Literature DB >> 25775176

More than accuracy: Nonverbal dialects modulate the time course of vocal emotion recognition across cultures.

Xiaoming Jiang1, Silke Paulmann2, Jessica Robin3, Marc D Pell1.   

Abstract

Using a gating paradigm, this study investigated the nature of the in-group advantage in vocal emotion recognition by comparing 2 distinct cultures. Pseudoutterances conveying 4 basic emotions, expressed in English and Hindi, were presented to English and Hindi listeners. In addition to hearing full utterances, each stimulus was gated from its onset to construct 5 processing intervals to pinpoint when the in-group advantage emerges, and whether this differs when listening to a foreign language (English participants judging Hindi) or a second language (Hindi participants judging English). An index of the mean emotion identification point for each group and unbiased measures of accuracy at each time point was calculated. Results showed that in each language condition, native listeners were faster and more accurate than non-native listeners to recognize emotions. The in-group advantage emerged in both conditions after processing 400 ms to 500 ms of acoustic information. In the bilingual Hindi group, greater oral proficiency in English predicted faster and more accurate recognition of English emotional expressions. Consistent with dialect theory, our findings provide new evidence that nonverbal dialects impede both the accuracy and the efficiency of vocal emotion processing in cross-cultural settings, even when individuals are highly proficient in the out-group target language. (c) 2015 APA, all rights reserved).

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Mesh:

Year:  2015        PMID: 25775176     DOI: 10.1037/xhp0000043

Source DB:  PubMed          Journal:  J Exp Psychol Hum Percept Perform        ISSN: 0096-1523            Impact factor:   3.332


  5 in total

1.  Automaticity in the recognition of nonverbal emotional vocalizations.

Authors:  César F Lima; Andrey Anikin; Ana Catarina Monteiro; Sophie K Scott; São Luís Castro
Journal:  Emotion       Date:  2018-05-24

2.  Identifying the evidence of speech emotional dialects using artificial intelligence: A cross-cultural study.

Authors:  Sofia Kanwal; Sohail Asghar; Akhtar Hussain; Adnan Rafique
Journal:  PLoS One       Date:  2022-03-17       Impact factor: 3.240

3.  Cultural differences in vocal expression analysis: Effects of task, language, and stimulus-related factors.

Authors:  Shuyi Zhang; Marc D Pell
Journal:  PLoS One       Date:  2022-10-10       Impact factor: 3.752

4.  The development of cross-cultural recognition of vocal emotion during childhood and adolescence.

Authors:  Georgia Chronaki; Michael Wigelsworth; Marc D Pell; Sonja A Kotz
Journal:  Sci Rep       Date:  2018-06-14       Impact factor: 4.379

Review 5.  Good vibrations: A review of vocal expressions of positive emotions.

Authors:  Roza G Kamiloğlu; Agneta H Fischer; Disa A Sauter
Journal:  Psychon Bull Rev       Date:  2020-04
  5 in total

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