Since many real-world concepts are associated with colour, for example danger with red, linguistic information is often complimented with the use of appropriate colours in information visualization and product marketing. Yet, there is no comprehensive resource that captures concept-colour associations. We present a method to create a large word-colour association lexicon by crowdsourcing. We focus especially on abstract concepts and emotions to show that even though they cannot be physically visualized, they too tend to have strong colour associations. Finally, we show how word-colour associations manifest themselves in language, and quantify usefulness of co-occurrence and polarity cues in automatically detecting colour associations.
The relation between language and cognition has received considerable attention over the years, mainly on answering whether language impacts thought, and if so, to what extent. Experiments with colour categories have been used both to show that language has an effect on thought @cite_17 @cite_1 and that it does not @cite_14 . However, that line of work does not explicitly deal with word--colour associations. In fact, we did not find any other academic work that gathered large word--colour associations. There is, however, a commercial endeavor---Cymbolism http: www.cymbolism.com about .
@cite_14 @cite_1 @cite_17
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Recent research has shown that a two second glimpse of color can have an important influence on affect, cognition, and behavior. The present research examined whether perceiving color is necessary to produce an effect on psychological functioning or whether the mere act of processing a color word might be sufficient. Specifically, four experiments tested the hypothesis that processing the word red undermines intellectual performance, much like actually perceiving the color red. Supportive data were obtained with three different types of subtle manipulation, with three different types of control words, and on two different types of IQ test performance. Worry, but not mood or general arousal, was shown to mediate the semantic red effect, which appears to take place outside of individuals’ awareness. The theoretical and practical implications of the results are discussed. Since many real-world concepts are associated with colour, for example danger with red, linguistic information is often complimented with the use of appropriate colours in information visualization and product marketing. Yet, there is no comprehensive resource that captures concept-colour associations. We present a method to create a large word-colour association lexicon by crowdsourcing. We focus especially on abstract concepts and emotions to show that even though they cannot be physically visualized, they too tend to have strong colour associations. Finally, we show how word-colour associations manifest themselves in language, and quantify usefulness of co-occurrence and polarity cues in automatically detecting colour associations. Abstract In this study, we investigated the spatio-temporal patterns of category-specific cortical activation elicited by the visual presentation of words whose meaning relates to a color or to a visual form or shape. We recorded the event-related potentials (ERPs) of ten healthy, right-handed volunteers while they passively read words presented tachistoscopically. As early as 150 ms after stimulus onset, the ERPs revealed significant neurophysiological differences between words and strings of hash marks. Around 200 ms after stimulus onset, we found significant differences in the ERPs elicited by color- and form-related words. We used minimum norm current estimates to investigate the spatial location of these differences. This revealed that, at the 150 ms peak, the activation advantage of words over sequences of hash marks was located in a left posterior area, proximal to what has previously been called the visual word form area. At the 200 ms peak, the advantage of words related to colors over words related to forms seemed to reside in temporal cortical areas, whereas the form-related words elicited greater activation in frontal areas than color-related words. These results provide evidence for early access to detailed category-specific representations of word meaning, with subtle differences in meaning being reflected in the activation of different cortical areas, as early as 200 ms after stimulus presentation. In line with previous studies, these differences can be related to the areas involved in the conceptual processing of sensory (visual) and action-related information. Abstract Theories of lexical representation in production provide sophisticated accounts of the way in which information is activated during lexical access (e.g., Levelt, Roelofs, & Meyer, 1999 ), but there has been little attempt to account for the way in which the structure of the lexical entry affects the formulation processes that underlie the production of complex expressions. This paper first outlines such an account, and then reports three experiments that investigated the priming of noun-phrase structure in dialogue. Experiment 1 showed that speakers used a complex noun phrase containing a relative clause (e.g., “the square that’s red”) more often after hearing a syntactically similar noun phrase than after hearing a simple noun phrase, and that this effect was enhanced when the head noun (“square”) was repeated. Experiment 2 showed an enhanced priming effect when prime and target contained semantically related nouns (e.g., “goat” and “sheep”). Experiment 3 showed no enhanced effect when prime and target bore a close phonological relationship (e.g., “ship” and “sheep”). These results provide support for our account, and suggest that syntactic encoding may be unaffected by phonological feedback. How do emotions and moods color cognition? In this article, we examine how such reactions influence both judgments and cognitive performance. We argue that many affective influences are due, not to affective reactions themselves, but to the information they carry about value. The specific kind of influence that occurs depends on the focus of the agent at the time. When making evaluative judgments, for example, an agent's positive affect may emerge as a positive attitude toward a person or object. But when an agent focuses on a cognitive task, positive affect may act like feedback about the value of one's approach. As a result, positive affect tends to promote cognitive, relational processes, whereas negative affect tends to inhibit relational processing, resulting in more