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In diesem Aufsatz wird einzelfallanalytisch der Frage nachgegangen, wie die Struktur einer Kirchenbesichtigung aussieht. Im theoretischen Rahmen, der die Kirchenbesichtigung als kulturelle Praktik konzeptualisiert, wird „Objektkonstitution“ als eine aktive Leistung des Kirchenbesichtigers in den Blick genommen. Bei den Aufnahmen zum Kirchenbesichtigungskorpus wurden die Besichtiger nicht nur bei ihrem Gang durch den Kirchenraum und der visuellen Wahrnehmung bestimmter Raumaspekte gefilmt. Sie wurden vielmehr darum gebeten, ihre visuelle Wahrnehmung durch begleitendes Sprechen auch zu kommentieren. Aufgezeichnet wurde das Besichtigungskorpus mit zwei Kameras: einer Actionkamera, die den Wahrnehmungsraum der Besichtiger dokumentiert, und einer Kontextkamera, die ihnen bei ihrem Weg durch den Raum folgt.
Dieses experimentelle Erhebungsdesign, bei dem exothetisches Sprechen bewusst als wissenschaftliche Erhebungsmethode eingesetzt wird, macht es möglich, das Besichtigungskonzept der Personen als dynamisches Zusammenspiel ihrer visuellen Wahrnehmung des Kirchenraums und ihrer wahrnehmungsbegleitenden Exothese zu rekonstruieren. Dass Objektkonstitution eine aktive Herstellung ist, durch die der Kirchenraum in den Relevanzen seines Betrachters teilweise neu entsteht, zeigt die Fallanalyse in exemplarischer Klarheit: Anton, der analysierte Besichtiger, der sich ausführlich mit zwei großen Gemälden beschäftigt, konstituiert diese de facto als „Bilderrahmen“, ohne überhaupt auf die dargestellten Szenen einzugehen.
Sound units play a pivotal role in cognitive models of auditory comprehension. The general consensus is that during perception listeners break down speech into auditory words and subsequently phones. Indeed, cognitive speech recognition is typically taken to be computationally intractable without phones. Here we present a computational model trained on 20 hours of conversational speech that recognizes word meanings within the range of human performance (model 25%, native speakers 20–44%), without making use of phone or word form representations. Our model also generates successfully predictions about the speed and accuracy of human auditory comprehension. At the heart of the model is a ‘wide’ yet sparse two-layer artificial neural network with some hundred thousand input units representing summaries of changes in acoustic frequency bands, and proxies for lexical meanings as output units. We believe that our model holds promise for resolving longstanding theoretical problems surrounding the notion of the phone in linguistic theory.
Multinomial processing tree (MPT) models are a class of measurement models that account for categorical data by assuming a finite number of underlying cognitive processes. Traditionally, data are aggregated across participants and analyzed under the assumption of independently and identically distributed observations. Hierarchical Bayesian extensions of MPT models explicitly account for participant heterogeneity by assuming that the individual parameters follow a continuous hierarchical distribution.We provide an accessible introduction to hierarchical MPT modeling and present the user-friendly and comprehensive R package TreeBUGS, which implements the two most important hierarchical MPT approaches for participant heterogeneity—the beta-MPT approach (Smith & Batchelder, Journal of Mathematical Psychology 54:167-183, 2010) and the latent-trait MPT approach (Klauer, Psychometrika 75:70-98, 2010). TreeBUGS reads standard MPT model files and obtains Markov-chain Monte Carlo samples that approximate the posterior distribution. The functionality and output are tailored to the specific needs of MPT modelers and provide tests for the homogeneity of items and participants, individual and group parameter estimates, fit statistics, and within- and between-subjects comparisons, as well as goodness-of-fit and summary plots. We also propose and implement novel statistical extensions to include continuous and discrete predictors (as either fixed or random effects) in the latent-trait MPT model.
Languages employ different strategies to transmit structural and grammatical information. While, for example, grammatical dependency relationships in sentences are mainly conveyed by the ordering of the words for languages like Mandarin Chinese, or Vietnamese, the word ordering is much less restricted for languages such as Inupiatun or Quechua, as these languages (also) use the internal structure of words (e.g. inflectional morphology) to mark grammatical relationships in a sentence. Based on a quantitative analysis of more than 1,500 unique translations of different books of the Bible in almost 1,200 different languages that are spoken as a native language by approximately 6 billion people (more than 80% of the world population), we present large-scale evidence for a statistical trade-off between the amount of information conveyed by the ordering of words and the amount of information conveyed by internal word structure: languages that rely more strongly on word order information tend to rely less on word structure information and vice versa. Or put differently, if less information is carried within the word, more information has to be spread among words in order to communicate successfully. In addition, we find that–despite differences in the way information is expressed–there is also evidence for a trade-off between different books of the biblical canon that recurs with little variation across languages: the more informative the word order of the book, the less informative its word structure and vice versa. We argue that this might suggest that, on the one hand, languages encode information in very different (but efficient) ways. On the other hand, content-related and stylistic features are statistically encoded in very similar ways.