pwc-archive/papers-with-abstracts huggingface dataset:
Linked Open Data and Web Corpus Data for noun compound bracketing
Authors: Pierre Andr{\'e} M{\'e}nard, Caroline Barri{\`e}re
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

This research provides a comparison of a linked open data resource (DBpedia) and web corpus data resources (Google Web Ngrams and Google Books Ngrams) for noun compound bracketing. Large corpus statistical analysis has often been used for noun compound bracketing, and our goal is to introduce a linked open data (LOD) resource for such task. We show its particularities and its performance on the task. Results obtained on resources tested individually are promising, showing a potential for DBpedia to be included in future hybrid systems.
Multimodal Corpora for Silent Speech Interaction
Authors: Jo{\~a}o Freitas, Ant{\'o}nio Teixeira, Miguel Dias
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), speech-recognition, Speech Recognition

A Silent Speech Interface (SSI) allows for speech communication to take place in the absence of an acoustic signal. This type of interface is an alternative to conventional Automatic Speech Recognition which is not adequate for users with some speech impairments or in the presence of environmental noise. The work presented here produces the conditions to explore and analyze complex combinations of input modalities applicable in SSI research. By exploring non-invasive and promising modalities, we have selected the following sensing technologies used in human-computer interaction: Video and Depth input, Ultrasonic Doppler sensing and Surface Electromyography. This paper describes a novel data collection methodology where these independent streams of information are synchronously acquired with the aim of supporting research and development of a multimodal SSI. The reported recordings were divided into two rounds: a first one where the acquired data was silently uttered and a second round where speakers pronounced the scripted prompts in an audible and normal tone. In the first round of recordings, a total of 53.94 minutes were captured where 30.25{\%} was estimated to be silent speech. In the second round of recordings, a total of 30.45 minutes were obtained and 30.05{\%} of the recordings were audible speech.
Constructing a Corpus of Japanese Predicate Phrases for Synonym/Antonym Relations
Authors: Tomoko Izumi, Tomohide Shibata, Hisako Asano, Yoshihiro Matsuo, Sadao Kurohashi
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Binary Classification, General Classification, Information Retrieval

We construct a large corpus of Japanese predicate phrases for synonym-antonym relations. The corpus consists of 7,278 pairs of predicates such as receive-permission (ACC) vs. obtain-permission (ACC), in which each predicate pair is accompanied by a noun phrase and case information. The relations are categorized as synonyms, entailment, antonyms, or unrelated. Antonyms are further categorized into three different classes depending on their aspect of oppositeness. Using the data as a training corpus, we conduct the supervised binary classification of synonymous predicates based on linguistically-motivated features. Combining features that are characteristic of synonymous predicates with those that are characteristic of antonymous predicates, we succeed in automatically identifying synonymous predicates at the high F-score of 0.92, a 0.4 improvement over the baseline method of using the Japanese WordNet. The results of an experiment confirm that the quality of the corpus is high enough to achieve automatic classification. To the best of our knowledge, this is the first and the largest publicly available corpus of Japanese predicate phrases for synonym-antonym relations.
The Impact of Cohesion Errors in Extraction Based Summaries
Authors: Evelina Rennes, Arne J{\"o}nsson
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Text Summarization

We present results from an eye tracking study of automatic text summarization. Automatic text summarization is a growing field due to the modern world{'}s Internet based society, but to automatically create perfect summaries is challenging. One problem is that extraction based summaries often have cohesion errors. By the usage of an eye tracking camera, we have studied the nature of four different types of cohesion errors occurring in extraction based summaries. A total of 23 participants read and rated four different texts and marked the most difficult areas of each text. Statistical analysis of the data revealed that absent cohesion or context and broken anaphoric reference (pronouns) caused some disturbance in reading, but that the impact is restricted to the effort to read rather than the comprehension of the text. However, erroneous anaphoric references (pronouns) were not always detected by the participants which poses a problem for automatic text summarizers. The study also revealed other potential disturbing factors.
The CUHK Discourse TreeBank for Chinese: Annotating Explicit Discourse Connectives for the Chinese TreeBank
Authors: Lanjun Zhou, Binyang Li, Zhongyu Wei, Kam-Fai Wong
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Part-Of-Speech Tagging, Question Answering, Sentence, Sentence Compression, Sentiment Analysis, Text Generation

