Publications

Abstract

We present an overview of several corpus studies we carried out into the frequencies of argument NP orderings in the midfield of subordinate and main clauses of German. Comparing the corpus frequencies with grammaticality ratings published by Keller’s (2000), we observe a “grammaticality–frequency gap”: Quite a few argument orderings with zero corpus frequency are nevertheless assigned medium–range grammaticality ratings. We propose an explanation in terms of a two-factor theory. First, we hypothesize that the grammatical induction component needs a sufficient number of exposures to a syntactic pattern to incorporate it into its repertoire of more or less stable rules of grammar. Moderately to highly frequent argument NP orderings are likely have attained this status, but not their zero-frequency counterparts. This is why the latter argument sequences cannot be produced by the grammatical encoder and are absent from the corpora. Secondly, we assumed that an extraneous (nonlinguistic) judgment process biases the ratings of moderately grammatical linear order patterns: Confronted with such structures, the informants produce their own “ideal delivery” variant of the to-be-rated target sentence and evaluate the similarity between the two versions. A high similarity score yielded by this judgment then exerts a positive bias on the grammaticality rating—a score that should not be mistaken for an authentic grammaticality rating. We conclude that, at least in the linearization domain studied here, the goal of gaining a clear view of the internal grammar of language users is best served by a combined strategy in which grammar rules are founded on structures that elicit moderate to high grammaticality ratings and attain at least moderate usage frequencies.

Abstract

[Seven one-page psycholinguistic sketches]

Abstract

The ”download first, then process paradigm” is still the predominant working method amongst the research community. The web-based paradigm, however, offers many advantages from a tool development and data management perspective as they allow a quick adaptation to changing research environments. Moreover, new ways of combining tools and data are increasingly becoming available and will eventually enable a true web-based workflow approach, thus challenging the ”download first, then process” paradigm. The necessary infrastructure for managing, exploring and enriching language resources via the Web will need to be delivered by projects like CLARIN and DARIAH

Abstract

In this paper, we describe a unifying approach to tackle data heterogeneity issues for lexica and related resources. We present LEXUS, our software that implements the Lexical Markup Framework (LMF) to uniformly describe and manage lexica of different structures. LEXUS also makes use of a central Data Category Registry (DCR) to address terminological issues with regard to linguistic concepts as well as the handling of working and object languages. Finally, we report on ViCoS, a LEXUS extension, providing support for the definition of arbitrary semantic relations between lexical entries or parts thereof.

Abstract

To achieve true interoperability for valuable linguistic resources different levels of variation need to be addressed. ISO Technical Committee 37, Terminology and other language and content resources, is developing a Data Category Registry. This registry will provide a reusable set of data categories. A new implementation, dubbed ISOcat, of the registry is currently under construction. This paper shortly describes the new data model for data categories that will be introduced in this implementation. It goes on with a sketch of the standardization process. Completed data categories can be reused by the community. This is done by either making a selection of data categories using the ISOcat web interface, or by other tools which interact with the ISOcat system using one of its various Application Programming Interfaces. Linguistic resources that use data categories from the registry should include persistent references, e.g. in the metadata or schemata of the resource, which point back to their origin. These data category references can then be used to determine if two or more resources share common semantics, thus providing a level of interoperability close to the source data and a promising layer for semantic alignment on higher levels

Abstract

Language documentation involves linguistic analysis of the collected material, which is typically done manually. Automatic methods for language processing usually require large corpora. The method presented in this paper uses techniques from bioinformatics and contextual information to morphologically analyze raw text corpora. This paper presents initial results of the method when applied on a small Kilivila corpus.

Abstract

This task investigates the expression of “enter” and “exit” events, and is a supplement to the Motion Elicitation task (https://doi.org/10.17617/2.3003391). Consultants are asked to describe a series of animated clips where a man moves into or out of a house. The clips focus on contrasts to do with perspective (e.g., whether the man appears to move away or towards the viewer) and transitional movement (e.g., whether the man walks or “teleports” into his new location).

Abstract

The previous literature has suggested that the hand movement in co-speech gestures and signs consists of a series of phases with qualitatively different dynamic characteristics. In this paper, we propose a syntagmatic rule system for movement phases that applies to both co-speech gestures and signs. Descriptive criteria for the rule system were developed for the analysis video-recorded continuous production of signs and gesture. It involves segmenting a stream of body movement into phases and identifying different phase types. Two human coders used the criteria to analyze signs and cospeech gestures that are produced in natural discourse. It was found that the criteria yielded good inter-coder reliability. These criteria can be used for the technology of automatic recognition of signs and co-speech gestures in order to segment continuous production and identify the potentially meaningbearing phase.

