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4. To which world regions does the valence–dominance model of social perception apply?

Author

Jones, Benedict C., DeBruine, Lisa M., Flake, Jessica K., Liuzza, Marco Tullio, Antfolk, Jan, Arinze, Nwadiogo C., Ndukaihe, Izuchukwu L. G., Bloxsom, Nicholas G., Lewis, Savannah C., Foroni, Francesco, Willis, Megan L., Cubillas, Carmelo P., Vadillo, Miguel A., Turiegano, Enrique, Gilead, Michael, Simchon, Almog, Saribay, S. Adil, Owsley, Nicholas C., Jang, Chaning, Mburu, Georgina, Calvillo, Dustin P., Wlodarczyk, Anna, Qi, Yue, Ariyabuddhiphongs, Kris, Jarukasemthawee, Somboon, Manley, Harry, Suavansri, Panita, Taephant, Nattasuda, Stolier, Ryan M., Evans, Thomas R., Bonick, Judson, Lindemans, Jan W., Ashworth, Logan F., Hahn, Amanda C., Chevallier, Coralie, Kapucu, Aycan, Karaaslan, Aslan, Leongómez, Juan David, Sánchez, Oscar R., Valderrama, Eugenio, Vásquez-Amézquita, Milena, Hajdu, Nandor, Aczel, Balazs, Szecsi, Peter, Andreychik, Michael, Musser, Erica D., Batres, Carlota, Hu, Chuan-Peng, Liu, Qing-Lan, Legate, Nicole, Vaughn, Leigh Ann, Barzykowski, Krystian, Golik, Karolina, Schmid, Irina, Stieger, Stefan, Artner, Richard, Mues, Chiel, Vanpaemel, Wolf, Jiang, Zhongqing, Wu, Qi, Marcu, Gabriela M., Stephen, Ian D., Lu, Jackson G., Philipp, Michael C., Arnal, Jack D., Hehman, Eric, Xie, Sally Y., Chopik, William J., Seehuus, Martin, Azouaghe, Soufian, Belhaj, Abdelkarim, Elouafa, Jamal, Wilson, John P., Kruse, Elliott, Papadatou-Pastou, Marietta, De La Rosa-Gómez, Anabel, Barba-Sánchez, Alan E., González-Santoyo, Isaac, Hsu, Tsuyueh, Kung, Chun-Chia, Wang, Hsiao-Hsin, Freeman, Jonathan B., Oh, Dong Won, Schei, Vidar, Sverdrup, Therese E., Levitan, Carmel A., Cook, Corey L., Chandel, Priyanka, Kujur, Pratibha, Parganiha, Arti, Parveen, Noorshama, Pati, Atanu Kumar, Pradhan, Sraddha, Singh, Margaret M., Pande, Babita, Bavolar, Jozef, Kačmár, Pavol, Zakharov, Ilya, Álvarez-Solas, Sara, Baskin, Ernest, Thirkettle, Martin, Schmidt, Kathleen, Christopherson, Cody D., Leonis, Trinity, Suchow, Jordan W., Olofsson, Jonas K., Jernsäther, Teodor, Lee, Ai-Suan, Beaudry, Jennifer L., Gogan, Taylor D., Oldmeadow, Julian A., Balas, Benjamin, Stevens, Laura M., Colloff, Melissa F., Flowe, Heather D., Gülgöz, Sami, Brandt, Mark J., Hoyer, Karlijn, Jaeger, Bastian, Ren, Dongning, Sleegers, Willem W. A., Wissink, Joeri, Kaminski, Gwenaël, Floerke, Victoria A., Urry, Heather L., Chen, Sau-Chin, Pfuhl, Gerit, Vally, Zahir, Basnight-Brown, Dana M., Jzerman, Hans I., Sarda, Elisa, Neyroud, Lison, Badidi, Touhami, Van der Linden, Nicolas, Tan, Chrystalle B. Y., Kovic, Vanja, Sampaio, Waldir, Ferreira, Paulo, Santos, Diana, Burin, Debora I., Gardiner, Gwendolyn, Protzko, John, Schild, Christoph, Ścigała, Karolina A., Zettler, Ingo, O’Mara Kunz, Erin M., Storage, Daniel, Wagemans, Fieke M. A., Saunders, Blair, Sirota, Miroslav, Sloane, Guyan V., Lima, Tiago J. S., Uittenhove, Kim, Vergauwe, Evie, Jaworska, Katarzyna, Stern, Julia, Ask, Karl, van Zyl, Casper J. J., Körner, Anita, Weissgerber, Sophia C., Boudesseul, Jordane, Ruiz-Dodobara, Fernando, Ritchie, Kay L., Michalak, Nicholas M., Blake, Khandis R., White, David, Gordon-Finlayson, Alasdair R., Anne, Michele, Janssen, Steve M. J., Lee, Kean Mun, Nielsen, Tonje K., Tamnes, Christian K., Zickfeld, Janis H., Rosa, Anna Dalla, Vianello, Michelangelo, Kocsor, Ferenc, Kozma, Luca, Putz, Ádám, Tressoldi, Patrizio, Irrazabal, Natalia, Chatard, Armand, Lins, Samuel, Pinto, Isabel R., Lutz, Johannes, Adamkovic, Matus, Babincak, Peter, Baník, Gabriel, Ropovik, Ivan, Coetzee, Vinet, Dixson, Barnaby J. W., Ribeiro, Gianni, Peters, Kim, Steffens, Niklas K., Tan, Kok Wei, Thorstenson, Christopher A., Fernandez, Ana Maria, Hsu, Rafael M. C. S., Valentova, Jaroslava V., Varella, Marco A. C., Corral-Frías, Nadia S., Frías-Armenta, Martha, Hatami, Javad, Monajem, Arash, Sharifian, MohammadHasan, Frohlich, Brooke, Lin, Hause, Inzlicht, Michael, Alaei, Ravin, Rule, Nicholas O., Lamm, Claus, Pronizius, Ekaterina, Voracek, Martin, Olsen, Jerome, Giolla, Erik Mac, Akgoz, Aysegul, Özdoğru, Asil A., Crawford, Matthew T., Bennett-Day, Brooke, Koehn, Monica A., Okan, Ceylan, Gill, Tripat, Miller, Jeremy K., Dunham, Yarrow, Yang, Xin, Alper, Sinan, Borras-Guevara, Martha Lucia, Cai, Sun Jun, Tiantian, Dong, Danvers, Alexander F., Feinberg, David R., Armstrong, Marie M., Gilboa-Schechtman, Eva, McCarthy, Randy J., Muñoz-Reyes, Jose Antonio, Polo, Pablo, Shiramazu, Victor K. M., Yan, Wen-Jing, Carvalho, Lilian, Forscher, Patrick S., Chartier, Christopher R., and Coles, Nicholas A.

