the Municipals'11 online project which investigates the Spanish local election campaign in the blogosphere. We will see how NLP tools and LRs make possible the so called e-Humanities research' as they provide Humanities with tools to perform intensive and automatic text analyses. Language technologies have evolved a lot and are mature enough to provide useful tools to researchers dealing with large amount of textual data. The language resources that have been developed within the field of NLP have proven to be useful for other disciplines that are unaware of their existence and nevertheless would greatly benefit from them as they provide (i) exhaustiveness -to guarantee that data coverage is wide and representative enough- and (ii) reliable and significant results -to guarantee that the reported results are statistically significant.
A Treebank-driven Creation of an OntoValence Verb lexicon for Bulgarian
Authors: Petya Osenova, Kiril Simov, Laska Laskova, Stanislava Kancheva
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5

The paper presents a treebank-driven approach to the construction of a Bulgarian valence lexicon with ontological restrictions over the inner participants of the event. First, the underlying ideas behind the Bulgarian Ontology-based lexicon are outlined. Then, the extraction and manipulation of the valence frames is discussed with respect to the BulTreeBank annotation scheme and DOLCE ontology. Also, the most frequent types of syntactic frames are specified as well as the most frequent types of ontological restrictions over the verb arguments. The envisaged application of such a lexicon would be: in assigning ontological labels to syntactically parsed corpora, and expanding the lexicon and lexical information in the Bulgarian Resource Grammar.
Integrating NLP Tools in a Distributed Environment: A Case Study Chaining a Tagger with a Dependency Parser
Authors: Francesco Rubino, Francesca Frontini, Valeria Quochi
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Machine Translation, POS, POS Tagging, TAG

The present paper tackles the issue of PoS tag conversion within the framework of a distributed web service platform for the automatic creation of language resources. PoS tagging is now considered a ''''''``solved problem''''''''; yet, because of the differences in the tagsets, interchange of the various PoS tagger available is still hampered. In this paper we describe the implementation of a pos-tagged-corpus converter, which is needed for chaining together in a workflow the Freeling PoS tagger for Italian and the DESR dependency parser, given that these two tools have been developed independently. The conversion problems experienced during the implementation, related to the properties of the different tagsets and of tagset conversion in general, are discussed together with the heuristics implemented in the attempt to solve them. Finally, the converter is evaluated by assessing the impact of conversion on the performance of the dependency parser. From this we learn that in most cases parsing errors are due to actual tagging errors, and not to conversion itself. Besides, information on accuracy loss is an important feature in a distributed environment of (NLP) services, where users need to decide which services best suit their needs.
Spell Checking for Chinese
Authors: Shaohua Yang, Hai Zhao, Xiaolin Wang, Bao-liang Lu
Date: 2012-05-01 00:00:00
Proceeding: LREC 2012 5
Tasks: Chinese Spell Checking

This paper presents some novel results on Chinese spell checking. In this paper, a concise algorithm based on minimized-path segmentation is proposed to reduce the cost and suit the needs of current Chinese input systems. The proposed algorithm is actually derived from a simple assumption that spelling errors often make the number of segments larger. The experimental results are quite positive and implicitly verify the effectiveness of the proposed assumption. Finally, all approaches work together to output a result much better than the baseline with 12{\%} performance improvement.