linguistic labels
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Author(s):  
Mark Pallen ◽  
Nabil-Fareed Alikhan

Thousands of new bacterial and archaeal species and higher-level taxa are discovered each year through the analysis of genomes and metagenomes. The Genome Taxonomy Database (GTDB) provides hierarchical sequence-based descriptions and classifications for new and as-yet-unnamed taxa. However, bacterial nomenclature, as currently configured, cannot keep up with the need for new well-formed names. Instead, microbiologists have been forced to use hard-to-remember alphanumeric placeholder labels. Here, we exploit an approach to the generation of well-formed arbitrary Latinate names at a scale sufficient to name tens of thousands of unnamed taxa within GTDB. These newly created names represent an important resource for the microbiology community, facilitating communication between bioinformaticians, microbiologists and taxonomists, while populating the emerging landscape of microbial taxonomic and functional discovery with accessible and memorable linguistic labels.


2021 ◽  
Author(s):  
Najlaa Maaroof ◽  
Antonio Moreno ◽  
Mohammed Jabreel ◽  
Aida Valls

Despite the broad adoption of Machine Learning models in many domains, they remain mostly black boxes. There is a pressing need to ensure Machine Learning models that are interpretable, so that designers and users can understand the reasons behind their predictions. In this work, we propose a new method called C-LORE-F to explain the decisions of fuzzy-based black box models. This new method uses some contextual information about the attributes as well as the knowledge of the fuzzy sets associated to the linguistic labels of the fuzzy attributes to provide actionable explanations. The experimental results on three datasets reveal the effectiveness of C-LORE-F when compared with the most relevant related works.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ksenija Slivac ◽  
Alexis Hervais-Adelman ◽  
Peter Hagoort ◽  
Monique Flecken

AbstractLinguistic labels exert a particularly strong top-down influence on perception. The potency of this influence has been ascribed to their ability to evoke category-diagnostic features of concepts. In doing this, they facilitate the formation of a perceptual template concordant with those features, effectively biasing perceptual activation towards the labelled category. In this study, we employ a cueing paradigm with moving, point-light stimuli across three experiments, in order to examine how the number of biological motion features (form and kinematics) encoded in lexical cues modulates the efficacy of lexical top-down influence on perception. We find that the magnitude of lexical influence on biological motion perception rises as a function of the number of biological motion-relevant features carried by both cue and target. When lexical cues encode multiple biological motion features, this influence is robust enough to mislead participants into reporting erroneous percepts, even when a masking level yielding high performance is used.


2021 ◽  
Author(s):  
Victoria Yantseva

The goal of this work is to study the social construction of migrant categories and immigration discourse on Swedish Facebook in the last decade. I combine the insights from computational linguistics and distributional semantics approach with those from classical sociological theories in order to explore a corpus of more than 1M Facebook posts. This allows to compare the intended meanings of various linguistic labels denoting voluntary versus forced character of migration, as well as to distinguish the most salient themes that constitute the Facebook discourse. The study concludes that, although Facebook seems to have the highest potential in the promotion of tolerance and support for migrants, its audience is nevertheless active in the discursive discrimination of those identified as "refugees" or "immigrants". The results of the study are then related to the technological design of new media and the overall social and political climate surrounding the Swedish immigration agenda.


2021 ◽  
pp. 174702182110141
Author(s):  
Giulia Calignano ◽  
Eloisa Valenza ◽  
Francesco Vespignani ◽  
Sofia Russo ◽  
Simone Sulpizio

Do novel linguistic labels have privileged access to attentional resources compared to non-linguistic labels? This study explores this possibility through two experiments with a training and an attentional overlap task. Experiment 1 investigates how novel label and object-only stimuli influence resource allocation and disengagement of visual attention. Experiment 2 tests the impact of linguistic information on visual attention by comparing novel tones and labels. Because disengagement of attention is affected both by the saliency of the perceptual stimulus and by the degree of familiarity with the stimulus to be disengaged from, we compared pupil size variations and saccade latency under different test conditions: (i) consistent with (i.e., identical to) the training; (ii) inconsistent with the training (i.e., with an altered feature), and (iii) deprived of one feature only in Experiment 1. Experiment 1 indicated a general consistency advantage (and deprived disadvantage) driven by linguistic label-object pairs compared to object-only stimuli. Experiment 2 revealed that tone-object pairs led to higher pupil dilation and longer saccade latency than linguistic label-object pairs. Our results suggest that novel linguistic labels preferentially impact the early orienting of attention.


2021 ◽  
Author(s):  
Agata Dymarska ◽  
Louise Connell ◽  
Briony Banks

[Draft version, 04/03/21. This paper has not been peer reviewed. Please do not copy or cite without author's permission] The linguistic-simulation approach to cognition predicts that language can enable more efficient conceptual processing than purely sensorimotor-affective simulations of concepts. We tested the implications of this approach in working memory, where use of linguistic labels (i.e., words and phrases) could enable more efficient representation of concepts in a limited-capacity store than representation via full sensorimotor simulation; a proposal called linguistic bootstrapping. In four pre-registered experiments using a nonverbal recognition memory paradigm, we asked participants to remember sequences of real-world objects, and used articulatory suppression to selectively block implicit activation of linguistic labels, which we predicted would impair object memory performance. We found that blocking access to language at encoding impaired memory accuracy, though not latency, and that this impairment was not simply dual-task load. Results show that a sequence of up to 10 contextually-situated object concepts can be held in working memory when language is blocked, but this capacity increases to 12 objects when language is available. The findings support the linguistic bootstrapping hypothesis that working memory for familiar object concepts normally relies on language, and that implicitly-retrieved object labels, used as linguistic placeholders, enhance the achievable capacity of working memory beyond what sensorimotor information alone can accomplish.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Joshua R. de Leeuw ◽  
Jan Andrews ◽  
Lori Barney ◽  
Margaret Bigler ◽  
Polyphony J. Bruna ◽  
...  

We report a replication of Boutonnet and Lupyan’s (2015) study of the effects of linguistic labelling on perceptual performance. In addition to a response time advantage of linguistic labels over non-linguistic auditory cues in judging visual objects, Boutonnet and Lupyan found that the two types of cues produced different patterns in the early perceptual ERP components P1 and P2 but not the later, semantics-relevant N4. This study thus adds an important piece of evidence supporting the claim of genuine top-down effects on perception. Given the controversy over this claim and the need for replication of key findings, we attempted to replicate Boutonnet and Lupyan (2015). We replicated their behavioral findings that response times to indicate whether an auditory cue matches a visual image of an object were faster for match than mismatch trials and faster for linguistic than non-linguistic cues. We did not replicate the main ERP effects supporting a positive effect of linguistic labels on the early perceptual ERP components P1 and P2, though we did find a congruence by cue type interaction effect on those components. Unlike Boutonnet and Lupyan, we found a main effect of cue type on the N4 in which non-linguistic cues produced more negative amplitudes. Exploratory analyses of the unpredicted N4 effect suggest that the response time advantage of linguistic labels occurred during semantic rather than early visual processing. This experiment was pre-registered at https://osf.io/cq8g4/ and conducted as part of an undergraduate cognitive science research methods class at Vassar College.


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