The lack of open discourse corpus for Chinese brings limitations for many natural language processing tasks. In this work, we present the first open discourse treebank for Chinese, namely, the Discourse Treebank for Chinese (DTBC). At the current stage, we annotated explicit intra-sentence discourse connectives, their corresponding arguments and senses for all 890 documents of the Chinese Treebank 5. We started by analysing the characteristics of discourse annotation for Chinese, adapted the annotation scheme of Penn Discourse Treebank 2 (PDTB2) to Chinese language while maintaining the compatibility as far as possible. We made adjustments to 3 essential aspects according to the previous study of Chinese linguistics. They are sense hierarchy, argument scope and semantics of arguments. Agreement study showed that our annotation scheme could achieve highly reliable results.
Extraction of Daily Changing Words for Question Answering
Authors: Kugatsu Sadamitsu, Ryuichiro Higashinaka, Yoshihiro Matsuo
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: BIG-bench Machine Learning, Question Answering, Template Matching

This paper proposes a method for extracting Daily Changing Words (DCWs), words that indicate which questions are real-time dependent. Our approach is based on two types of template matching using time and named entity slots from large size corpora and adding simple filtering methods from news corpora. Extracted DCWs are utilized for detecting and sorting real-time dependent questions. Experiments confirm that our DCW method achieves higher accuracy in detecting real-time dependent questions than existing word classes and a simple supervised machine learning approach.
MTWatch: A Tool for the Analysis of Noisy Parallel Data
Authors: D, S apat, ipan, Declan Groves
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Classification, General Classification, Machine Translation, Sentence, Translation

State-of-the-art statistical machine translation (SMT) technique requires a good quality parallel data to build a translation model. The availability of large parallel corpora has rapidly increased over the past decade. However, often these newly developed parallel data contains contain significant noise. In this paper, we describe our approach for classifying good quality parallel sentence pairs from noisy parallel data. We use 10 different features within a Support Vector Machine (SVM)-based model for our classification task. We report a reasonably good classification accuracy and its positive effect on overall MT accuracy.
Distributed Distributional Similarities of Google Books Over the Centuries
Authors: Martin Riedl, Richard Steuer, Chris Biemann
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Graph Clustering

This paper introduces a distributional thesaurus and sense clusters computed on the complete Google Syntactic N-grams, which is extracted from Google Books, a very large corpus of digitized books published between 1520 and 2008. We show that a thesaurus computed on such a large text basis leads to much better results than using smaller corpora like Wikipedia. We also provide distributional thesauri for equal-sized time slices of the corpus. While distributional thesauri can be used as lexical resources in NLP tasks, comparing word similarities over time can unveil sense change of terms across different decades or centuries, and can serve as a resource for diachronic lexicography. Thesauri and clusters are available for download.
The CLE Urdu POS Tagset
Authors: Saba Urooj, Sarmad Hussain, Asad Mustafa, Rahila Parveen, Farah Adeeba, Tafseer Ahmed Khan, Miriam Butt, Annette Hautli
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation, POS, TAG

