Search

This study investigates the effects of prior intentions and intentions in action during the initial stage of a process of design in search of correlations between these cognitive processes and the quality of the design outcomes. We found that the quality of the outcomes was not influenced by sketching. Nevertheless, most of the participants said that they preferred sketching, and their verbal reports can be seen as indicative of the formation of prior intentions. Therefore, we argue that prior intentions have an important role even within a process of pure material engagement. This has important implications for understanding the active role of human agency and our capacity to form prior intentions with pragmatic effects in the world. [ABSTRACT FROM AUTHOR]

Students with hearing loss (HL) often fall behind hearing peers in complex language tasks such as narrative writing. This study explored the effects of school grade, gender, cognitive and linguistic predisposition and audiological factors on narrative text quality in this target group. Eleven students with HL in Grades 5–6 and 7–8 (age 12–15) who took part in a writing intervention wrote four narrative texts over six months. A trained panel rated text quality. The effects of the students' working memory capacity, language comprehension, reading comprehension, school grade and gender and the intervention were analyzed as a mixed-effects regression model. Audiological factors were considered separately. The analysis showed that throughout the period, texts written by female students in Grade 7–8 received the highest text quality ratings, while those written by male students in Grade 7–8 received the lowest ratings. There was no effect of the intervention, or of the linguistic and cognitive measures. The students with the lowest text quality ratings received amplification later than those with high ratings, but HL severity was not associated with text quality. Hearing loss severity was not a decisive factor in narrative text quality. The intervention which the students took part in is potentially effective, with some adaptation to the special needs of students with HL. The strong gender effects are discussed. [ABSTRACT FROM AUTHOR]

In this study, we investigated the prosody of domestic cat meows produced in different contexts. Prosodic cues – i.e., variation in intonation, duration, voice quality and fundamental frequency – in humans as well as in nonhuman animals carry information about idiosyncratic traits of the signaller, including sex, age, and physical and mental state. The duration, fundamental frequency (F0) and intonation in a sample of 969 meows recorded in seven different contexts (i.e., cuddle , door , food , greeting , lifting , play , cat carrier) were analysed using linear mixed effects regression and generalized additive models. In this, we controlled for cat age and sex, as meows produced by old cats had lower mean F0 than those produced by young cats, and female cats produced meows with higher mean F0 than male cats. We found significant effects of context on duration and mean F0, but not on F0 range. Furthermore, the results showed that the intonation of meows produced by cats in a cat carrier displayed a falling pattern, while that of meows produced in cuddle and door contexts was relatively level, and that of meows produced in the other contexts consisted of combinations of rising and falling. The average slope of meows produced in cat carrier and play contexts was negative, while that of meows produced in the other contexts was positive. We argue that this prosodic variation reflects the cats' mental or emotional state, because of valence and arousal differences associated with the various contexts that were included in the study. Further studies will need to confirm this. In addition, we also plan additional analyses of spectral and voice quality parameters in meows and other cat vocalisation types. • The vocal prosody of domestic cat meows varies with the physical context. • Domestic cat meows vary in duration, mean fundamental frequency (F0) and intonation. • Young and female cat meows have higher F0 than old and male cat meows. • Meows in cat carriers have falling intonation, but is more varied in other contexts. [ABSTRACT FROM AUTHOR]

• We study feature replay with compressed exemplars for online continual learning. • We show the importance of replaying features from intermediate layers of the network. • We propose ACAE-REMIND enabling better feature compression based on auto-encoders. • The method achieves good performance in several online continual learning settings. • Our online method even surpasses several offline continual learning methods. Online continual learning aims to learn from a non-IID stream of data from a number of different tasks, where the learner is only allowed to consider data once. Methods are typically allowed to use a limited buffer to store some of the images in the stream. Recently, it was found that feature replay, where an intermediate layer representation of the image is stored (or generated) leads to superior results than image replay, while requiring less memory. Quantized exemplars can further reduce the memory usage. However, a drawback of these methods is that they use a fixed (or very intransigent) backbone network. This significantly limits the learning of representations that can discriminate between all tasks. To address this problem, we propose an auxiliary classifier auto-encoder (ACAE) module for feature replay at intermediate layers with high compression rates. The reduced memory footprint per image allows us to save more exemplars for replay. In our experiments, we conduct task-agnostic evaluation under online continual learning setting and get state-of-the-art performance on ImageNet-Subset, CIFAR100 and CIFAR10 dataset. [ABSTRACT FROM AUTHOR]

