Cognitive Science

Abstract Research on the relation between sound and meaning in language has reported substantial evidence for implicit associations between articulatory?acoustic characteristics of phonemes and emotions. In the present study, we specifically tested the relation between the acoustic properties of a text and its emotional tone as perceived by readers. To this end, we asked participants to assess the emotional tone of single stanzas extracted from a large variety of poems. The selected stanzas had either an extremely high, a neutral, or an extremely low average formant dispersion. To assess the average formant dispersion per stanza, all words were phonetically transcribed and the distance between the first and second formant per vowel was calculated. Building on a long tradition of research on associations between sound frequency on the one hand and non-acoustic concepts such as size, strength, or happiness on the other hand, we hypothesized that stanzas with an extremely high average formant dispersion would be rated lower on items referring to Potency (dominance) and higher on items referring to Activity (arousal) and Evaluation (emotional valence). The results confirmed our hypotheses for the dimensions of Potency and Evaluation, but not for the dimension of Activity. We conclude that, at least in poetic language, extreme values of acoustic features of vowels are a significant predictor for the emotional tone of a text

Questioning Arbitrariness in Language: a Data-Driven Study of Conventional Iconicity

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The Natural Selection of Words: Finding the Features of Fitness

We introduce a dataset for studying the evolution of words, constructed from WordNet and the Google Books Ngram Corpus. The dataset tracks the evolution of 4,000 synonym sets (synsets), containing 9,000 English words, from 1800 AD to 2000 AD. We present a supervised learning algorithm that is able to predict the future leader of a synset: the word in the synset that will have the highest frequency. The algorithm uses features based on a word's length, the characters in the word, and the historical frequencies of the word. It can predict change of leadership (including the identity of the new leader) fifty years in the future, with an F-score considerably above random guessing. Analysis of the learned models provides insight into the causes of change in the leader of a synset. The algorithm confirms observations linguists have made, such as the trend to replace the -ise suffix with -ize, the rivalry between the -ity and -ness suffixes, and the struggle between economy (shorter words are easier to remember and to write) and clarity (longer words are more distinctive and less likely to be confused with one another). The results indicate that integration of the Google Books Ngram Corpus with WordNet has significant potential for improving our understanding of how language evolves

Exploring the adaptive structure of the mental lexicon

The mental lexicon is a complex structure organised in terms of phonology, semantics and syntax, among other levels. In this thesis I propose that this structure can be explained in terms of the pressures acting on it: every aspect of the organisation of the lexicon is an adaptation ultimately related to the function of language as a tool for human communication, or to the fact that language has to be learned by subsequent generations of people. A collection of methods, most of which are applied to a Spanish speech corpus, reveal structure at different levels of the lexicon.• The patterns of intra-word distribution of phonological information may be a consequence of pressures for optimal representation of the lexicon in the brain, and of the pressure to facilitate speech segmentation.• An analysis of perceived phonological similarity between words shows that the sharing of different aspects of phonological similarity is related to different functions. Phonological similarity perception sometimes relates to morphology (the stressed final vowel determines verb tense and person) and at other times shows processing biases (similarity in the word initial and final segments is more readily perceived than in word-internal segments).• Another similarity analysis focuses on cooccurrence in speech to create a representation of the lexicon where the position of a word is determined by the words that tend to occur in its close vicinity. Variations of context-based lexical space naturally categorise words syntactically and semantically.• A higher level of lexicon structure is revealed by examining the relationships between the phonological and the cooccurrence similarity spaces. A study in Spanish supports the universality of the small but significant correlation between these two spaces found in English by Shillcock, Kirby, McDonald and Brew (2001). This systematicity across levels of representation adds an extra layer of structure that may help lexical acquisition and recognition. I apply it to a new paradigm to determine the function of parameters of phonological similarity based on their relationships with the syntacticsemantic level. I find that while some aspects of a language's phonology maintain systematicity, others work against it, perhaps responding to the opposed pressure for word identification.This thesis is an exploratory approach to the study of the mental lexicon structure that uses existing and new methodology to deepen our understanding of the relationships between language use and language structure

The building blocks of sound symbolism

Languages contain thousands of words each and are made up by a seemingly endless collection of sound combinations. Yet a subsection of these show clear signs of corresponding word shapes for the same meanings which is generally known as vocal iconicity and sound symbolism. This dissertation explores the boundaries of sound symbolism in the lexicon from typological, functional and evolutionary perspectives in an attempt to provide a deeper understanding of the role sound symbolism plays in human language. In order to achieve this, the subject in question was triangulated by investigating different methodologies which included lexical data from a large number of language families, experiment participants and robust statistical tests.Study I investigates basic vocabulary items in a large number of language families in order to establish the extent of sound symbolic items in the core of the lexicon, as well as how the sound-meaning associations are mapped and interconnected. This study shows that by expanding the lexical dataset compared to previous studies and completely controlling for genetic bias, a larger number of sound-meaning associations can be established. In addition, by placing focus on the phonetic and semantic features of sounds and meanings, two new types of sounds symbolism could be established, along with 20 semantically and phonetically superordinate concepts which could be linked to the semantic development of the lexicon.Study II explores how sound symbolic associations emerge in arbitrary words through sequential transmission over language users. This study demonstrates that transmission of signals is sufficient for iconic effects to emerge and does not require interactional communication. Furthermore, it also shows that more semantically marked meanings produce stronger effects and that iconicity in the size and shape domains seems to be dictated by similarities between the internal semantic relationships of each oppositional word pair and its respective associated sounds.Studies III and IV use color words to investigate differences and similarities between low-level cross-modal associations and sound symbolism in lexemes. Study III explores the driving factors of cross-modal associations between colors and sounds by experimentally testing implicit preferences between several different acoustic and visual parameters. The most crucial finding was that neither specific hues nor specific vowels produced any notable effects and it is therefore possible that previously reported associations between vowels and colors are actually dependent on underlying visual and acoustic parameters.Study IV investigates sound symbolic associations in words for colors in a large number of language families by correlating acoustically described segments with luminance and saturation values obtained from cross-linguistic color-naming data. In accordance with Study III, this study showed that luminance produced the strongest results and was primarily associated with vowels, while saturation was primarily associated with consonants. This could then be linked to cross-linguistic lexicalization order of color words.To summarize, this dissertation shows the importance of studying the underlying parameters of sound symbolism semantically and phonetically in both language users and cross-linguistic language data. In addition, it also shows the applicability of non-arbitrary sound-meaning associations for gaining a deeper understanding of how linguistic categories have developed evolutionarily and historically