Publications

Abstract

In this paper, we describe the core pillars of a large archive oflanguage material recorded worldwide partly about languages that are highly endangered. The bases for the documentation of these languages are audio/video recordings which are then annotated at several linguistic layers. The digital age completely changed the requirements of long-term preservation and it is discussed how the archive met these new challenges. An extensive solution for data replication has been worked out to guarantee bit-stream preservation. Due to an immediate conversion of the incoming data to standards -based formats and checks at upload time lifecycle management of all 50 Terabyte of data is widely simplified. A suitable metadata framework not only allowing users to describe and discover resources, but also allowing them to organize their resources is enabling the management of this amount of resources very efficiently. Finally, it is the Language Archiving Technology software suite which allows users to create, manipulate, access and enrich all archived resources given that they have access permissions.

Abstract

Currently, research infrastructures are being designed and established in manydisciplines since they all suffer from an enormous fragmentation of theirresources and tools. In the domain of language resources and tools the CLARINinitiative has been funded since 2008 to overcome many of the integration andinteroperability hurdles. CLARIN can build on knowledge and work from manyprojects that were carried out during the last years and wants to build stableand robust services that can be used by researchers. Here service centres willplay an important role that have the potential of being persistent and thatadhere to criteria as they have been established by CLARIN. In the last year ofthe so-called preparatory phase these centres are currently developing four usecases that can demonstrate how the various pillars CLARIN has been working oncan be integrated. All four use cases fulfil the criteria of beingcross-national.

Abstract

Language users process utterances by segmenting them into many cognitive units, which vary in their sizes and linguistic levels. Although we can do such unitization/segmentation easily, its cognitive mechanism is still not clear. This paper proposes an unsupervised model, Less-is-Better (LiB), to simulate the human cognitive process with respect to language unitization/segmentation. LiB follows the principle of least effort and aims to build a lexicon which minimizes the number of unit tokens (alleviating the effort of analysis) and number of unit types (alleviating the effort of storage) at the same time on any given corpus. LiB’s workflow is inspired by empirical cognitive phenomena. The design makes the mechanism of LiB cognitively plausible and the computational requirement light-weight. The lexicon generated by LiB performs the best among different types of lexicons (e.g. ground-truth words) both from an information-theoretical view and a cognitive view, which suggests that the LiB lexicon may be a plausible proxy of the mental lexicon.

Abstract

Although sign language-using communities exist in all areas of the world, few sign languages have been documented in detail. Sign languages occur in a variety of sociocultural contexts, ranging from sign languages used in closed village communities to officially recognized national sign languages. They may be grouped into language families on historical grounds or may participate in various language contact situations. Systematic cross-linguistic comparison reveals both significant structural similarities and important typological differences between sign languages. Focusing on information from non-Western countries, this article provides an overview of the sign languages of the world.

Abstract

To acquire the meaning of a verb, language learners not only need to find the correct mapping between a specific verb and an action or event in the world, but also infer the underlying relational meaning that the verb encodes. Most verb naming instances in naturalistic contexts are highly ambiguous as many possible actions can be embedded in the same scenario and many possible verbs can be used to describe those actions. To understand whether learners can find the correct verb meaning from referentially ambiguous learning situations, we conducted three experiments using the Human Simulation Paradigm with adult learners. Our results suggest that although finding the right verb meaning from one learning instance is hard, there is a statistical solution to this problem. When provided with multiple verb learning instances all referring to the same verb, learners are able to aggregate information across situations and gradually converge to the correct semantic space. Even in cases where they may not guess the exact target verb, they can still discover the right meaning by guessing a similar verb that is semantically close to the ground truth.

Abstract

In informal interaction, speakers rarely thank a person who has complied with a request. Examining data from British English, German, Italian, Polish, and Telugu, we ask when speakers do thank after compliance. The results show that thanking treats the other’s assistance as going beyond what could be taken for granted in the circumstances. Coupled with the rareness of thanking after requests, this suggests that cooperation is to a great extent governed by expectations of helpfulness, which can be long-standing, or built over the course of a particular interaction. The higher frequency of thanking in some languages (such as English or Italian) suggests that cultures differ in the importance they place on recognizing the other’s agency in doing as requested.

Abstract

The amount of research data in the Humanities is increasing at fastspeed. Metadata helps describing and making accessible this data tointerested researchers within and across institutions. While metadatainteroperability is an issue that is being recognised and addressed,the systematic and user-driven provision of annotations and thelinking together of resources into new organisational layers havereceived much less attention. This paper gives an overview of ourevolving technological eScience environment to support suchfunctionality. It describes two tools, ADDIT and ViCoS, which enableresearchers, rather than archive managers, to organise and reorganiseresearch data to fit their particular needs. The two tools, which areembedded into our institute's existing software landscape, are aninitial step towards an eScience environment that gives our scientistseasy access to (multimodal) research data of their interest, andempowers them to structure, enrich, link together, and share such dataas they wish.