Revista CEFAC
https://revistacefac.org.br/article/doi/10.1590/1982-0216/20242653624
Revista CEFAC
Original Articles

Emotional prosody recognition using pseudowords from the Hoosier Vocal Emotions Collection

Reconhecimento da prosódia emocional por meio de pseudopalavras do Hoosier Vocal Emotions Collection

Paulo Vitor de Oliveira Santos Matos; Rayssa Silva Santos Andrade; Maria Inês Beltrati Cornacchioni Rehder; Raphaela Barroso Guedes-Granzotti; Kelly da Silva; Carla Patrícia Hernandez Alves Ribeiro César

http://dx.doi.org/10.1590/1982-0216/20242653624 Revista CEFAC, vol.26, n5, e3624, 2024
PDF English
PDF Português
SciELO
Downloads: 0
Views: 109

Abstract

Purpose: to verify whether the Hoosier Vocal Emotions Collection corpus allows the identification of different emotional prosodies in Brazilian adults.

Methods: 60 healthy adults equally distributed by sex, aged between 18 and 42 years, participated in the Mini-Mental State Examination and subtests related to prosody (Montreal communication battery and those from the Hoosier Vocal Emotions Collection corpus, with 73 pseudowords produced by two different actresses). The results were analyzed using descriptive statistics and the Chi-square test, which had a significance of 5%.

Results: in general, the emotional prosodies from the Hoosier Vocal Emotions Collection were identified with an average accuracy of 43.63%, with the highest hits, in descending order, for neutrality, sadness, happiness, disgust, anger, and fear. As for sex, there were statistically significant differences regarding the correct answers in the neutrality and disgust prosodies for males, while for females, there were differences in happiness and anger prosodies. Both sexes had more incredible difficulty in identifying prosody related to fear.

Conclusion: the Hoosier Vocal Emotions Collection corpus allowed the identification of the emotional prosodies tested in the studied sample, with sexual dysmorphism to emotional prosodic identification being found.

Keywords

Emotions; Voice Recognition; Speech, Language and Hearing Sciences

Resumo

Objetivo: verificar se o corpus do Hoosier Vocal Emotions Collection permite a identificação de diferentes prosódias emocionais em adultos brasileiros, além de vislumbrar se a respectiva identificação é igual entre os sexos.

Métodos: 60 adultos hígidos distribuídos igualmente pelo sexo, com idades entre 18 e 42 anos, participaram do Mini-Exame do Estado Mental e de subtestes relacionados à prosódia (bateria Montreal de comunicação e os do corpus do Hoosier Vocal Emotions Collection, com 73 pseudopalavras produzidas por duas atrizes distintas). A análise dos resultados ocorreu por estatística descritiva e pelo teste Qui-quadrado com significância de 5%.

Resultados: de forma geral, as prosódias emocionais do Hoosier Vocal Emotions Collection foram identificadas com precisão média de 43,63%, com maiores acertos, em ordem decrescente, para: neutro, tristeza, alegria, aversão, raiva e medo. Em relação ao sexo, houve diferenças estatisticamente significantes quanto aos acertos nas prosódias de neutralidade e aversão para o masculino, enquanto para o feminino nas prosódias de alegria e raiva. Ambos os sexos apresentaram maior dificuldade na identificação da prosódia relacionada ao medo.

Conclusão: o corpus do Hoosier Vocal Emotions Collection permitiu a identificação das prosódias emocionais testadas na amostra estudada, sendo constatada presença de dismorfismo sexual em relação à identificação prosódica emocional.

Palavras-chave

Emoções; Reconhecimento de Voz; Fonoaudiologia

References

1. Sznycer D, Cohen AS. Are emotions natural kinds after all? Rethinking the issue of response coherence. Evol. psychol. 2021;19(2):14747049211016009. https://doi.org/10.1177/14747049211016009 PMID: 34060370.

2. César CPHAR, Pellicani AD, Farias IS, Reis LF, Santos L. The identification of voice in emotions: A narrative review of the literature. In: Pereira S, César CPHAR, Landy N, editors. Face Summit 2021. Porto: FeeLab; 2022. p. 51-67.

3. Kim J, Toutios A, Lee S, Narayanan SS. Vocal tract shaping of emotional speech. Comput. Speech Lang. 2020;64:101100. https://doi.org/10.1016/j.csl.2020.101100 PMID: 32523241.

4. Yeshoda K, Raveendran R, Konadath S. Perception of vocal emotional prosody in children with hearing impairment. Int. j. pediatr. otorhinolaryngol. 2020;137:110252. https://doi.org/10.1016/j.ijporl.2020.110252 PMID: 32896359.

5. Coulombe V, Happinessal M, Martel-Sauvageau V, Monetta L. Affective prosody disorders in adults with neurological conditions: A scoping review. International Int. J. Lang. Commun. Disord. 2023;58(6):1939-54. https://doi.org/10.1111/1460-6984.12909 PMID: 37212522.

6. Zhang M, Xu S, Chen Y, Lin Y, Ding H, Zhang Y. Recognition of affective prosody in autism spectrum conditions: A systematic review and meta-analysis. Autism. 2022;26(4):798-813. https://doi.org/10.1177/1362361321995725 PMID: 33722094.

7. Ikeda S. Overcoming lexical bias in the judgment of emotion in speech: Role of executive function and usefulness understanding in young children. J. genet. psychol. 2022;183(3):211-21. https://doi.org/10.1080/00221325.2022.2037499 PMID: 35132942.

