pwc-archive/papers-with-abstracts huggingface dataset:
A Semantically Compositional Annotation Scheme for Time Normalization
Authors: Steven Bethard, Jonathan Parker
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Semantic Composition

We present a new annotation scheme for normalizing time expressions, such as {``}three days ago{''}, to computer-readable forms, such as 2016-03-07. The annotation scheme addresses several weaknesses of the existing TimeML standard, allowing the representation of time expressions that align to more than one calendar unit (e.g., {``}the past three summers{''}), that are defined relative to events (e.g., {``}three weeks postoperative{''}), and that are unions or intersections of smaller time expressions (e.g., {``}Tuesdays and Thursdays{''}). It achieves this by modeling time expression interpretation as the semantic composition of temporal operators like UNION, NEXT, and AFTER. We have applied the annotation scheme to 34 documents so far, producing 1104 annotations, and achieving inter-annotator agreement of 0.821.
PROMETHEUS: A Corpus of Proverbs Annotated with Metaphors
Authors: G{\"o}zde {\"O}zbal, Carlo Strapparava, Serra Sinem Tekiro{\u{g}}lu
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: English Proverbs

Proverbs are commonly metaphoric in nature and the mapping across domains is commonly established in proverbs. The abundance of proverbs in terms of metaphors makes them an extremely valuable linguistic resource since they can be utilized as a gold standard for various metaphor related linguistic tasks such as metaphor identification or interpretation. Besides, a collection of proverbs fromvarious languages annotated with metaphors would also be essential for social scientists to explore the cultural differences betweenthose languages. In this paper, we introduce PROMETHEUS, a dataset consisting of English proverbs and their equivalents in Italian.In addition to the word-level metaphor annotations for each proverb, PROMETHEUS contains other types of information such as the metaphoricity degree of the overall proverb, its meaning, the century that it was first recorded in and a pair of subjective questions responded by the annotators. To the best of our knowledge, this is the first multi-lingual and open-domain corpus of proverbs annotated with word-level metaphors.
Corpus Annotation within the French FrameNet: a Domain-by-domain Methodology
Authors: Marianne Djemaa, C, Marie ito, Philippe Muller, Laure Vieu
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

This paper reports on the development of a French FrameNet, within the ASFALDA project. While the first phase of the project focused on the development of a French set of frames and corresponding lexicon (Candito et al., 2014), this paper concentrates on the subsequent corpus annotation phase, which focused on four notional domains (commercial transactions, cognitive stances, causality and verbal communication). Given full coverage is not reachable for a relatively {``}new{''} FrameNet project, we advocate that focusing on specific notional domains allowed us to obtain full lexical coverage for the frames of these domains, while partially reflecting word sense ambiguities. Furthermore, as frames and roles were annotated on two French Treebanks (the French Treebank (Abeill{\'e} and Barrier, 2004) and the Sequoia Treebank (Candito and Seddah, 2012), we were able to extract a syntactico-semantic lexicon from the annotated frames. In the resource{'}s current status, there are 98 frames, 662 frame evoking words, 872 senses, and about 13000 annotated frames, with their semantic roles assigned to portions of text. The French FrameNet is freely available at alpage.inria.fr/asfalda.
Covering various Needs in Temporal Annotation: a Proposal of Extension of ISO TimeML that Preserves Upward Compatibility
Authors: Ana{\"\i}s Lefeuvre-Halftermeyer, Jean-Yves Antoine, Alain Couillault, Emmanuel Schang, Lotfi Abouda, Agata Savary, Denis Maurel, Iris Eshkol, Delphine Battistelli
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

This paper reports a critical analysis of the ISO TimeML standard, in the light of several experiences of temporal annotation that were conducted on spoken French. It shows that the norm suffers from weaknesses that should be corrected to fit a larger variety of needs inNLP and in corpus linguistics. We present our proposition of some improvements of the norm before it will be revised by the ISO Committee in 2017. These modifications concern mainly (1) Enrichments of well identified features of the norm: temporal function of TIMEX time expressions, additional types for TLINK temporal relations; (2) Deeper modifications concerning the units or features annotated: clarification between time and tense for EVENT units, coherence of representation between temporal signals (the SIGNAL unit) and TIMEX modifiers (the MOD feature); (3) A recommendation to perform temporal annotation on top of a syntactic (rather than lexical) layer (temporal annotation on a treebank).
A General Framework for the Annotation of Causality Based on FrameNet
Authors: Laure Vieu, Philippe Muller, C, Marie ito, Marianne Djemaa
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

