@article {494,
	title = {Linguistic asymmetries in cross-cultural emotion recognition},
	year = {2021},
	publisher = {Nederlandse Vereniging voor Fonetische Wetenschappen},
	address = {online},
	abstract = {The aim of this study is to explore cross-linguistic/cross-cultural recognition of emotion in a relatively understudied language (Korean). Previous studies on cross-linguistic emotion recognition found that intercultural emotion recognition is the combination of universal, cultural and, to a lesser extent, linguistic factors (Mesquita \& Fridja, 1992; Scherer, 1997a, 1997b). However, these studies have mostly adopted unbalanced experimental designs that either used a {\textquotedblleft}one-to-many{\textquotedblright} approach (presenting the same stimuli to different listener groups), or a {\textquotedblleft}many-to-one{\textquotedblright} approach (presenting different stimuli to the same listeners). Moreover, these studies are often limited to basic emotions (Ekman, 1992). Consequently, current work on cross-linguistic emotion recognition may fail to take linguistic asymmetries into account. Thus, in the present study, we developed a full cross-language design ({\textquotedblleft}two-to-two{\textquotedblright}), with speakers and listeners from two typologically different languages and different cultures, Dutch and Korean. Participants heard carrier phrases that are linguistically appropriate in both languages ([nuto hɔm sɛpika{\ng}]) expressed with eight different emotions (balanced in terms of valence and arousal), and were then asked to choose one of the eight emotions that they thought the speaker was expressing. 

Consistent with previous studies, our data revealed that both groups can successfully decode the emotions above chance level, supporting the universal hypothesis (Scherer et al., 2001). Also consistent with previous work (Elfenbein \& Ambady, 2002), our data highlighted an in-group advantage for recognizing vocal emotions produced in listeners{\textquoteright} native language. The similarities and differences in confusion patterns across languages will be discussed in terms of the influence of linguistic asymmetries. 

References

Ekman, P. (1992). An argument for basic emotions. Cognition and Emotion, 6, 169{\textendash} 200. 
Elfenbein, H. A., \& Ambady, H. (2002). On the universality and cultural specificity of emotion recognition: a meta-analysis. Psychological bulletin, 128, 203-235. 
Mesquita, B., \& Frijda, N. H. (1992). Cultural variations in emotions: A review. Psychological Bulletin, 112, 179 {\textendash}204. 
Scherer, K. R. (1997a). Profiles of emotion-antecedent appraisal: Testing theoretical predictions across cultures. Cognition and Emotion, 11, 113-150. 
Scherer, K. R. (1997b). The role of culture in emotion-antecedent appraisal. Journal of Personality and Social Psychology, 73, 902-922. 
Scherer, K. R., Banse, R., \& Wallbott, H. G. (2001). Emotion inferences from vocal expression correlate across languages and cultures. Journal of Cross Culture Psychology, 32, 76-92.
},
	author = {Liang, Yachan and Mirjam Broersma and Martijn Goudbeek and Konopka, Agnieszka and Choi, Jiyoun}
}
@article {467,
	title = {Poster: Auditory and Visual Cues in the Production and Perception of Mandarin Tones},
	year = {2019},
	publisher = {Nederlandse Vereniging voor Fonetische Wetenschappen},
	address = {Amsterdam, The Netherlands},
	abstract = {Which acoustic and visual cues can be used to classify Mandarin tones? Furthermore, are these cues the same for producers (i.e., the ground truth) and (tone-na{\"\i}ve) perceivers? To address these questions we video-taped four Mandarin speakers while they produced ten syllables with four Mandarin tones, i.e. forty words in two styles (natural and teaching), totaling 160 stimuli. The audiovisual stimuli were subsequently presented to 43 tone-na{\"\i}ve participants in a tone identification task. Basic acoustic and visual features were extracted. We used decision trees and machine learning to identify the most important acoustic and visual features for classifying the tones. These features were identified separately for the tones as produced by the four speakers and for the tones as identified by the 43 perceivers. Based on previous work, we expected that acoustic features would be more relevant than visual features, but that non-native perceivers might still benefit from the visual signal. The results showed that acoustic features were ranked higher than the visual features for tone classification, both for the classification of the intended and the perceived tone. However, tone perceivers did revert to the use of visual information in certain cases. So, while visual information does not seem to play a significant role in native speakers{\textquoteright} tone production, tone-na{\"\i}ve perceivers do sometimes consider visual information in their tone identification.},
	author = {Yueqiao Han and Castro Ferreira, Thiago and Martijn Goudbeek and Maria Mos and Marc Swerts}
}
@article {449,
	title = {Mandarin tone identification by musicians and non-musicians: effects of modality and speaking style},
	year = {2018},
	publisher = {Nederlandse Vereniging voor Fonetische Wetenschappen},
	address = {Amsterdam, The Netherlands},
	abstract = {A considerable number of studies have shown that musical ability has a positive effect on second language learning. Extending the existing body of work, this study investigates the combined effects of musical ability, modality and speaking style on Mandarin tone identification in tone-na{\"\i}ve listeners. To examine the effects of visual information and hyperarticulated speech, Mandarin tones elicited in two speaking styles (natural and teaching style) were presented in audio-only or audiovisual modality to listeners with or without musical experience. The Goldsmith Musicality Index was used to measure the musical aptitude of the participants. Musicians generally outperformed non-musicians in a tone identification task, and modality and speaking style both affected the tone identification: participants performed better in the audiovisual and teaching style conditions. In addition, the tones differed in recognition: the identification of tone 3 (a low-falling-rising) proved the easiest and all participants had more difficulty identifying tone 4 (a high-falling). Musical training was the most important predictor for Mandarin tone perception. These findings suggest that learning to perceive Mandarin tones benefits from musical expertise, visual information and hyperarticulated speaking style.},
	keywords = {Mandarin tone identification; audiovisual modality; speaking style; musicians and non-musicians},
	author = {Yueqiao Han and Martijn Goudbeek and Maria Mos and Marc Swerts}
}
