1,925 research outputs found

    Face-to-face spatial orientation fine-tunes the brain for neurocognitive processing in conversation

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    We here demonstrate that face-to-face spatial orientation induces a special ‘social mode’ for neurocognitive processing during conversation, even in the absence of visibility. Participants conversed face-to-face, face-to-face but visually occluded, and back-to-back to tease apart effects caused by seeing visual communicative signals and by spatial orientation. Using dual-EEG, we found that 1) listeners’ brains engaged more strongly while conversing in face-to-face than back-to-back, irrespective of the visibility of communicative signals, 2) listeners attended to speech more strongly in a back-to-back compared to a face-to-face spatial orientation without visibility; visual signals further reduced the attention needed; 3) the brains of interlocutors were more in sync in a face-to-face compared to a back-to-back spatial orientation, even when they could not see each other; visual signals further enhanced this pattern. Communicating in face-to-face spatial orientation is thus sufficient to induce a special ‘social mode’ which fine-tunes the brain for neurocognitive processing in conversation

    Individual differences in working memory and semantic fluency predict younger and older adults' multimodal recipient design in an interactive spatial task

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    Aging appears to impair the ability to adapt speech and gestures based on knowledge shared with an addressee (common ground-based recipient design) in narrative settings. Here, we test whether this extends to spatial settings and is modulated by cognitive abilities. Younger and older adults gave instructions on how to assemble 3D- models from building blocks on six consecutive trials. We induced mutually shared knowledge by either showing speaker and addressee the model beforehand, or not. Additionally, shared knowledge accumulated across the trials. Younger and crucially also older adults provided recipient-designed utterances, indicated by a significant reduction in the number of words and of gestures when common ground was present. Additionally, we observed a reduction in semantic content and a shift in cross-modal distribution of information across trials. Rather than age, individual differences in verbal and visual working memory and semantic fluency predicted the extent of addressee-based adaptations. Thus, in spatial tasks, individual cognitive abilities modulate the inter- active language use of both younger and older adu

    Presence of Mycoplasma sp. in Lambs with Lung Lesions

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    Objectives: To test the impact of NPCoat administration on the prevalence of lung lesions in lambs

    Speeding up the detection of non-iconic and iconic gestures (SPUDNIG): A toolkit for the automatic detection of hand movements and gestures in video data

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    In human face-to-face communication, speech is frequently accompanied by visual signals, especially communicative hand gestures. Analyzing these visual signals requires detailed manual annotation of video data, which is often a labor-intensive and time-consuming process. To facilitate this process, we here present SPUDNIG (SPeeding Up the Detection of Non-iconic and Iconic Gestures), a tool to automatize the detection and annotation of hand movements in video data. We provide a detailed description of how SPUDNIG detects hand movement initiation and termination, as well as open-source code and a short tutorial on an easy-to-use graphical user interface (GUI) of our tool. We then provide a proof-of-principle and validation of our method by comparing SPUDNIG’s output to manual annotations of gestures by a human coder. While the tool does not entirely eliminate the need of a human coder (e.g., for false positives detection), our results demonstrate that SPUDNIG can detect both iconic and non-iconic gestures with very high accuracy, and could successfully detect all iconic gestures in our validation dataset. Importantly, SPUDNIG’s output can directly be imported into commonly used annotation tools such as ELAN and ANVIL. We therefore believe that SPUDNIG will be highly relevant for researchers studying multimodal communication due to its annotations significantly accelerating the analysis of large video corpora