The paper presents a design schema and details of a new Urdu POS tagset. This tagset is designed due to challenges encountered in working with existing tagsets for Urdu. It uses tags that judiciously incorporate information about special morpho-syntactic categories found in Urdu. With respect to the overall naming schema and the basic divisions, the tagset draws on the Penn Treebank and a Common Tagset for Indian Languages. The resulting CLE Urdu POS Tagset consists of 12 major categories with subdivisions, resulting in 32 tags. The tagset has been used to tag 100k words of the CLE Urdu Digest Corpus, giving a tagging accuracy of 96.8{\%}.
NoSta-D Named Entity Annotation for German: Guidelines and Dataset
Authors: Darina Benikova, Chris Biemann, Marc Reznicek
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: named-entity-recognition, Named Entity Recognition, Named Entity Recognition (NER), NER, Question Answering, Semantic Parsing

We describe the annotation of a new dataset for German Named Entity Recognition (NER). The need for this dataset is motivated by licensing issues and consistency issues of existing datasets. We describe our approach to creating annotation guidelines based on linguistic and semantic considerations, and how we iteratively refined and tested them in the early stages of annotation in order to arrive at the largest publicly available dataset for German NER, consisting of over 31,000 manually annotated sentences (over 591,000 tokens) from German Wikipedia and German online news. We provide a number of statistics on the dataset, which indicate its high quality, and discuss legal aspects of distributing the data as a compilation of citations. The data is released under the permissive CC-BY license, and will be fully available for download in September 2014 after it has been used for the GermEval 2014 shared task on NER. We further provide the full annotation guidelines and links to the annotation tool used for the creation of this resource.
Phone Boundary Annotation in Conversational Speech
Authors: Yi-Fen Liu, Shu-Chuan Tseng, J.-S. Roger Jang
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: valid

Phone-aligned spoken corpora are indispensable language resources for quantitative linguistic analyses and automatic speech systems. However, producing this type of data resources is not an easy task due to high costs of time and man power as well as difficulties of applying valid annotation criteria and achieving reliable inter-labelerÂ’s consistency. Among different types of spoken corpora, conversational speech that is often filled with extreme reduction and varying pronunciation variants is particularly challenging. By adopting a combined verification procedure, we obtained reasonably good annotation results. Preliminary phone boundaries that were automatically generated by a phone aligner were provided to human labelers for verifying. Instead of making use of the visualization of acoustic cues, the labelers should solely rely on their perceptual judgments to locate a position that best separates two adjacent phones. Impressionistic judgments in cases of reduction and segment deletion were helpful and necessary, as they balanced subtle nuance caused by differences in perception.
A Colloquial Corpus of Japanese Sign Language: Linguistic Resources for Observing Sign Language Conversations
Authors: Mayumi Bono, Kouhei Kikuchi, Paul Cibulka, Yutaka Osugi
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

We began building a corpus of Japanese Sign Language (JSL) in April 2011. The purpose of this project was to increase awareness of sign language as a distinctive language in Japan. This corpus is beneficial not only to linguistic research but also to hearing-impaired and deaf individuals, as it helps them to recognize and respect their linguistic differences and communication styles. This is the first large-scale JSL corpus developed for both academic and public use. We collected data in three ways: interviews (for introductory purposes only), dialogues, and lexical elicitation. In this paper, we focus particularly on data collected during a dialogue to discuss the application of conversation analysis (CA) to signed dialogues and signed conversations. Our annotation scheme was designed not only to elucidate theoretical issues related to grammar and linguistics but also to clarify pragmatic and interactional phenomena related to the use of JSL.
Walenty: Towards a comprehensive valence dictionary of Polish
Authors: Adam Przepi{\'o}rkowski, El{\.z}bieta Hajnicz, Agnieszka Patejuk, Marcin Woli{\'n}ski, Filip Skwarski, Marek {\'S}widzi{\'n}ski
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