We present here a general set of semantic frames to annotate causal expressions, with a rich lexicon in French and an annotated corpus of about 5000 instances of causal lexical items with their corresponding semantic frames. The aim of our project is to have both the largest possible coverage of causal phenomena in French, across all parts of speech, and have it linked to a general semantic framework such as FN, to benefit in particular from the relations between other semantic frames, e.g., temporal ones or intentional ones, and the underlying upper lexical ontology that enable some forms of reasoning. This is part of the larger ASFALDA French FrameNet project, which focuses on a few different notional domains which are interesting in their own right (Djemma et al., 2016), including cognitive positions and communication frames. In the process of building the French lexicon and preparing the annotation of the corpus, we had to remodel some of the frames proposed in FN based on English data, with hopefully more precise frame definitions to facilitate human annotation. This includes semantic clarifications of frames and frame elements, redundancy elimination, and added coverage. The result is arguably a significant improvement of the treatment of causality in FN itself.
Annotating Temporally-Anchored Spatial Knowledge on Top of OntoNotes Semantic Roles
Authors: Alakan Vempala, a, Eduardo Blanco
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: BIG-bench Machine Learning

This paper presents a two-step methodology to annotate spatial knowledge on top of OntoNotes semantic roles. First, we manipulate semantic roles to automatically generate potential additional spatial knowledge. Second, we crowdsource annotations with Amazon Mechanical Turk to either validate or discard the potential additional spatial knowledge. The resulting annotations indicate whether entities are or are not located somewhere with a degree of certainty, and temporally anchor this spatial information. Crowdsourcing experiments show that the additional spatial knowledge is ubiquitous and intuitive to humans, and experimental results show that it can be inferred automatically using standard supervised machine learning techniques.
SpaceRef: A corpus of street-level geographic descriptions
Authors: Jana G{\"o}tze, Johan Boye
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Position

This article describes SPACEREF, a corpus of street-level geographic descriptions. Pedestrians are walking a route in a (real) urban environment, describing their actions. Their position is automatically logged, their speech is manually transcribed, and their references to objects are manually annotated with respect to a crowdsourced geographic database. We describe how the data was collected and annotated, and how it has been used in the context of creating resources for an automatic pedestrian navigation system.
Persian Proposition Bank
Authors: Azadeh Mirzaei, Amirsaeid Moloodi
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Semantic Role Labeling

This paper describes the procedure of semantic role labeling and the development of the first manually annotated Persian Proposition Bank (PerPB) which added a layer of predicate-argument information to the syntactic structures of Persian Dependency Treebank (known as PerDT). Through the process of annotating, the annotators could see the syntactic information of all the sentences and so they annotated 29982 sentences with more than 9200 unique verbs. In the annotation procedure, the direct syntactic dependents of the verbs were the first candidates for being annotated. So we did not annotate the other indirect dependents unless their phrasal heads were propositional and had their own arguments or adjuncts. Hence besides the semantic role labeling of verbs, the argument structure of 1300 unique propositional nouns and 300 unique propositional adjectives were annotated in the sentences, too. The accuracy of annotation process was measured by double annotation of the data at two separate stages and finally the data was prepared in the CoNLL dependency format.
Typed Entity and Relation Annotation on Computer Science Papers
Authors: Yuka Tateisi, Tomoko Ohta, Sampo Pyysalo, Yusuke Miyao, Akiko Aizawa
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Articles, Relation

We describe our ongoing effort to establish an annotation scheme for describing the semantic structures of research articles in the computer science domain, with the intended use of developing search systems that can refine their results by the roles of the entities denoted by the query keys. In our scheme, mentions of entities are annotated with ontology-based types, and the roles of the entities are annotated as relations with other entities described in the text. So far, we have annotated 400 abstracts from the ACL anthology and the ACM digital library. In this paper, the scheme and the annotated dataset are described, along with the problems found in the course of annotation. We also show the results of automatic annotation and evaluate the corpus in a practical setting in application to topic extraction.
Enriching TimeBank: Towards a more precise annotation of temporal relations in a text
Authors: Volker Gast, Bierk, Lennart t, Stephan Druskat, Christoph Rzymski
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: POS

We propose a way of enriching the TimeML annotations of TimeBank by adding information about the Topic Time in terms of Klein (1994). The annotations are partly automatic, partly inferential and partly manual. The corpus was converted into the native format of the annotation software GraphAnno and POS-tagged using the Stanford bidirectional dependency network tagger. On top of each finite verb, a FIN-node with tense information was created, and on top of any FIN-node, a TOPICTIME-node, in accordance with Klein{'}s (1994) treatment of finiteness as the linguistic correlate of the Topic Time. Each TOPICTIME-node is linked to a MAKEINSTANCE-node representing an (instantiated) event in TimeML (Pustejovsky et al. 2005), the markup language used for the annotation of TimeBank. For such links we introduce a new category, ELINK. ELINKs capture the relationship between the Topic Time (TT) and the Time of Situation (TSit) and have an aspectual interpretation in Klein{'}s (1994) theory. In addition to these automatic and inferential annotations, some TLINKs were added manually. Using an example from the corpus, we show that the inclusion of the Topic Time in the annotations allows for a richer representation of the temporal structure than does TimeML. A way of representing this structure in a diagrammatic form similar to the T-Box format (Verhagen, 2007) is proposed.
How Diachronic Text Corpora Affect Context based Retrieval of OOV Proper Names for Audio News
Authors: Imran Sheikh, Irina Illina, Dominique Fohr
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Retrieval, speech-recognition, Speech Recognition