perceptual, stimulus-specific processing. As a consequence, many textbook phenomena from cognitive psychology occur readily in happy moods, but are inhibited or even absent in sad moods (149). Two projects explored the links between language use and aging. In the first project, written or spoken text samples from disclosure studies from over 3,000 research participants from 45 different studies representing 21 laboratories in 3 countries were analyzed to determine how people change in their use of 14 text dimensions as a function of age. A separate project analyzed the collected works of 10 well-known novelists, playwrights, and poets who lived over the last 500 years. Both projects found that with increasing age, individuals use more positive and fewer negative affect words, use fewer self-references, use more future-tense and fewer past-tense verbs, arid demonstrate a general pattern of increasing cognitive complexity. Implications for using language as a marker of personality among current and historical texts are discussed. The frequency of words and syntactic constructions has been observed to have a substantial effect on language processing. This begs the question of what causes certain constructions to be more or less frequent. A theory of grounding (Phillips, 2010) would suggest that cognitive limitations might cause languages to develop frequent constructions in such a way as to avoid processing costs. This paper studies how current theories of working memory fit into theories of language processing and what influence memory limitations may have over reading times. Measures of such limitations are evaluated on eye-tracking data and the results are compared with predictions made by different theories of processing. Three experiments were conducted to determine the psychometric properties of language in dyadic interactions. Using text-analysis, it was possible to assess the degree to which people coordinate their word use in natural conversations. In Experiments 1 (n = 130) and 2( n = 32), college students interacted in dyadic conversations in laboratory-based private Internet chat rooms. Experiment 3 analyzed the official transcripts of the Watergate tapes involving the dyadic interactions between President Richard Nixon and his aids H. R. Haldeman, John Erlichman, and John Dean. The results of the three studies offer sub- stantial evidence that individuals in dyadic interactions exhibit linguistic style matching (LSM) on both the conversation level as well as on a turn-by-turn level. Furthermore, LSM is unrelated to ratings of the quality of the interaction by both participants and judges. We propose that a coordination-engagement hypothesis is a better description of linguistic behaviors than the coordination-rapport hypothesis that has been proposed in the nonver- bal literature. For years social psychologists have exalted the power of the situa- tion. We comfortably acknowledge that across different situations, with different people, we may act in a range of ways, or even talk using a variety of styles. Aware of this tendency, Gergen (1972) began his explorations of our shifting masks of identity. In writing letters to close friends, he realized that he came across as a "completely different per- son" in each letter. "In one, I was morose, pouring out a philosophy of existential sorrow; in another I was a lusty realist: in a third I was a lighthearted jokester" (p. 32). Based merely on his word choices, Gergen inadvertently varied his style to adapt to the recipients of his letters. This is a prime demonstration of our inherent knowledge of the mutability of our language with respect to varying social contexts. Abstract In this paper we present the results of two experiments. The first is on the categorization of texture words in the English language. The goal was to determine whether there is a common basis for subjects' groupings of words related to visual texture, and if so, to identify the underlying dimensions used to categorize those words. Eleven major clusters were identified through hierarchical cluster analysis, ranging from ‘random’ to ‘repetitive’. These clusters remained intact in a multidimensional scaling solution. The stress for a three-dimensional solution obtained through multidimensional scaling was 0.18, meaning that 82 of the variance in the data is explained through the use of three dimensions. It appears that the major dimensions of texture descriptors are repetitive versus nonrepetitive; linearly oriented versus circularly oriented; and simple versus complex. In the second experiment we measured the strength of association between texture words and texture images. The goal was to determine whether there is any systematic correspondence between the domains of texture words and texture images. Pearson's coefficient of contingency, a measure of the strength of association, was found to be 0.63 for words corresponding to given images and 0.56 for images corresponding to given words. Thus the texture categories in the verbal space and those in the visual space are strongly tied. In sum, our two experiments show (a) that despite the tremendous variety in the words we have to describe textures, there is an underlying structure to the lexical space which can be derived from the experimental data; and (b) that the association between a category of words and a category of images was strongest when both categories represent the same underlying property. This suggests that subjects' organizations of texture terms are systematically tied to their organization of texture images. Abstract In this article we propose an account of the early development of children's knowledge about the mind and report two studies designed to test a part of it. According to this “connections-representations” account, young children begin their discovery of the mental world by learning that they and other people have internal experiences or mental states that connect them cognitively to external objects and events-experiences such as seeing them, hearing them, and wanting them. Later, they realize that the same object can be seriously (other than in pretense) mentally represented in different, seemingly contradictory ways: for example, as A in appearance, B in reality, C according to their perceptual or conceptual perspective, and D according to another person's. The results of both studies confirmed the prediction that 3-year-olds would perform well on appearance-reality and perceptual perspective-taking tasks requiring only an understanding of cognitive connections, but perform poorly on tasks requiring an understanding of