Abstract

Do our hands 'speak the same language' across cultures? Gesture is the silent partner of spoken languages in face-to-face interaction, but we still have a lot to learn about gesture practices in different speech communities. The primary purpose of this task is to collect data in naturalistic settings that can be used to investigate the linguistic and cultural relativity of gesture performance, especially spatially indicative gestures. It involves video-recording pairs of speakers in both free conversation and more structured communication tasks (e.g., describing film plots).

Please note: the stimuli mentioned in this entry are available elsewhere: 'The Pear Story', a short film made at the University of California at Berkeley; "Frog, where are you?" from the original Mayer (1969) book, as published in the Appendix of Berman & Slobin (1994).

Abstract

This chapter explores the expression of placement (or Goal-oriented) and removal (or Source-oriented) events by speakers of Polish (a West Slavic language). Its aim is to investigate the hypothesis known as ‘Source/Goal asymmetry’ according to which languages tend to favor the expression of Goals (e.g., into, onto) and to encode them more systematically and in a more fine-grained way than Sources (e.g., from, out of). The study provides both evidence and counter-evidence for Source/Goal asymmetry. On the one hand, it shows that Polish speakers use a greater variety of verbs to convey Manner and/or mode of manipulation in the expression of placement, encoding such events in a more fine-grained manner than removal events. The expression of placement is also characterized by a greater variety of verb prefixes conveying Path and prepositional phrases (including prepositions and case markers) conveying Ground. On the other hand, the study reveals that Polish speakers attend to Sources as often as to Goals, revealing no evidence for an attentional bias toward the endpoints of events.

Abstract

Words can be distinguished by segmental differences or by suprasegmental differences or both. Studies from English suggest that suprasegmentals play little role in human spoken-word recognition; English stress, however, is nearly always unambiguously coded in segmental structure (vowel quality); this relationship is less close in Dutch. The present study directly compared the effects of segmental and suprasegmental mispronunciation on word recognition in Dutch. There was a strong effect of suprasegmental mispronunciation, suggesting that Dutch listeners do exploit suprasegmental information in word recognition. Previous findings indicating the effects of mis-stressing for Dutch differ with stress position were replicated only when segmental change was involved, suggesting that this is an effect of segmental rather than suprasegmental processing.

Abstract

Citations play a crucial role in the scientific discourse, in information retrieval, and in bibliometrics. Many initiatives are currently promoting the idea of having free and open citation data. Creation of citation data, however, is not part of the cataloging workflow in libraries nowadays.
In this paper, we present our project Linked Open Citation Database, in which we design distributed processes and a system infrastructure based on linked data technology. The goal is to show that efficiently cataloging citations in libraries using a semi-automatic approach is possible. We specifically describe the current state of the workflow and its implementation. We show that we could significantly improve the automatic reference extraction that is crucial for the subsequent data curation. We further give insights on the curation and linking process and provide evaluation results that not only direct the further development of the project, but also allow us to discuss its overall feasibility.

Abstract

It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.

Abstract

In different fields of the humanities annotations of multimodal resources are a necessary component of the research workflow. Examples include linguistics, psychology, anthropology, etc. However, creation of those annotations is a very laborious task, which can take 50 to 100 times the length of the annotated media, or more. This can be significantly improved by applying innovative audio and video processing algorithms, which analyze the recordings and provide automated annotations. This is the aim of the AVATecH project, which is a collaboration of the Max Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS. In this paper we present a set of results of automated annotation together with an evaluation of their quality.

Abstract

Digital processing of medical images has helped physicians and patients during past years by allowing examination and diagnosis on a very precise level. Nowadays possibly the biggest deal of support it can offer for modern healthcare is the use of high performance computing architectures to treat the huge amounts of data that can be collected by modern acquisition devices. This paper presents a parallel processing implementation of an image segmentation algorithm that operates on a computer cluster equipped with 10 processing units. Thanks to well-organized distribution of the workload we manage to significantly shorten the execution time of the developed algorithm and reach a performance gain very close to linear.

Abstract

Annotations of media recordings are the grounds for linguistic research. Since creating those annotations is a very laborious task, reaching 100 times longer than the length of the annotated media, innovative audio and video processing algorithms are needed, in order to improve the efficiency and quality of annotation process. The AVATecH project, started by the Max-Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS, aims at significantly speeding up the process of creating annotations of audio-visual data for humanities research. In order for this to be achieved a range of state-of-the-art audio and video pattern recognition algorithms have been developed and integrated into widely used ELAN annotation tool. To address the problem of heterogeneous annotation tasks and recordings we provide modular components extended by adaptation and feedback mechanisms to achieve competitive annotation quality within significantly less annotation time.