8. Darcy I, Fontaine NMG. The Hoosier vocal emotions corpus: a validated set of north american English pseudowords for evaluating emotion processing. Behav. Res. Meth. 2020;52(2):901-17. https://doi.org/10.3758/s13428-019-01288-0 PMID: 31485866.

9. Kerr MS, Pagliarin KC, Mineiro A, Ferré P, Joanette Y, Fonseca RP. Montreal Communication Evaluation Battery - Portuguese version: Age and education effects. CoDAS. 2015;27(6):550-6. https://doi.org/10.1590/2317-1782/20152015029 PMID: 26691619.

10. Folstein MF, Folstein SE, McHugh PR. Mini-Mental State: A practical method for grading the cognitive state of patients for clinician. J. Psychiatr. Res. 1975;12:189-98. https://doi.org/10.1016/0022-3956(75)90026-6 PMID: 1202204.

11. Bertolucci PHF, Brucki SMD, Campacci SR, Juliano Y. O mini-exame do estado mental em uma população geral: impacto da escolaridade. Arq. Neuro-Psiquiatr. 1994;52(1):1-7. https://doi.org/10.1590/S0004-282X1994000100001 PMID: 1202204.

12. Fonseca RP, Parente MAMP, Côté H, Joanette Y. Adaptation process to Brazilian Portuguese of the Montreal communication evaluation battery: MAC battery. Psicol. Reflex. Crit. 2007;20:259-67. https://doi.org/10.1590/S0102-79722007000200012

13. Gruber T, Debracque C, Ceravolo L, Igloi K, Bosch BM, Frühholz S et al. Human discrimination and categorization of emotions in voices: A functional near-infrared spectroscopy (fNIRS) study. Front. Neurosci. 2020;14:570. https://doi.org/10.3389/fnins.2020.00570.eCollection2020 PMID: 32581695.

14. van Rijn P, Larrouy-Maestri P. Modelling individual and cross-cultural variation in the mapping of emotions to speech prosody. Nat. Hum. Behav. 2023;7(3):386-96. https://doi.org/10.1038/s41562-022-01505-5 PMID: 36646838.

15. Morningstar M, Gilbert AC, Burdo J, Leis M, Dirks MA. Recognition of vocal socioemotional expressions at varying levels of emotional intensity. Emotion. 2021;21(7):1570-5. https://doi.org/10.1037/emo0001024 PMID: 34570558.

16. Scherer KR. Vocal communication of emotion: A review of research paradigms. Speech Commun. 2003;40(1-2):227-56. https://doi.org/10.1016/S0167-6393(02)00084-5

17. Ertürk A, Gürses E, Kulak Kayikci ME. Sex related differences in the perception and production of emotional prosody in adults. Psychol. Res. 2024;88(2):449-57. https://doi.org/10.1007/s00426-023-01865-1 PMID: 37542581.

18. Lin Y, Ding H, Zhang Y. Unisensory and multisensory stroop effects modulate gender differences in verbal and nonverbal emotion perception. J. Speech Lang. Hear. Res. 2021;64(11):4439-57. https://doi.org/10.1044/2021_JSLHR-20-00338 PMID: 34469179.

19. Filkowski MM, Olsen RM, Duda B, Wanger TJ, Sabatinelli D. Sex differences in emotional perception: Meta analysis of divergent activation. Neuroimage. 2017;147:925-33. https://doi.org/10.1016/j.neuroimage.2016.12.016 PMID: 27988321.

20. Themistocleous C, Eckerström M, Kokkinakis D. Identification of mild cognitive impairment from speech in Swedish using deep sequential neural networks. Front. Neurol. 2018;9:975. https://doi.org/10.3389/fneur.2018.00975 PMID: 30498472.

21. Gosztolya G, Vincze V, Tóth L, Pákáski M, Kálmán J, Hoffmann I. Identifying mild cognitive impairment and mild Alzheimer's disease based on spontaneous speech using ASR and linguistic features. Comput. Speech Lang. 2019;53:181-97. https://doi.org/10.1016/j.csl.2018.07.007

22. Zuanetti PA, Silva K, Pontes-Fernandes ÂC, Dornelas R, Fukuda MTH. Characteristics of the emissive prosody of children with Autism Spectrum Disorder. Rev. CEFAC. 2018;20(5):565-72. https://doi.org/10.1590/1982-021620182051718

23. Van Zonneveld L, De Sonneville L, Van Goozen S, Swaab H. Recognition of facial emotion and affective prosody in children at high risk of criminal behavior. J. Int. Neuropsychol. Soc. 2019;25(1):57-64. https://doi.org/10.1017/S1355617718000796 PMID: 30394247.

24. Eskritt M, Zupan B. Emotion perception from vocal cues: Testing the influence of emotion intensity and sex on in-group advantage. Can. J. Exp. Psychol. 2023;77(3):202-11. https://doi.org/10.1037/cep0000310 PMID: 37535514.

25. Martzoukou M, Nasios G, Kosmidis MH, Papadopoulou D. Aging and the perception of affective and linguistic prosody. J. Psycholinguist Res. 2022;51(5):1001-21. https://doi.org/10.1007/s10936-022-09875-7 PMID: 35441951.
 

Submitted date:
04/08/2024

Accepted date:
06/05/2024

66ce1e7ca95395285e3fd113 cefac Articles
1982-0216 (Electronic) 1516-1846 (Printed)
Revista CEFAC ©2024 All rights reserved.

Revista CEFAC

Share this page
Page Sections