In the last few years, the traditional analysis of know as a factive verb has been lively debated by linguists and philosophers of language: several scholars have pointed out that know may be used non-factively in ordinary language. The aim of the present study is to expand this inquiry to other cognitive factive verbs than know , such as discover , realize , etc., and to investigate cross-linguistically the question of whether know and other cognitive factive verbs may occur in non-factive contexts, that is, in contexts where it is clear that the embedded proposition is false. Moreover, we investigate whether so-called evidential uses of cognitive factive verbs are acceptable across languages. We administered an online survey to native speakers of nine different languages (English, French, German, Greek, Italian, Portuguese, Serbian, Spanish, and Swedish), and we found considerable cross-linguistic variation in the acceptability of the use of know and other cognitive factive verbs in non-factive contexts. For Italian and English, we put forward the claim that non-factive uses of cognitive factives instantiate a case of polysemy resulting from a process of semantic change that moves along a three-step pattern: from a factive sense to a more general non-factive sense to a non-factive sense characterized by an evidential function. • Cognitive factive verbs are investigated cross-linguistically. • Know and other cognitive factive verbs are used non-factively in ordinary language. • Cognitive factive verbs may be used to fulfill an evidential strategy. • An Acceptability Judgment Task was submitted to native speakers of nine languages. • Evidential uses may be a step in a process of defactivization of factive verbs. [ABSTRACT FROM AUTHOR]

Would metaphors used in the context of psychotherapy by people who experience various forms of anxiety disorders differ from those used by people who experience stress? We investigated this question with the help of the Motivation & Sedimentation Model (MSM), a theory of meaning-making developed within the synthetic new discipline of cognitive semiotics. The analysis of a sample of ten transcripts of psychotherapy sessions concerning the topic of anxiety, and a comparable sample concerning stress, showed a significantly stronger proportion of conventionalized metaphors in the stress sample, and a marginally significant difference in the number of innovative metaphors in the anxiety sample. These results suggest that lived experience of an anxiety disorder or another form of maladaptive anxiety affects metaphorical meaning-making, and manifests itself in spontaneous metaphor use. Furthermore, as a result of the conceptual and the empirical investigations of the topic, we propose novel theoretical and operational definitions of the notion of metaphoricity. [ABSTRACT FROM AUTHOR]

Gender inflection for animated nouns in Italian presents challenges influenced by societal pressures and linguistic structure, especially in morphologically complex words like compounds. The study investigates gender inflection distribution in compounds with capo- compared to other nouns (i.e., occupations traditionally performed by women, by men, and the word capo in isolation), exploring the interplay of social, etymological and morphological factors. 192 native Italian speakers inflected masculine nouns to feminine forms after hearing the stimulus. Results reveal that respondents’ attitudes towards gender-fair language significantly determine the use of feminine, indicating a complex interplay between linguistic structures and social perceptions. Despite historical resistance, the word capa in isolation shows increasing acceptance, challenging entrenched norms. In compounds, capo- element’s gender inflection appears more resistant due to morphological complexity, with an interaction with number. This study advances our understanding of gender inflection, with implications for broader conversations about gender representation and language inclusivity. [ABSTRACT FROM AUTHOR]

• We show that saliency maps can be obtained as a byproduct of image classification. • Our method does not require any saliency ground truth. • We include an extensive study of the effect of center bias on the results. • We get competitive results even when comparing to methods that do use ground truth. Saliency is the perceptual capacity of our visual system to focus our attention (i.e. gaze) on relevant objects instead of the background. So far, computational methods for saliency estimation required the explicit generation of a saliency map, process which is usually achieved via eyetracking experiments on still images. This is a tedious process that needs to be repeated for each new dataset. In the current paper, we demonstrate that is possible to automatically generate saliency maps without ground-truth. In our approach, saliency maps are learned as a side effect of object recognition. Extensive experiments carried out on both real and synthetic datasets demonstrated that our approach is able to generate accurate saliency maps, achieving competitive results when compared with supervised methods. [ABSTRACT FROM AUTHOR]