Out-Of-Vocabulary (OOV) words missed by Large Vocabulary Continuous Speech Recognition (LVCSR) systems can be recovered with the help of topic and semantic context of the OOV words captured from a diachronic text corpus. In this paper we investigate how the choice of documents for the diachronic text corpora affects the retrieval of OOV Proper Names (PNs) relevant to an audio document. We first present our diachronic French broadcast news datasets, which highlight the motivation of our study on OOV PNs. Then the effect of using diachronic text data from different sources and a different time span is analysed. With OOV PN retrieval experiments on French broadcast news videos, we conclude that a diachronic corpus with text from different sources leads to better retrieval performance than one relying on text from single source or from a longer time span.
Collecting Resources in Sub-Saharan African Languages for Automatic Speech Recognition: a Case Study of Wolof
Authors: Elodie Gauthier, Laurent Besacier, Sylvie Voisin, Michael Melese, Uriel Pascal Elingui
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), speech-recognition, Speech Recognition

This article presents the data collected and ASR systems developped for 4 sub-saharan african languages (Swahili, Hausa, Amharic and Wolof). To illustrate our methodology, the focus is made on Wolof (a very under-resourced language) for which we designed the first ASR system ever built in this language. All data and scripts are available online on our github repository.
SCALE: A Scalable Language Engineering Toolkit
Authors: Joris Pelemans, Lyan Verwimp, Kris Demuynck, Hugo Van hamme, Patrick Wambacq
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Language Modeling, Language Modelling

In this paper we present SCALE, a new Python toolkit that contains two extensions to n-gram language models. The first extension is a novel technique to model compound words called Semantic Head Mapping (SHM). The second extension, Bag-of-Words Language Modeling (BagLM), bundles popular models such as Latent Semantic Analysis and Continuous Skip-grams. Both extensions scale to large data and allow the integration into first-pass ASR decoding. The toolkit is open source, includes working examples and can be found on http://github.com/jorispelemans/scale.
Combining Manual and Automatic Prosodic Annotation for Expressive Speech Synthesis
Authors: S Brognaux, rine, Thomas Fran{\c{c}}ois, Marco Saerens
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Expressive Speech Synthesis, Speech Synthesis, TAG, text-to-speech, Text to Speech

Text-to-speech has long been centered on the production of an intelligible message of good quality. More recently, interest has shifted to the generation of more natural and expressive speech. A major issue of existing approaches is that they usually rely on a manual annotation in expressive styles, which tends to be rather subjective. A typical related issue is that the annotation is strongly influenced ― and possibly biased ― by the semantic content of the text (e.g. a shot or a fault may incite the annotator to tag that sequence as expressing a high degree of excitation, independently of its acoustic realization). This paper investigates the assumption that human annotation of basketball commentaries in excitation levels can be automatically improved on the basis of acoustic features. It presents two techniques for label correction exploiting a Gaussian mixture and a proportional-odds logistic regression. The automatically re-annotated corpus is then used to train HMM-based expressive speech synthesizers, the performance of which is assessed through subjective evaluations. The results indicate that the automatic correction of the annotation with Gaussian mixture helps to synthesize more contrasted excitation levels, while preserving naturalness.
BAS Speech Science Web Services - an Update of Current Developments
Authors: Thomas Kisler, Uwe Reichel, Florian Schiel, Christoph Draxler, Bernhard Jackl, Nina P{\"o}rner
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Grapheme-to-Phoneme Conversion

In 2012 the Bavarian Archive for Speech Signals started providing some of its tools from the field of spoken language in the form of Software as a Service (SaaS). This means users access the processing functionality over a web browser and therefore do not have to install complex software packages on a local computer. Amongst others, these tools include segmentation {\&} labeling, grapheme-to-phoneme conversion, text alignment, syllabification and metadata generation, where all but the last are available for a variety of languages. Since its creation the number of available services and the web interface have changed considerably. We give an overview and a detailed description of the system architecture, the available web services and their functionality. Furthermore, we show how the number of files processed over the system developed in the last four years.
SPA: Web-based Platform for easy Access to Speech Processing Modules
Authors: Fern Batista, o, Pedro Curto, Isabel Trancoso, Alberto Abad, Jaime Ferreira, Eug{\'e}nio Ribeiro, Helena Moniz, David Martins de Matos, Ricardo Ribeiro
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Age And Gender Classification, Gender Classification, General Classification, Single Particle Analysis