This paper presents Walenty, a comprehensive valence dictionary of Polish, with a number of novel features, as compared to other such dictionaries. The notion of argument is based on the coordination test and takes into consideration the possibility of diverse morphosyntactic realisations. Some aspects of the internal structure of phraseological (idiomatic) arguments are handled explicitly. While the current version of the dictionary concentrates on syntax, it already contains some semantic features, including semantically defined arguments, such as locative, temporal or manner, as well as control and raising, and work on extending it with semantic roles and selectional preferences is in progress. Although Walenty is still being intensively developed, it is already by far the largest Polish valence dictionary, with around 8600 verbal lemmata and almost 39 000 valence schemata. The dictionary is publicly available on the Creative Commons BY SA licence and may be downloaded from http://zil.ipipan.waw.pl/Walenty.
Can the Crowd be Controlled?: A Case Study on Crowd Sourcing and Automatic Validation of Completed Tasks based on User Modeling
Authors: Balamurali A.R
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Sentiment Analysis

Annotation is an essential step in the development cycle of many Natural Language Processing (NLP) systems. Lately, crowd-sourcing has been employed to facilitate large scale annotation at a reduced cost. Unfortunately, verifying the quality of the submitted annotations is a daunting task. Existing approaches address this problem either through sampling or redundancy. However, these approaches do have a cost associated with it. Based on the observation that a crowd-sourcing worker returns to do a task that he has done previously, a novel framework for automatic validation of crowd-sourced task is proposed in this paper. A case study based on sentiment analysis is presented to elucidate the framework and its feasibility. The result suggests that validation of the crowd-sourced task can be automated to a certain extent.
Computational Narratology: Extracting Tense Clusters from Narrative Texts
Authors: Thomas B{\"o}gel, Jannik Str{\"o}tgen, Michael Gertz
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Event Extraction, Morphological Tagging

Computational Narratology is an emerging field within the Digital Humanities. In this paper, we tackle the problem of extracting temporal information as a basis for event extraction and ordering, as well as further investigations of complex phenomena in narrative texts. While most existing systems focus on news texts and extract explicit temporal information exclusively, we show that this approach is not feasible for narratives. Based on tense information of verbs, we define temporal clusters as an annotation task and validate the annotation schema by showing that the task can be performed with high inter-annotator agreement. To alleviate and reduce the manual annotation effort, we propose a rule-based approach to robustly extract temporal clusters using a multi-layered and dynamic NLP pipeline that combines off-the-shelf components in a heuristic setting. Comparing our results against human judgements, our system is capable of predicting the tense of verbs and sentences with very high reliability: for the most prevalent tense in our corpus, more than 95{\%} of all verbs are annotated correctly.
Designing the Latvian Speech Recognition Corpus
Authors: M{\=a}rcis Pinnis, Ilze Auzi{\c{n}}a, K{\=a}rlis Goba
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: speech-recognition, Speech Recognition, Speech Synthesis

In this paper the authors present the first Latvian speech corpus designed specifically for speech recognition purposes. The paper outlines the decisions made in the corpus designing process through analysis of related work on speech corpora creation for different languages. The authors provide also guidelines that were used for the creation of the Latvian speech recognition corpus. The corpus creation guidelines are fairly general for them to be re-used by other researchers when working on different language speech recognition corpora. The corpus consists of two parts â€• an orthographically annotated corpus containing 100 hours of orthographically transcribed audio data and a phonetically annotated corpus containing 4 hours of phonetically transcribed audio data. Metadata files in XML format provide additional details about the speakers, noise levels, speech styles, etc. The speech recognition corpus is phonetically balanced and phonetically rich and the paper describes also the methodology how the phonetical balancedness has been assessed.
Aligning parallel texts with InterText
Authors: Pavel Vond{\v{r}}i{\v{c}}ka
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

InterText is a flexible manager and editor for alignment of parallel texts aimed both at individual and collaborative creation of parallel corpora of any size or translational memories. It is available in two versions: as a multi-user server application with a web-based interface and as a native desktop application for personal use. Both versions are able to cooperate with each other. InterText can process plain text or custom XML documents, deploy existing automatic aligners and provide a comfortable interface for manual post-alignment correction of both the alignment and the text contents and segmentation of the documents. One language version may be aligned with several other versions (using stand-off alignment) and the application ensures consistency between them. The server version supports different user levels and privileges and it can also track changes made to the texts for easier supervision. It also allows for batch import, alignment and export and can be connected to other tools and scripts for better integration in a more complex project workflow.
Corpus for Coreference Resolution on Scientific Papers
Authors: Panot Chaimongkol, Akiko Aizawa, Yuka Tateisi
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: coreference-resolution, Coreference Resolution, Optical Character Recognition (OCR)