seemingly-contrary-to-fact mental representations. To illustrate, children of this age had little difficulty determining that they could hear but could not see a noise-making object located on the experimenter's side of a barrier, and that the experimenter could see it (connections-level tasks). In contrast, they were largely unable to say, for instance, that a toy bear held behind a large elephant mask and emitting a cat sound looked like an elephant, sounded like a cat, and really was a toy bear (representations-level tasks)—even though the experimenter had actually told them previously what it looked like, sounded like, and really was. The article concludes with speculations about the possible origins of connections and representations knowledge and observations about the significance of these acquisitions for the child's development. “The Whorf thesis on the relationship between language and thought is found to involve the following two propositions: (a) Different linguistic communities perceive and conceive reality in different ways. (b) The language spoken in a community helps to shape the cognitive structure of the individual One of the main findings of cognitive sciences is that automatic processes of which we are unaware shape, to a significant extent, our perception of the environment. The phenomenon applies not only to the real world, but also to multimedia data we consume every day. Whenever we look at pictures, watch a video or listen to audio recordings, our conscious attention efforts focus on the observable content, but our cognition spontaneously perceives intentions, beliefs, values, attitudes and other constructs that, while being outside of our conscious awareness, still shape our reactions and behavior. So far, multimedia technologies have neglected such a phenomenon to a large extent. This paper argues that taking into account cognitive effects is possible and it can also improve multimedia approaches. As a supporting proof-of-concept, the paper shows not only that there are visual patterns correlated with the personality traits of 300 Flickr users to a statistically significant extent, but also that the personality traits (both self-assessed and attributed by others) of those users can be inferred from the images these latter post as "favourite". Natural language meanings allow speakers to encode important real-world distinctions, but corpora of grounded language use also reveal that speakers categorize the world in different ways and describe situations with different terminology. To learn meanings from data, we therefore need to link underlying representations of meaning to models of speaker judgment and speaker choice. This paper describes a new approach to this problem: we model variability through uncertainty in categorization boundaries and distributions over preferred vocabulary. We apply the approach to a large data set of color descriptions, where statistical evaluation documents its accuracy. The results are available as a Lexicon of Uncertain Color Standards (LUX), which supports future efforts in grounded language understanding and generation by probabilistically mapping 829 English color descriptions to potentially context-sensitive regions in HSV color space. The question of how meaning might be acquired by young children and represented by adult speakers of a language is one of the most debated topics in cognitive science. Existing semantic representation models are primarily amodal based on information provided by the linguistic input despite ample evidence indicating that the cognitive system is also sensitive to perceptual information. In this work we exploit the vast resource of images and associated documents available on the web and develop a model of multimodal meaning representation which is based on the linguistic and visual context. Experimental results show that a closer correspondence to human data can be obtained by taking the visual modality into account. An elementary way of using language is to refer to objects. Often, these objects are physically present in the shared environment and reference is done via mention of perceivable properties of the objects. This is a type of language use that is modelled well neither by logical semantics nor by distributional semantics, the former focusing on inferential relations between expressed propositions, the latter on similarity relations between words or phrases. We present an account of word and phrase meaning that is perceptually grounded, trainable, compositional, and ‘dialogueplausible’ in that it computes meanings word-by-word. We show that the approach performs well (with an accuracy of 65 on a 1-out-of-32 reference resolution task) on direct descriptions and target landmark descriptions, even when trained with less than 800 training examples and automatically transcribed utterances. How do children learn that the word "dog" refers not to all four-legged animals, and not just to Ralph, but to all members of a particular species? How do they learn the meanings of verbs like "think," adjectives like "good," and words for abstract entities such as "mortgage" and "story"? The acquisition of word meaning is one of the fundamental issues in the study of mind. According to Paul Bloom, children learn words through sophisticated cognitive abilities that exist for other purposes. These include the ability to infer others' intentions, the ability to acquire concepts, an appreciation of syntactic structure, and certain general learning and memory abilities. Although other researchers have associated word learning with some of these capacities, Bloom is the first to show how a complete explanation requires all of them. The acquisition of even simple nouns requires rich conceptual, social, and linguistic capacities interacting in complex ways. This book requires no background in psychology or linguistics and is written in a clear, engaging style. Topics include the effects of language on spatial reasoning, the origin of essentialist beliefs, and the young child's understanding of representational art. The book should appeal to general readers interested in language and cognition as well as to researchers in the field. Besides making our thoughts more vivid and filling our communication with richer imagery, metaphor also plays an important structural role in our cognition. Although there is a consensus in the linguistics and NLP research communities that the phenomenon of metaphor is not restricted to similarity-based extensions of meanings of isolated words, but rather involves reconceptualization of a whole area of experience (target domain) in terms