Given the often enormous effort required to train GANs, both computationally as well as in dataset collection, the re-use of pretrained GANs largely increases the potential impact of generative models. Therefore, we propose a novel knowledge transfer method for generative models based on mining the knowledge that is most beneficial to a specific target domain, either from a single or multiple pretrained GANs. This is done using a miner network that identifies which part of the generative distribution of each pretrained GAN outputs samples closest to the target domain. Mining effectively steers GAN sampling towards suitable regions of the latent space, which facilitates the posterior finetuning and avoids pathologies of other methods, such as mode collapse and lack of flexibility. Furthermore, to prevent overfitting on small target domains, we introduce sparse subnetwork selection, that restricts the set of trainable neurons to those that are relevant for the target dataset. We perform comprehensive experiments on several challenging datasets using various GAN architectures (BigGAN, Progressive GAN, and StyleGAN) and show that the proposed method, called MineGAN, effectively transfers knowledge to domains with few target images, outperforming existing methods. In addition, MineGAN can successfully transfer knowledge from multiple pretrained GANs. MineGAN. [ABSTRACT FROM AUTHOR]

A match-action cut in feature films connects two shots of a single continuous movement. This type of editing often goes unnoticed and is arguably the most effective form of continuity editing. However, the literature offers little agreement on editing best practice and, by implication, on how our perceptual system deals with disjointed moving images. Studies have suggested that frames should overlap across the cut for the viewer to experience continuity, but also that leaving out frames is preferable, and even that viewers are unable to discriminate such detail. We conducted an experiment to investigate viewer preferences for match-action cuts, using type of cut as well as velocity of movement as predictors and number of overlapping/elliptical frames as the outcome variable. Thirty-nine participants determined the smoothest cut in eight film-clips in a within-subjects design. Surprisingly, we found that average viewer preferences were less than a single frame from a straight cut for all cut-types. We also found that velocity had a small but statistically significant effect on editing preferences. The preference for straight cuts found in the present study runs counter to the idea that perceived continuity across match-action cuts requires objective dis-continuity and suggests that the straight cut provides a simple rule of thumb for film editors. In addition, we interpret the conflicting results from previous studies together with our own findings based on a discrimination task of finding the optimal cut as indicating that human visual perception allows for a window of acceptable continuity cuts centered around the straight cut. [ABSTRACT FROM AUTHOR]

This study addresses the postulate of non-conventionality of pantomime, inherent in pantomimic scenarios of language origin. Since lack of semiotic conventions does not preclude micro-conventions resulting from cultural differences, pantomimes should be easier to interpret when the actor and recipient share the same culture than between two different cultures. In the study, Italian and Polish amateur "actors" re-enacted transitive events from a matrix of cartoon-like drawings. Randomly selected clips were matched by Polish and Italian participants to the corresponding drawings. We found no difference in the number of correct guesses when the actors and matchers were from the same versus from different cultures. We discuss this result in the context of the core assumptions of pantomimic scenarios of language origin. • Pantomimic scenarios of language origins assume that pantomime is robustly iconic and free from communicative conventions. • Lack of conventions does not preclude micro-conventions, thus pantomime should be more successful within cultures. • This was tested in a study with Italian and Polish participants. • Communicative success of pantomimes did not differ between same-culture and different-culture conditions. • Italian pantomimes were better guessed by both Italian and Polish participants. [ABSTRACT FROM AUTHOR]

Modern computer vision requires processing large amounts of data, both while training the model and/or during inference, once the model is deployed. Scenarios where images are captured and processed in physically separated locations are increasingly common (e.g. autonomous vehicles, cloud computing, smartphones). In addition, many devices suffer from limited resources to store or transmit data (e.g. storage space, channel capacity). In these scenarios, lossy image compression plays a crucial role to effectively increase the number of images collected under such constraints. However, lossy compression entails some undesired degradation of the data that may harm the performance of the downstream analysis task at hand, since important semantic information may be lost in the process. Moreover, we may only have compressed images at training time but are able to use original images at inference time (i.e. test), or vice versa, and in such a case, the downstream model suffers from covariate shift. In this paper, we analyze this phenomenon, with a special focus on vision-based perception for autonomous driving as a paradigmatic scenario. We see that loss of semantic information and covariate shift do indeed exist, resulting in a drop in performance that depends on the compression rate. In order to address the problem, we propose dataset restoration, based on image restoration with generative adversarial networks (GANs). Our method is agnostic to both the particular image compression method and the downstream task; and has the advantage of not adding additional cost to the deployed models, which is particularly important in resource-limited devices. The presented experiments focus on semantic segmentation as a challenging use case, cover a broad range of compression rates and diverse datasets, and show how our method is able to significantly alleviate the negative effects of compression on the downstream visual task. [ABSTRACT FROM AUTHOR]