• Corpus ID: 9410196

Iconicity in Word Learning: What Can We Learn from Cross-Situational Learning Experiments?

  title={Iconicity in Word Learning: What Can We Learn from Cross-Situational Learning Experiments?},
  author={John Matthew Jones and Gabriella Vigliocco},
  journal={Cognitive Science},
Iconicity, i.e. resemblance between form and meaning, is a widespread feature of natural language vocabulary (Perniss, Thompson, & Vigliocco, 2010), and has been shown to facilitate vocabulary acquisition (Imai, Kita, Nagumo, & Okada). But what kind of advantage does iconicity actually give? Here we use cross-situational learning (Yu & Smith, 2007), to address the question for sound-shape iconicity (the so-called kiki-bouba effect, Ramachandran & Hubbard, 2001). In contrast to Monaghan, Mattock… 
Towards emotion recognition in texts: A sound-symbolic experiment
  • V. Slavova
  • Psychology
    International Journal of Cognitive Research in Science Engineering and Education
  • 2019
The purpose of this study is to investigate the relationship between the phonetic content of prose texts in English and the emotion that the texts inspire, namely - the effect of vowel-consonant


Iconicity as a General Property of Language: Evidence from Spoken and Signed Languages
The idea that iconicity need also be recognized as a general property of language, which may serve the function of reducing the gap between linguistic form and conceptual representation to allow the language system to “hook up” to motor, perceptual, and affective experience is put forward.
Rapid Word Learning Under Uncertainty via Cross-Situational Statistics
A cross-situational learning strategy based on computing distributional statistics across words, across referents, and, most important, across the co-occurrences of words and refereNTs at multiple moments to rapidly learn word-referent pairs even in highly ambiguous learning contexts.
The role of sound symbolism in language learning.
It is found that sound symbolism resulted in an advantage for learning categories of sound-shape mappings but did not assist in learning individual word meanings, consistent with the limited presence of sound symbolism in natural language.
Iconicity in English and Spanish and Its Relation to Lexical Category and Age of Acquisition
Findings show that iconicity is a graded quality that pervades vocabularies of even the most “arbitrary” spoken languages, including Indo-European languages.
The shape of words in the brain
In a categorisation task that captures the processes involved in natural language interpretation, participants were faster to identify novel objects when label-object mappings were sound-symbolic than when they were not, highlighting the non-arbitrary relation between the objects and the labels used to name them.
Synaesthesia? A window into perception, thought and language
We investigated grapheme–colour synaesthesia and found that: (1) The induced colours led to perceptual grouping and pop-out, (2) a grapheme rendered invisible through ‘crowding’ or lateral masking
Japanese Sound-Symbolism Facilitates Word Learning in English-Speaking Children
It is concluded that children are sensitive to universal sound-symbolism and can utilize it in word learning and generalization, regardless of their native language.
Sound symbolism facilitates early verb learning
It is reported that 25-month-old children are sensitive to cross-linguistically valid sound-symbolic matches in the domain of action and that this sound symbolism facilitates verb learning in young children, suggesting that iconic scaffolding by means of sound symbolism plays an important role in early verb learning.
Random effects structure for confirmatory hypothesis testing: Keep it maximal.
It is argued that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades, and it is shown thatLMEMs generalize best when they include the maximal random effects structure justified by the design.
A weakly informative default prior distribution for logistic and other regression models
We propose a new prior distribution for classical (nonhierarchical) logistic regression models, constructed by first scaling all nonbinary variables to have mean 0 and standard deviation 0.5, and