Abstract

Evolution and changes of all modern languages is a well-known fact. However, recently it is reaching dynamics never seen before, which results in loss of the vast amount of information encoded in every language. In order to preserve such heritage, properly annotated recordings of world languages are necessary. Since creating those annotations is a very laborious task, reaching times 100 longer than the length of the annotated media, innovative video processing algorithms are needed, in order to improve the efficiency and quality of annotation process.

Abstract

Introduction Human spoken communication is multimodal, i.e. it encompasses both speech and gesture. Acoustic properties of voice, body movements, facial expression, etc. are an inherent and meaningful part of spoken interaction; they can provide attitudinal, grammatical and semantic information. In the recent years interest in audio-visual corpora has been rising rapidly as they enable investigation of different communicative modalities and provide more holistic view on communication (Kipp et al. 2009). Moreover, for some languages such corpora are the only available resource, as is the case for endangered languages for which no written resources exist.

Abstract

Processing medical data has always been an interesting field that has shown the need for effective image segmentation methods. Modern medical image segmentation solutions are focused on 3D image volumes, which originate at advanced acquisition devices. Operating on such data in a 3D envi- ronment is essential in order to take the full advantage of the available information. In this paper we present an extended version of our 3D image segmentation and reconstruction model that belongs to the family of Deformable Models and is capable of processing large image volumes in competitive times and in fully 3D environment, offering a big level of automation of the process and a high precision of results. It is also capable of handling topology changes and offers a very good scalability on multi-processing unit architectures. We present a description of the model and show its capabilities in the field of medical image processing.

Abstract

In this paper we describe audio and video processing algorithms that are developed in the scope of AVATecH project. The purpose of these algorithms is to shorten the time taken by manual annotation of audio and video recordings by extracting features from media files and creating semi-automated annotations. We show that the use of such supporting algorithms can shorten the annotation time to 30-50% of the time necessary to perform a fully manual annotation of the same kind.

Abstract

It has been hypothesised that human reasoning has a non-linguistic foundation, but is nevertheless influenced by the formal means available in a language. For example, Western logic is transparently related to European sentential connectives (e.g., and, if … then, or, not), some of which cannot be unambiguously expressed in other languages. The questionnaire explores reasoning tools and practices through investigating translation equivalents of English sentential connectives and collecting examples of “reasoned arguments”.

Abstract

Reproduced with permission of Blackwell Publishing from: Levinson, S. C. (2004) 'Deixis'. In: Horn, L.R. and Ward, G. (Eds.) The Handbook of Pragmatics. Oxford: Blackwell Publishing, pp. 100-121

Abstract

Reprinted with permission of The MIT Press from Levinson (2000) Presumptive meanings: The theory of generalized conversational implicature, pp. 112-118, 116-167, 170-173, 177-180. MIT Press

Abstract

This paper describes the linguistic treatment of placement events in the Rossel Island (Papua New Guinea) language Yélî Dnye. Yélî Dnye is unusual in treating PUT and TAKE events symmetrically with a remarkable consistency. In what follows, we first provide a brief background for the language, then describe the six core PUT/TAKE verbs that were drawn upon by Yélî Dnye speakers to describe the great majority of the PUT/TAKE stimuli clips, along with some of their grammatical properties. In Section 5 we describe alternative verbs usable in particular circumstances and give an indication of the basis for variability in responses across speakers. Section 6 presents some reasons why the Yélî verb pattern for expressing PUT and TAKE events is of broad interest.

Abstract

Yélî Dnye has two discernable dedicated constructions for reciprocal marking. The first and main construction uses a dedicated reciprocal pronoun numo, somewhat like English each other. We can recognise two subconstructions. First, the ‘numo-construction’, where the reciprocal pronoun is a patient of the verb, and where the invariant pronoun numo is obligatorily incorporated, triggering intransitivisation (e.g. A-NPs become absolutive). This subconstruction has complexities, for example in the punctual aspect only, the verb is inflected like a transitive, but with enclitics mismatching actual person/number. In the second variant or subconstruction, the ‘noko-construction’, the same reciprocal pronoun (sometimes case-marked as noko) occurs but now in oblique positions with either transitive or intransitive verbs. The reciprocal element here has some peculiar binding properties. Finally, the second independent construction is a dedicated periphrastic (or woni…woni) construction, glossing ‘the one did X to the other, and the other did X to the one’. It is one of the rare cross-serial dependencies that show that natural languages cannot be modelled by context-free phrase-structure grammars. Finally, the usage of these two distinct constructions is discussed.

