Previous studies have shown that Chinese speakers and non-Chinese speakers exhibit different patterns of cross-modal congruence for the lexical tones of Mandarin Chinese, depending on which features of the pitch they attend to. But is this pattern of language-specific listening a conscious cultural strategy or an automatic processing effect? If automatic, does it also apply when the same pitch contours no longer sound like speech? Implicit Association Tests (IATs) provide an indirect measure of cross-modal association. In a series of IAT (...) studies, conducted with participants with three kinds of language backgrounds (Chinese-dominant bilinguals, Chinese balanced bilinguals, and English speakers with no Chinese experience) we find language-specific congruence effects for Mandarin lexical tones but not for matched sine-wave stimuli. That is, for linguistic stimuli, non-Chinese speakers show advantages for pitch-height congruence (high-pointy, low-curvy); no congruence effects were found for Chinese speakers. For non-linguistic stimuli, all participant groups showed advantages for pitch-height congruence. The present findings suggest that non-lexical tone congruence (high-pointy, low-curvy) is a basic congruence pattern, and the acquisition of a language with lexical tone can alter this perception. (shrink)

Contrary to the assumption of arbitrariness in modern linguistics, sound symbolism, which is the non-arbitrary relationship between sounds and meanings, exists. Sound symbolism, including the “Bouba–Kiki” effect, implies the universality of such relationships; individuals from different cultural and linguistic backgrounds can similarly relate sound-symbolic words to referents, although the extent of these similarities remains to be fully understood. Here, we examined if subjects from different countries could similarly infer the surface texture properties from words that sound-symbolically represent hardness in Japanese. (...) We prepared Japanese sound-symbolic words of which novelty was manipulated by a genetic algorithm. Japanese speakers in Japan and English speakers in both Singapore and the United States rated these words based on surface texture properties, as well as familiarity. The results show that hardness-related words were rated as harder and rougher than softness-related words, regardless of novelty and countries. Multivariate analyses of the ratings classified the hardness-related words along the hardness-softness dimension at over 80% accuracy, regardless of country. Multiple regression analyses revealed that the number of speech sounds /g/ and /k/ predicted the ratings of the surface texture properties in non-Japanese countries, suggesting a systematic relationship between phonetic features of a word and perceptual quality represented by the word across culturally and linguistically diverse samples. (shrink)