Articles

We present the Extended Paraphrase Typology (EPT) and the Extended Typology Paraphrase Corpus (ETPC). The EPT typology addresses several practical limitations of existing paraphrase typologies: it is the first typology that copes with the non-paraphrase pairs in the paraphrase identification corpora and distinguishes between contextual and habitual paraphrase types. ETPC …...

This paper accompanies the release of Opusparcus, a new paraphrase corpus for six European languages: German, English, Finnish, French, Russian, and Swedish. The corpus consists of paraphrases, that is, pairs of sentences in the same language that mean approximately the same thing. The paraphrases are extracted from the OpenSubtitles2016 corpus, …...

Tasks such as knowledge extraction, text simplification and summarization have in common the fact that from a text fragment a smaller (not necessarily contiguous) portion is obtained by discarding part of the context. This may cause the text fragment to acquire a new meaning, or even to become false. The …...

We describe the automated multi-language text normalization infrastructure that prepares textual data to train language models used in Google’s keyboards and speech recognition systems, across hundreds of language varieties. Training corpora are sourced from various types of data sets, and the text is then normalized using a sequence of hand-written …...

In this paper, we present Tilde MT, a custom machine translation (MT) platform that provides linguistic data storage (parallel, monolingual corpora, multilingual term collections), data cleaning and normalisation, statistical and neural machine translation system training and hosting functionality, as well as wide integration capabilities (a machine user API and popular …...

We describe a pre-existing rule-based homograph disambiguation system used for text-to-speech synthesis at Google, and compare it to a novel system which performs disambiguation using classifiers trained on a small amount of labeled data. An evaluation of these systems, using a new, freely available English data set, finds that hybrid …...

NLP and automatic text analysis necessarily involve the annotation of natural language texts. The Apache Unstructured Information Management applications (UIMA) framework is used in several projects, tools and resources, and has become a de facto standard in this area. Despite the multiple use of UIMA as a document-based schema, it …...

CLARIN is a European Research Infrastructure that has been established to support the accessibility of language resources and technologies to researchers from the Digital Humanities and Social Sciences. This paper presents CLARIN’s Key Resource Families, a new initiative within the infrastructure, the goal of which is to collect and present …...

In recent years word embedding/distributional semantic models evolved to become a fundamental component in many natural language processing (NLP) architectures due to their ability of capturing and quantifying semantic associations at scale. Word embedding models can be used to satisfy recurrent tasks in NLP such as lexical and semantic generalisation …...

The iLCM project pursues the development of an integrated research environment for the analysis of structured and unstructured data in a “Software as a Service” architecture (SaaS). The research environment addresses requirements for the quantitative evaluation of large amounts of qualitative data with text mining methods as well as requirements …...

e-magyar is a new toolset for the analysis of Hungarian texts. It was produced as a collaborative effort of the Hungarian language technology community integrating the best state-of-the-art tools, enhancing them where necessary, making them interoperable and releasing them with a clear license. It is a free, open, modular text …...

This paper presents a novel word granularity-aware annotation framework for Chinese. Anchored in current functionalist linguistics, this model rearranges the boundary of word segmentation and linguistic annotation, and gears toward a deeper understanding of lexical units and their behavior. The web-based annotation UI also supports flexible annotation tasks for various …...

The LAPPS-CLARIN project is creating a “trust network” between the Language Applications (LAPPS) Grid and the WebLicht work- flow engine hosted by the CLARIN-D Center in T¨ubingen. The project also includes integration of NLP services available from the LINDAT/CLARIN Center in Prague. The goal is to allow users on one …...

The current paper outlines the ELRC-SHARE repository, an infrastructure designed and developed in the framework of the European Language Resource Coordination action with the objective to host, document, manage and appropriately distribute language resources pertinent to machine translation, and specifically tailored to the needs of the eTranslation service of the …...

In this paper we motivate the need for introducing more elaborate and consistent metadata records for collections of (linguistic) data resources in the CLARIN context. For this purpose we designed and implemented a CMDI profile. We validated the profile in a first pilot in which we populated the profile for …...

A significant concern in processing natural language data is the often unclear legal status of the input and output data/resources. In this paper, we investigate this problem by discussing a typical activity in Natural Language Processing: the training of a machine learning model from an annotated corpus. We examine which …...

The legal culture in the European Union imposes almost unsurmountable hurdles to exploit copyright protected language data (in terms of intellectual property rights (IPRs) of media contents) and privacy protected medical health data (in terms of the notion of informational self-determination) as language resources for the NLP community. These juridical …...

Language disturbances can be a diagnostic marker for neurodegenerative diseases, such as Alzheimer’s disease, at earlier stages. Connected speech analysis provides a non-invasive and easy-to-assess measure for determining aspects of the severity of language impairment. In this paper we focus on the development of a new corpus consisting of audio …...

We introduce Arabic Data Science Toolkit (ADST), a framework for Arabic language feature extraction, designed for data scientists that may not be familiar with Arabic or natural language processing. The functions in the toolkit allow data scientists to extend their algorithms beyond lexical or statistical methods and leverage Arabic-specific linguistic …...

Modern research on emotion recognition often deals with time-continuously labelled spontaneous interactions. Such data is much closer to real world problems in contrast to utterance-level categorical labelling in acted emotion corpora that have widely been used to date. While working with time-continuous labelling, one usually uses context-aware models, such as …...