Abstract

Reprint from Stephen C. Levinson, ‘Three Levels of Meaning’, in Frank Palmer (ed.), Grammar and Meaning: Essays in Honor of Sir John Lyons (Cambridge University Press, 1995), pp. 90–115

Abstract

This entry contains: 1. An invitation to think about to what extent the grammar of space and time share lexical and morphosyntactic resources − the suggestions here are only prompts, since it would take a long questionnaire to fully explore this; 2. A suggestion about how to collect gestural data that might show us to what extent the spatial and temporal domains, have a psychological continuity. This is really the goal − but you need to do the linguistic work first or in addition. The goal of this task is to explore the extent to which time is conceptualised on a spatial basis.

Abstract

Changing Prospects for Universals in Pragmatics
The term PRAGMATICS has come to denote the study of general principles of language use. It is usually understood to contrast with SEMANTICS, the study of encoded meaning, and also, by some authors, to contrast with SOCIOLINGUISTICS
and the ethnography of speaking, which are more concerned with local sociocultural practices. Given that pragmaticists come from disciplines as varied as philosophy, sociology,
linguistics, communication studies, psychology, and anthropology, it is not surprising that definitions of pragmatics vary. Nevertheless, most authors agree on a list of topics
that come under the rubric, including DEIXIS, PRESUPPOSITION,
implicature (see CONVERSATIONAL IMPLICATURE), SPEECH-ACTS, and conversational organization (see CONVERSATIONAL ANALYSIS). Here, we can use this extensional definition as a starting point (Levinson 1988; Huang 2007).

Abstract

We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.

Abstract

Young children demonstrate the ability to make inferences about the preferences of other agents based on their choices. However, there exists no overarching account of what children are doing when they learn about preferences or how they use that knowledge. We use a rational model of preference learning, drawing on ideas from economics and computer science, to explain the behavior of children in several recent experiments. Specifically, we show how a simple econometric model can be extended to capture two- to four-year-olds’ use of statistical information in inferring preferences, and their generalization of these preferences.

Abstract

We examined how communicators can switch between speaker and listener role with such accurate timing. During conversations, the majority of role transitions happens with a gap or overlap of only a few hundred milliseconds. This suggests that listeners can predict when the turn of the current speaker is going to end. Our hypothesis is that listeners know when a turn ends because they know how it ends. Anticipating the last words of a turn can help the next speaker in predicting when the turn will end, and also in anticipating the content of the turn, so that an appropriate response can be prepared in advance. We used the stimuli material of an earlier experiment (De Ruiter, Mitterer & Enfield, 2006), in which subjects were listening to turns from natural conversations and had to press a button exactly when the turn they were listening to ended. In the present experiment, we investigated if the subjects can complete those turns when only an initial fragment of the turn is presented to them. We found that the subjects made better predictions about the last words of those turns that had more accurate responses in the earlier button press experiment.

Abstract

For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.

Abstract

This Field Manual entry has been superceded by the 2009 version:
https://doi.org/10.17617/2.883570

Abstract

In this task we aim to find what the best exemplars or “focal colours” of each basic colour term is in our field languages. This is an important part of the evidence we need in order to understand the colour data collected using 'The Language of Vision I: Colour'. This task consists of an experiment where participants pick out the best exemplar for the colour terms in their language. The goal is to establish language specific focal colours.

Abstract

What is the relationship between the language we speak and the way we think? Researchers working at the interface of language and cognition hope to understand the complex interplay between linguistic structures and the way the mind works. This is thorny territory in anthropology and its closely allied disciplines, such as linguistics and psychology.

Abstract

Scholars disagree about the extent to which language can tell us
about conceptualisation of the world. Some believe that language
is a direct window onto concepts: Having a word ‘‘bird’’, ‘‘table’’ or
‘‘sour’’ presupposes the corresponding underlying concept, BIRD,
TABLE, SOUR. Others disagree. Words are thought to be uninformative,
or worse, misleading about our underlying conceptual representations;
after all, our mental worlds are full of ideas that we
struggle to express in language. How could this be so, argue sceptics,
if language were a direct window on our inner life? In this presentation,
I consider what language can tell us about the
conceptualisation of taste. By considering linguistic data from
twenty unrelated cultures – varying in subsistence mode (huntergatherer
to industrial), ecological zone (rainforest jungle to desert),
dwelling type (rural and urban), and so forth – I argue any single language is, indeed, impoverished about what it can reveal about
taste. But recurrent lexicalisation patterns across languages can
provide valuable insights about human taste experience. Moreover,
language patterning is part of the data that a good theory of taste
perception has to be answerable for. Taste researchers, therefore,
cannot ignore the crosslinguistic facts.