Automatic Chinese Personality Recognition Based on Prosodic Features

Zhao, Huan; Yang, Zhongzhen; Chen, Zuo; Zhang, Xixiang

doi:10.1007/978-3-319-14445-0_16

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…Among the most popular vocal features, we find pitch, energy, speech rate, first and second formant, cepstral, jitter, and shimmer (An et al, 2016;J. Biel et al, 2011;Kwon et al, 2013;Zhao et al, 2015). Some earlier works used a mixture of handcrafted automatically extracted audio features and manually annotated visual features (Nguyen et al, 2013).…”

Section: Features Extractionmentioning

confidence: 99%

Toward an integrative approach to nonverbal personality detection: Connecting psychological and artificial intelligence research.

Cannata¹,

Breil²,

Lepri³

et al. 2022

Technology, Mind, and Behavior

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Our first impressions of the people we meet are the subject of considerable interest, academic, and nonacademic. Such initial estimates of another's personality (e.g., their sociality or agreeableness) are vital, since they enable us to predict the outcomes of interactions (e.g., can we trust them?). Nonverbal behaviors are a key medium through which personality is expressed and detected. The character and reliability of these expression and detection processes have been investigated within two major fields: psychological research on personality judgments accuracy and Artificial Intelligence research on personality computing. Communication between these fields has, however, been infrequent. In the present perspective, we summarize the contributions and open questions of both fields and propose an integrative approach to combine their strengths and overcome their limitations. The integrated framework will enable novel research programs, such as (a), identifying which detection tasks better suit humans or computers, (b), harmonizing the nonverbal features extracted by humans and computers, and (c), integrating human and artificial agents in hybrid systems.

show abstract

Section: Features Extractionmentioning

confidence: 99%

Toward an integrative approach to nonverbal personality detection: Connecting psychological and artificial intelligence research.

Cannata¹,

Breil²,

Lepri³

et al. 2022

Technology, Mind, and Behavior

View full text Add to dashboard Cite

show abstract

“…Amongst the most popular vocal features, we find pitch, energy, speech rate, first and second formant, cepstral, jitter, shimmer (An et al, 2016;J. Biel et al, 2011;Kwon et Zhao et al, 2015). Some earlier works used a mixture of handcrafted automatically extracted audio features and manually annotated visual features (Nguyen et al, 2013).…”

Section: Features Extractionmentioning

confidence: 99%

Toward an Integrative Approach to Nonverbal Personality Detection: Connecting Psychological and Artificial Intelligence Research.

Cannata¹,

Breil²,

Back³

et al. 2021

Preprint

View full text Add to dashboard Cite

Our first impressions of the people we meet are the subject of considerable interest, academic and non-academic. Such initial estimates of another’s personality (e.g., their sociality or agreeableness) are vital, since they enable us to predict the outcomes of interactions (e.g., can we trust them?). Nonverbal behaviors are a key medium through which personality is expressed and detected. The character and reliability of these expression and detection processes have been investigated within two major fields: Psychological research on personality judgments accuracy and Artificial Intelligence research on personality computing. Communication between these fields has, however, been infrequent. In the present perspective, we summarize the contributions and open questions of both fields and propose an integrative approach to combine their strengths and overcome their limitations. The integrated framework will enable novel research programs, such as (i), identifying which detection tasks better suit humans or computers, (ii), harmonizing the nonverbal features extracted by humans and computers, and (iii), integrating human and artificial agents in hybrid systems.

show abstract