    The Inverse Shapley Value Problem

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    For ff a weighted voting scheme used by nn voters to choose between two candidates, the nn \emph{Shapley-Shubik Indices} (or {\em Shapley values}) of ff provide a measure of how much control each voter can exert over the overall outcome of the vote. Shapley-Shubik indices were introduced by Lloyd Shapley and Martin Shubik in 1954 \cite{SS54} and are widely studied in social choice theory as a measure of the "influence" of voters. The \emph{Inverse Shapley Value Problem} is the problem of designing a weighted voting scheme which (approximately) achieves a desired input vector of values for the Shapley-Shubik indices. Despite much interest in this problem no provably correct and efficient algorithm was known prior to our work. We give the first efficient algorithm with provable performance guarantees for the Inverse Shapley Value Problem. For any constant \eps > 0 our algorithm runs in fixed poly(n)(n) time (the degree of the polynomial is independent of \eps) and has the following performance guarantee: given as input a vector of desired Shapley values, if any "reasonable" weighted voting scheme (roughly, one in which the threshold is not too skewed) approximately matches the desired vector of values to within some small error, then our algorithm explicitly outputs a weighted voting scheme that achieves this vector of Shapley values to within error \eps. If there is a "reasonable" voting scheme in which all voting weights are integers at most \poly(n) that approximately achieves the desired Shapley values, then our algorithm runs in time \poly(n) and outputs a weighted voting scheme that achieves the target vector of Shapley values to within error $\eps=n^{-1/8}.

    The predictive potential of hand gestures during conversation: An investigation of the timing of gestures in relation to speech

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    In face-to-face conversation, recipients might use the bodily movements of the speaker (e.g. gestures) to facilitate language processing. It has been suggested that one way through which this facilitation may happen is prediction. However, for this to be possible, gestures would need to precede speech, and it is unclear whether this is true during natural conversation. In a corpus of Dutch conversations, we annotated hand gestures that represent semantic information and occurred during questions, and the word(s) which corresponded most closely to the gesturally depicted meaning. Thus, we tested whether representational gestures temporally precede their lexical affiliates. Further, to see whether preceding gestures may indeed facilitate language processing, we asked whether the gesture-speech asynchrony predicts the response time to the question the gesture is part of. Gestures and their strokes (most meaningful movement component) indeed preceded the corresponding lexical information, thus demonstrating their predictive potential. However, while questions with gestures got faster responses than questions without, there was no evidence that questions with larger gesture-speech asynchronies get faster responses. These results suggest that gestures indeed have the potential to facilitate predictive language processing, but further analyses on larger datasets are needed to test for links between asynchrony and processing advantages

    Speakers exhibit a multimodal Lombard effect in noise

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    In everyday conversation, we are often challenged with communicating in non-ideal settings, such as in noise. Increased speech intensity and larger mouth movements are used to overcome noise in constrained settings (the Lombard effect). How we adapt to noise in face-to-face interaction, the natural environment of human language use, where manual gestures are ubiquitous, is currently unknown. We asked Dutch adults to wear headphones with varying levels of multi-talker babble while attempting to communicate action verbs to one another. Using quantitative motion capture and acoustic analyses, we found that (1) noise is associated with increased speech intensity and enhanced gesture kinematics and mouth movements, and (2) acoustic modulation only occurs when gestures are not present, while kinematic modulation occurs regardless of co-occurring speech. Thus, in face-to-face encounters the Lombard effect is not constrained to speech but is a multimodal phenomenon where the visual channel carries most of the communicative burden

    Embodied space-pitch associations are shaped by language

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    Height-pitch associations are claimed to be universal and independent of language, but this claim remains controversial. The present study sheds new light on this debate with a multimodal analysis of individual sound and melody descriptions obtained in an interactive communication paradigm with speakers of Dutch and Farsi. The findings reveal that, in contrast to Dutch speakers, Farsi speakers do not use a height-pitch metaphor consistently in speech. Both Dutch and Farsi speakers’ co-speech gestures did reveal a mapping of higher pitches to higher space and lower pitches to lower space, and this gesture space-pitch mapping tended to co-occur with corresponding spatial words (high-low). However, this mapping was much weaker in Farsi speakers than Dutch speakers. This suggests that cross-linguistic differences shape the conceptualization of pitch and further calls into question the universality of height-pitch associations
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