Conveying emotions in spoken poetry may be based on a poem’s semantic content and/or on emotional prosody, i.e. on acoustic features above single speech sounds. However, hypotheses of more direct sound–emotion relations in poetry, such as those based on the frequency of occurrence of certain phonemes, have not withstood empirical (re)testing. Therefore, we investigated sound–emotion associations based on prosodic features as a potential alternative route for the, at least partially, non-semantic expression and perception of emotions in poetry. We first conducted (...) a pre-study designed to validate relevant parameters of joy- and sadness-supporting prosody in the recitation, i.e. acoustic production, of poetry. The parameters obtained thereof guided the experimental modification of recordings of German joyful and sad poems such that for each poem, three prosodic variants were constructed: one with a joy-supporting prosody, one with a sadness-supporting prosody, and a neutral variant. In the subsequent experiment, native German speakers and participants with no command of German rated the joyfulness and sadness of these three variants. This design allowed us to investigate the role of emotional prosody, operationalized in terms of sound-emotion parameters, both in combination with and dissociated from semantic access to the emotional content of the poems. The findings from our pre-study showed that the emotional content of poems (based on pre-classifications into joyful and sad) indeed predicted the prosodic features pitch and articulation rate. The subsequent perception experiment revealed that cues provided by joyful and sad prosody specifically affect non-German-speaking listeners’ emotion ratings of the poems. Thus, the present investigation lends support to the hypothesis of prosody-based iconic relations between perceived emotion and sound qualia. At the same time, our findings also highlight that semantic access substantially decreases the role of cross-language sound–emotion associations and indicate that non-German-speaking participants may also use phonetic and prosodic cues other than the ones that were targeted and manipulated here. (shrink)

In this essay, I explore how cognitive science could illuminate the concept of beauty. Two results from the extensive literature on aesthetics guide my discussion. As the term “beauty” is overextended in general usage, I choose as my starting point the notion of “perfect form.” Aesthetic theorists are in reasonable agreement about the criteria for perfect form. What do these criteria imply for mental representations that are experienced as beautiful? Complexity theory can be used to specify constraints on mental representations (...) abstractly formulated as vectors in a high-dimensional space. A central feature of the proposed model is that perfect form depends both on features of the objects or events perceived and on the nature of the encoding strategies or model of the observer. A simple example illustrates the proposed calculations. A number of interesting implications that arise as a consequence of reformulating beauty in this way are noted. (shrink)

ABSTRACTIn this article we investigate structural differences between “literary” metaphors created by renowned poets and “nonliterary” ones imagined by non-professional authors from Katz et al.’s 1988 corpus. We provide data from quantitative narrative analyses of the altogether 464 metaphors on over 70 variables, including surface features like metaphor length, phonological features like sonority score, or syntactic-semantic features like sentence similarity. In a first computational study using machine learning tools we show that Katz et al.’s literary metaphors can be successfully discriminated (...) from their nonliterary ones on the basis of response measures, in particular the ratings for familiarity, ease of interpretation, semantic relatedness, and comprehensibility. A second computational study then shows that the classifier can reliably detect and predict between-group differences on the basis of five QNA features generalizing from a... (shrink)

Two main goals of the emerging field of neurocognitive poetics are the use of more natural and ecologically valid stimuli, tasks and contexts and providing methods and models allowing to quantify distinctive features of verbal materials used in such tasks and contexts and their effects on readers responses. A natural key element of poetic language, metaphor, still is understudied insofar as relatively little empirical research looked at literary or poetic metaphors. An exception is Katz et al.’s corpus of 204 literary (...) metaphors by authors such as Shakespeare or Dylan Thomas, for which various rating data are available. We reanalyzed their corpus using a combination of quantitative narrative analysis, latent semantic analysis, and machine learning in order to identify relevant features of the metaphors that influenced the ratings. The combined application of computational tools sheds light on surface and affective-semantic features that co-determine the reception of poetic metaphors and successfully predicted the period of origin, authorship and goodness ratings of the metaphors. The present results can be used for generating quantitative hypotheses or selecting and matching verbal stimuli in empirical studies of literature and neurocognitive poetics. (shrink)

The entropy-reduction hypothesis claims that the cognitive processing difficulty on a word in sentence context is determined by the word's effect on the uncertainty about the sentence. Here, this hypothesis is tested more thoroughly than has been done before, using a recurrent neural network for estimating entropy and self-paced reading for obtaining measures of cognitive processing load. Results show a positive relation between reading time on a word and the reduction in entropy due to processing that word, supporting the entropy-reduction (...) hypothesis. Although this effect is independent from the effect of word surprisal, we find no evidence that these two measures correspond to cognitively distinct processes. (shrink)