Published
2021
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8. Vocal attractiveness

Author

Feinberg, David R.

Subjects
306.7, HM1151.5F4, Voice--Psychological aspects, Sexual attraction, Mate selection, Voice--Physiology
Abstract

In this thesis, I aimed to explore vocal attractiveness from an evolutionary perspective: how listener's preferences for vocal qualities of potential partners could increase mating success and reproductive success. Chapters 1-4 outline the background to the thesis, reviews acoustics, sexual selection theory, and human mate-choice. In chapter 5, I correlated attributions made to voices to the acoustic properties of the voices. In men's voices, pitch negatively predicted vocal attractiveness. Attributions of masculinity, size, age, health and vocal attractiveness were all positively correlated. In women's voices, pitch, formant dispersion and perceived health positively predicted vocal attractiveness. Masculinity, size and age negatively predicted vocal attractiveness. In chapter 6, I measured the effect of manipulating fundamental and/or formant frequencies (apparent vocal-tract length) on vocal attributions. Women found men's voices with lowered voice pitch and decreased formant dispersion more attractive, masculine, large, older and healthier. Women's size predicted preference for male vocal- tract length. In chapter 7, I explored attitudes to voices speaking vowels and whole sentences using a correlation design and acoustic manipulations. Women's self-rated attractiveness positively predicted vocal masculinity preferences. Most of the remaining studies focus on how hormones relate to vocal production and perception. Women with less oestrogen showed the biggest menstrual cycle shifts in vocal masculinity preferences, preferring masculinity most in the fertile phase (chapter 8). Men's testosterone levels predicted the size of changes in attributions of dominance to men's voices (chapter 9). Women's voice pitch correlated with facial-metric masculinity and facial attractiveness (chapter 10). Men preferred women's voices with raised pitch to lowered pitch at multiple levels of starting pitch (chapter 11). These findings indicate men preferred femininity to averageness. In chapter 12, I relate the work in this thesis to other work and the broader evolutionary perspective.

Published
2005

50. The role of valence, dominance, and pitch in social perceptions of artificial intelligence (AI) conversational agents’ voices

Author

Lee, Anthony J, Shiramizu, Victor Kenji M., Jones, Benedict C., Feinberg, David R., and Altenburg, Daria

Abstract

There is growing concern that artificial intelligence (AI) conversational agents (e.g., Siri, Alexa) reinforce voice-based social stereotypes. Because little is known about social perceptions of conversational agents’ voices, we investigated the perceptual dimensions that underpin social perceptions of these synthetic voices and the role that acoustic parameters play in these perceptions. In Study 1 (N = 504), Principal Component Analysis of ratings of synthetic voices on a range of traits (trustworthiness, emotional stability, responsibility, sociability, caringness, attractiveness, intelligence, confidence, weirdness, unhappiness, meanness, aggressiveness, dominance, competence, age, masculinity, femininity) suggested that social perceptions of synthetic voices are underpinned by Valence and Dominance components that are highly similar to those previously reported for natural human stimuli. Study 1 also found that scores on the Dominance component were strongly and negatively related to voice pitch. Study 2 (N = 160) found that experimentally manipulating pitch in synthetic voices directly influenced perceptions of their dominance and aggressiveness, but not their competence or trustworthiness. Collectively, these results suggest that greater consideration of the role that voice pitch plays in dominance-related social perceptions when designing conversational agents will be effective in controlling stereotypic perceptions of their voices and the downstream consequences of those perceptions. (This research was supported by the EPSRC grant ‘Designing Conversational Assistants to Reduce Gender Bias’ EP/T023783/1, awarded to BCJ. Daria Altenburg was supported by Grant BOF.24Y.2019.0006.01 of Ghent University, awarded to Adriaan Spruyt.)

Published
2021
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