The ever-growing number of published scientific papers prompts the need for automatic knowledge extraction to help scientists keep up with the state-of-the-art in their respective fields. To construct a good knowledge extraction system, annotated corpora in the scientific domain are required to train machine learning models. As described in this paper, we have constructed an annotated corpus for coreference resolution in multiple scientific domains, based on an existing corpus. We have modified the annotation scheme from Message Understanding Conference to better suit scientific texts. Then we applied that to the corpus. The annotated corpus is then compared with corpora in general domains in terms of distribution of resolution classes and performance of the Stanford Dcoref coreference resolver. Through these comparisons, we have demonstrated quantitatively that our manually annotated corpus differs from a general-domain corpus, which suggests deep differences between general-domain texts and scientific texts and which shows that different approaches can be made to tackle coreference resolution for general texts and scientific texts.
From Non Word to New Word: Automatically Identifying Neologisms in French Newspapers
Authors: Ingrid Falk, Delphine Bernhard, Christophe G{\'e}rard
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: BIG-bench Machine Learning, Form

In this paper we present a statistical machine learning approach to formal neologism detection going some way beyond the use of exclusion lists. We explore the impact of three groups of features: form related, morpho-lexical and thematic features. The latter type of features has not yet been used in this kind of application and represents a way to access the semantic context of new words. The results suggest that form related features are helpful at the overall classification task, while morpho-lexical and thematic features better single out true neologisms.
Evaluating the effects of interactivity in a post-editing workbench
Authors: Nancy Underwood, Bartolom{\'e} Mesa-Lao, Mercedes Garc{\'\i}a Mart{\'\i}nez, Michael Carl, Vicent Alabau, Jes{\'u}s Gonz{\'a}lez-Rubio, Luis A. Leiva, Germ{\'a}n Sanchis-Trilles, Daniel Ort{\'\i}z-Mart{\'\i}nez, Francisco Casacuberta
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5
Tasks: Machine Translation

This paper describes the field trial and subsequent evaluation of a post-editing workbench which is currently under development in the EU-funded CasMaCat project. Based on user evaluations of the initial prototype of the workbench, this second prototype of the workbench includes a number of interactive features designed to improve productivity and user satisfaction. Using CasMaCat{'}s own facilities for logging keystrokes and eye tracking, data were collected from nine post-editors in a professional setting. These data were then used to investigate the effects of the interactive features on productivity, quality, user satisfaction and cognitive load as reflected in the post-editorsÂ’ gaze activity. These quantitative results are combined with the qualitative results derived from user questionnaires and interviews conducted with all the participants.
The Research and Teaching Corpus of Spoken German --- FOLK
Authors: Thomas Schmidt
Date: 2014-05-01 00:00:00
Proceeding: LREC 2014 5

FOLK is the {``}Forschungs- und Lehrkorpus Gesprochenes Deutsch (FOLK){''} (eng.: research and teaching corpus of spoken German). The project has set itself the aim of building a corpus of German conversations which a) covers a broad range of interaction types in private, institutional and public settings, b) is sufficiently large and diverse and of sufficient quality to support different qualitative and quantitative research approaches, c) is transcribed, annotated and made accessible according to current technological standards, and d) is available to the scientific community on a sound legal basis and without unnecessary restrictions of usage. This paper gives an overview of the corpus design, the strategies for acquisition of a diverse range of interaction data, and the corpus construction workflow from recording via transcription an annotation to dissemination.