Creating an Adaptive Voice and Language Model Capable of Emotional Response and Self-Profiling to Emulate User Personality

Palabras clave: adaptive voice model, psychological profiling, natural language processing (nlp), emotionally intelligent systems

Resumen

This work aims to show a cheap alternative of implementing an adaptive voice and language model, which has the opportunity not only react to the interlocutors’ emotions but also adapt the personality of the bot to the personality of the user. Through moderated Framework and a feedback loop process the author explores the possibility of a system model. The conversational agent of this framework uses Natural Language Process (NLP) technique for the psychological profiling in order to be self-directed and self-aware. Moreover, this system can be kept current with successive activity sequences with gradual enhancement in the identification of the user personality, which determines the manner in which the model interacts with the user. The author also presents a plan on how to design such a model supported by theory, method, and feasibility and possible uses

Descargas

La descarga de datos todavía no está disponible.

Citas

Bilquise, G., Ibrahim, S., & Shaalan, K. (2022). Emotionally intelligent chatbots: A systematic literature review. Human Behavior and Emerging Technologies, 2022

https://doi.org/10.1155/2022/9601630

Chakriswaran, P., Vincent, D. R., Srinivasan, K., & Sharma, V. (2019). Emotion AI-driven sentiment analysis: A survey, future research directions, and open issues. Applied Sciences. https://doi.org/10.3390/app9245462

Chen, Y., & Xiao, Y. (2024). Recent advancement of emotion cognition in large language models. _arXiv preprint,_arXiv:2409.13354. https://doi.org/10.48550/arXiv.2409.13354

Dolgikh, S. (2024). Self-awareness in natural and artificial intelligent systems: A unified information-based approach. Evolutionary Intelligence. https://doi.org/10.1007/s12065-024-00974-z

Döring, N., Le, T. D., Vowels, L. M., & Vowels, M. J. (2024). The Impact of Artificial Intelligence on Human Sexuality: A Five-Year Literature Review 2020–2024. Current Sexual Health Reports. https://doi.org/10.1007/s11930-024-00397-y

Ðula, I., Berberena, T., & Keplinger, K. (2024). From challenges to opportunities: navigating the human response to automated agents in the workplace. Humanities and Social Sciences Communications, 11(1). https://doi.org/10.1057/s41599-024-03962-x

Guo, Y., Smith, A. B., & Johnson, M. L. (2024). Personality prediction from task-oriented and open-domain human–machine dialogues. _Scientific Reports, 14_(1), Article 53989. https://doi.org/10.1038/s41598-024-53989-y

Kossack, S., & Unger, H. (2023). Emotion-aware chatbots: Understanding, reacting, and adapting to human emotions. In _Advances in Human-Computer Interaction_ (pp. 123–145). Springer. https://doi.org/10.1007/978-3-031-61418-7_8

Kubjana, L., Adekunle, P., & Aigbavboa, C. (2024). Analyzing the Impact of Emotional Intelligence on Leadership in Construction 4.0. Proceedings of the Future Technologies Conference. https://doi.org/10.1007/978-3-031-73128-0_30

Le, U. P. N., Nguyen, A. T. T., Nguyen, A. V., Huynh, V. K., Bui, C. T. L., & Nguyen (2024). How do emotional support and emotional exhaustion affect the relationship between incivility and students’ subjective well-being? In _Disruptive Technology and Business Continuity: Proceedings of the 5th International Conference on Business (ICB 2023)_(pp. 237–248). Springer. https://doi.org/10.1007/978-981-97-5452-6_18

Lee, J., Park, S., & Kim, H. (2023). A paradigm shift from 'human writing' to 'machine generation' in personality test development. _Journal of Business and Psychology, 38_(1), 45–62. https://doi.org/10.1007/s10869-022-09864-6

Fan, X., Luo, Y., Zhao, Y., & Li, J. (2017). Do we need emotionally intelligent artificial agents? In _International Conference on Human-Computer Interaction_ (pp. 194–205). Springer. https://doi.org/10.1007/978-3-319-67401-8_15

Lee, G. H., Lee, K. J., Jeong, B., & Kim, T. K. (2024). Developing Personalized Marketing Service Using Generative AI. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3361946

Flores, H. I. O., & Luna, A. (2024). AI for psychological profiles: Advances, challenges, and future directions. _Ciencia Latina Revista Científica Multidisciplinar, 8_(3), 10592–10609. https://doi.org/10.37811/cl_rcm.v8i3.12221

Flores, H. I. O. (2023). Human computer interaction’s insights into the recognition of love: A comprehensive framework. _Tierra Infinita, 9_(1), 228–245.

https://doi.org/10.32645/26028131.1254

Llanes, J., García-Sánchez, F., Moreno-Izquierdo, M., & Torres-Ramos, R. (2024). Developing conversational virtual humans for social emotion elicitation. _Expert Systems with Applications, 231,_ Article 122647. https://doi.org/10.1016/j.eswa.2024.122647

Ma, L., Chen, Y., & Zhao, X. (2024). Personality-enhanced emotion generation modeling for dialogue systems. _Cognitive Computation, 16_(1), 45–62. https://doi.org/10.1007/s12559-023-10204-w

López, C., & Rivera, M. (2023). Control de Enfermería en Personas con Diabetes Gestacional en Embarazadas de la Argentina. Revista Veritas De Difusão Científica, 4(2), 88–101. https://doi.org/10.61616/rvdc.v4i2.48