of another (source domain), there still has been no proposal for a comprehensive procedure for annotation of cross-domain mappings. However, a corpus annotated for conceptual mappings could provide a new starting point for both linguistic and cognitive experiments. The annotation scheme we present in this paper is a step towards filling this gap. We test our procedure in an experimental setting involving multiple annotators and estimate their agreement on the task. The associated corpus annotated for source target domain mappings will be publicly available. The verbal and nonverbal channels of human communication are internally and intricately connected. As a result, gestures and speech present high levels of correlation and coordination. This relationship is greatly affected by the linguistic and emotional content of the message. The present paper investigates the influence of articulation and emotions on the interrelation between facial gestures and speech. The analyses are based on an audio-visual database recorded from an actress with markers attached to her face, who was asked to read semantically neutral sentences, expressing four emotion states (neutral, sadness, happiness, and anger). A multilinear regression framework is used to estimate facial features from acoustic speech parameters. The levels of coupling between the communication channels are quantified by using Pearson's correlation between the recorded and estimated facial features. The results show that facial and acoustic features are strongly interrelated, showing levels of correlation higher than r = 0.8 when the mapping is computed at sentence-level using spectral envelope speech features. The results reveal that the lower face region provides the highest activeness and correlation levels. Furthermore, the correlation levels present significant interemo- tional differences, which suggest that emotional content affect the relationship between facial gestures and speech. Principal component analysis (PCA) shows that the audiovisual mapping parameters are grouped in a smaller subspace, which suggests that there is an emotion-dependent structure that is preserved from across sentences. The results suggest that this internal structure seems to be easy to model when prosodic-features are used to estimate the audiovisual mapping. The results also reveal that the correlation levels within a sentence vary according to broad phonetic properties presented in the sentence. Consonants, especially unvoiced and fricative sounds, present the lowest correlation levels. Likewise, the results show that facial gestures are linked at different resolutions. While the orofacial area is locally connected with the speech, other facial gestures such as eyebrow motion are linked only at the sentence-level. The results presented here have important implications for applications such as facial animation and multimodal emotion recognition. People interpret abstract meanings from colors, which makes color a useful perceptual feature for visual communication. This process is complicated, however, because there is seldom a one-to-one correspondence between colors and meanings. One color can be associated with many different concepts (one-to-many mapping) and many colors can be associated with the same concept (many-to-one mapping). We propose that to interpret color-coding systems, people perform assignment inference to determine how colors map onto concepts. We studied assignment inference in the domain of recycling. Participants saw images of colored but unlabeled bins and were asked to indicate which bins they would use to discard different kinds of recyclables and trash. In Experiment 1, we tested two hypotheses for how people perform assignment inference. The local assignment hypothesis predicts that people simply match objects with their most strongly associated color. The global assignment hypothesis predicts that people also account for the association strengths between all other objects and colors within the scope of the color-coding system. Participants discarded objects in bins that optimized the color-object associations of the entire set, which is consistent with the global assignment hypothesis. This sometimes resulted in discarding objects in bins whose colors were weakly associated with the object, even when there was a stronger associated option available. In Experiment 2, we tested different methods for encoding color-coding systems and found that people were better at assignment inference when color sets simultaneously maximized the association strength between assigned color-object parings while minimizing associations between unassigned pairings. Our study provides an approach for designing intuitive color-coding systems that facilitate communication through visual media such as graphs, maps, signs, and artifacts. Representing words into vectors in continuous space can form up a potentially powerful basis to generate high-quality textual features for many text mining and natural language processing tasks. Some recent efforts, such as the skip-gram model, have attempted to learn word representations that can capture both syntactic and semantic information among text corpus. However, they still lack the capability of encoding the properties of words and the complex relationships among words very well, since text itself often contains incomplete and ambiguous information. Fortunately, knowledge graphs provide a golden mine for enhancing the quality of learned word representations. In particular, a knowledge graph, usually composed by entities (words, phrases, etc.), relations between entities, and some corresponding meta information, can supply invaluable relational knowledge that encodes the relationship between entities as well as categorical knowledge that encodes the attributes or properties of entities. Hence, in this paper, we introduce a novel framework called RC-NET to leverage both the relational and categorical knowledge to produce word representations of higher quality. Specifically, we build the relational knowledge and the categorical knowledge into two separate regularization functions, and combine both of them with the original objective function of the skip-gram model. By solving this combined optimization problem using back propagation neural networks, we can obtain word representations enhanced by the knowledge graph. Experiments on popular text mining and natural language processing tasks, including analogical reasoning, word similarity, and topic prediction, have all demonstrated that our model can significantly improve the quality of word representations.