This paper presents SPA, a web-based Speech Analytics platform that integrates several speech processing modules and that makes it possible to use them through the web. It was developed with the aim of facilitating the usage of the modules, without the need to know about software dependencies and specific configurations. Apart from being accessed by a web-browser, the platform also provides a REST API for easy integration with other applications. The platform is flexible, scalable, provides authentication for access restrictions, and was developed taking into consideration the time and effort of providing new services. The platform is still being improved, but it already integrates a considerable number of audio and text processing modules, including: Automatic transcription, speech disfluency classification, emotion detection, dialog act recognition, age and gender classification, non-nativeness detection, hyper-articulation detection, dialog act recognition, and two external modules for feature extraction and DTMF detection. This paper describes the SPA architecture, presents the already integrated modules, and provides a detailed description for the ones most recently integrated.
Enhanced CORILGA: Introducing the Automatic Phonetic Alignment Tool for Continuous Speech
Authors: Roberto Seara, Marta Martinez, Roc{\'\i}o Varela, Carmen Garc{\'\i}a Mateo, Elisa Fern Rei, ez, Xos{\'e} Luis Regueira
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), Sentence, speech-recognition, Speech Recognition

The {``}Corpus Oral Informatizado da Lingua Galega (CORILGA){''} project aims at building a corpus of oral language for Galician, primarily designed to study the linguistic variation and change. This project is currently under development and it is periodically enriched with new contributions. The long-term goal is that all the speech recordings will be enriched with phonetic, syllabic, morphosyntactic, lexical and sentence ELAN-complaint annotations. A way to speed up the process of annotation is to use automatic speech-recognition-based tools tailored to the application. Therefore, CORILGA repository has been enhanced with an automatic alignment tool, available to the administrator of the repository, that aligns speech with an orthographic transcription. In the event that no transcription, or just a partial one, were available, a speech recognizer for Galician is used to generate word and phonetic segmentations. These recognized outputs may contain errors that will have to be manually corrected by the administrator. For assisting this task, the tool also provides an ELAN tier with the confidence measure of each recognized word. In this paper, after the description of the main facts of the CORILGA corpus, the speech alignment and recognition tools are described. Both have been developed using the Kaldi toolkit.
A Corpus of Argument Networks: Using Graph Properties to Analyse Divisive Issues
Authors: Barbara Konat, John Lawrence, Joonsuk Park, Katarzyna Budzynska, Chris Reed
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5
Tasks: Argument Mining

Governments are increasingly utilising online platforms in order to engage with, and ascertain the opinions of, their citizens. Whilst policy makers could potentially benefit from such enormous feedback from society, they first face the challenge of making sense out of the large volumes of data produced. This creates a demand for tools and technologies which will enable governments to quickly and thoroughly digest the points being made and to respond accordingly. By determining the argumentative and dialogical structures contained within a debate, we are able to determine the issues which are divisive and those which attract agreement. This paper proposes a method of graph-based analytics which uses properties of graphs representing networks of arguments pro- {\&} con- in order to automatically analyse issues which divide citizens about new regulations. By future application of the most recent advances in argument mining, the results reported here will have a chance to scale up to enable sense-making of the vast amount of feedback received from citizens on directions that policy should take.
metaTED: a Corpus of Metadiscourse for Spoken Language
Authors: Rui Correia, Nuno Mamede, Jorge Baptista, Maxine Eskenazi
Date: 2016-05-01 00:00:00
Proceeding: LREC 2016 5

This paper describes metaTED ― a freely available corpus of metadiscursive acts in spoken language collected via crowdsourcing. Metadiscursive acts were annotated on a set of 180 randomly chosen TED talks in English, spanning over different speakers and topics. The taxonomy used for annotation is composed of 16 categories, adapted from Adel(2010). This adaptation takes into account both the material to annotate and the setting in which the annotation task is performed. The crowdsourcing setup is described, including considerations regarding training and quality control. The collected data is evaluated in terms of quantity of occurrences, inter-annotator agreement, and annotation related measures (such as average time on task and self-reported confidence). Results show different levels of agreement among metadiscourse acts (α ∈ [0.15; 0.49]). To further assess the collected material, a subset of the annotations was submitted to expert appreciation, who validated which of the marked occurrences truly correspond to instances of the metadiscursive act at hand. Similarly to what happened with the crowd, experts revealed different levels of agreement between categories (α ∈ [0.18; 0.72]). The paper concludes with a discussion on the applicability of metaTED with respect to each of the 16 categories of metadiscourse.