León Mazón, K. M., & Naranjo Corría, R. (2024). Narración de Cuentos para el Desarrollo de la Habilidad de hablar Inglés en Estudiantes de Educación Básica Secundaria. Estudios Y Perspectivas Revista Científica Y Académica , 4(1), 2330–2349. https://doi.org/10.61384/r.c.a.v4i1.184

Ruiz Díaz Benítez , J. R. (2023). Design of a reference architecture in intelligent warehouse supply logistics through the use of Industry 4.0 technologies. Case of retail Warehouses in the city of Pilar. Revista Veritas De Difusão Científica, 4(2), 120–136. https://doi.org/10.61616/rvdc.v4i2.50

Fernández C., F. (2024). Determinación De Erodabilidad En Áreas De Influencia Cuenca Poopo Región Andina De Bolivia. Horizonte Académico, 4(4), 63–78. Recuperado a partir de https://horizonteacademico.org/index.php/horizonte/article/view/19

Medina Nolasco, E. K., Mendoza Buleje, E. R., Vilca Apaza, G. R., Mamani Fernández, N. N., & Alfaro Campos, K. (2024). Tamizaje de cáncer de cuello uterino en mujeres de una región Andina del Perú. Arandu UTIC, 11(1), 50–63. https://doi.org/10.69639/arandu.v11i1.177

Da Silva Santos , F., & López Vargas , R. (2020). Efecto del Estrés en la Función Inmune en Pacientes con Enfermedades Autoinmunes: una Revisión de Estudios Latinoamericanos. Revista Científica De Salud Y Desarrollo Humano, 1(1), 46–59. https://doi.org/10.61368/r.s.d.h.v1i1.9

Matsumoto, S., Washburn, A., & Riek, L. D. (2022). A framework to explore proximate human-robot coordination. _ACM Transactions on Human-Robot Interaction (THRI, 11_(3), Article 32, 1–34. https://doi.org/10.1145/3526101

Müller, L., Mattke, J., Maier, C., & Weitzel, T. (2019). Chatbot acceptance: A latent profile analysis on individuals' trust in conversational agents. Proceedings of the 2019 ACM SIGCHI Conference, 1-5. https://doi.org/10.1145/3322385.3322392

Ocaña, M., Villamarín, A., Chumaña, J., Narváez, M., Guallichico, G., Luna A.,(2023a). Artificial Intelligence in the Detection of Autism Spectrum Disorders (ASD): A Systematic Review. In Intelligent Vision and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-71388-0_3

Ocaña, M., Luna, A., Guallichico, G. (2023b). Aplicaciones móviles en el desarrollo del lenguaje Un enfoque comparativo entre padres y educadores. Revista ALPHA OMEGA. Retrieved From: https://link.springer.com/chapter/10.1007/978-3-030-68083-1_30

Ocaña, M., Mejía, R., Larrea, C., Analuisa, C. (2021a). Informal learning in social networks during the COVID-19 pandemic: an empirical analysis. Artificial Intelligence. Retrieved from: https://link.springer.com/chapter/10.1007/978-3-030-68083-1_30

Ocaña, M., Mejía, R., Larrea, C., Cruz, E., Santana, L. (2021b). Investigating the importance of student location and time spent online in academic performance and self-regulation. Artificial Intelligence. Retrieved from: https://link.springer.com/chapter/10.1007/978-3-030-68083-1_31

Ocaña, M., Luna, A., Jeada, V.Y., Carrillo, H.C. (2023c). Are VR and AR really viable in military education?: A position paper. Advances in Computing. https://doi.org/10.1007/978-981-19-7689-6_15

Ocaña, M., Almeida, E., Albán, S. (2021c). How Did Children Learn in an Online Course During Lockdown?: A Piagetian Approximation. XV Multidisciplinary International Congress. Retrieved from: https://link.springer.com/chapter/10.1007/978-3-030-96046-9_20

Pellert, M., Lechner, C. M., & Strohmaier, M. (2024). AI psychometrics: Assessing the psychological profiles of large language models through psychometric inventories. _Perspectives on Psychological Science, 19_(5). https://doi.org/10.1177/17456916231214460

Poggi I., & Pelachaud C.(2000). Emotion and personality in a conversational agent. In J. Cassell (Ed.), Embodied conversational agents (pp. 189-219). MIT Press.

https://doi.org/10.7551/mitpress/2697.003.0008. Psychometric profiling of individuals using Twitter profiles: A psychological natural language processing-based approach. _Concurrency and Computation: Practice and Experience, 34_(15), Article e7029. https://doi.org/10.1002/cpe.7029

Romero, P., Fitz, S., & Nakatsuma, T. (2024). Do GPT language models suffer from split personality disorder? The advent of substrate-free psychometrics. _arXiv preprint,_ arXiv:2408.07377. https://doi.org/10.48550/arXiv.2408.07377

Saha, R., Neogi, D., & Chaudhuri, R. (2024). L-BFGS optimization-based human body posture rectification—A smart interaction for computer-guided workout. In _Proceedings of the 12th International Conference on Soft Computing for Problem Solving_ (pp. 61–76). Springer. https://doi.org/10.1007/978-981-97-3292-0_4

Sikström, S., Johansson, B., & Larsson, M. (2024). Personality in just a few words: Assessment using natural language processing. _SSRN Electronic Journal._ https://doi.org/10.2139/ssrn.4933048

Sonlu, S., Güdükbay, U., & Durupinar, F. (2021). A conversational agent framework with multi-modal personality expression. _ACM Transactions on Graphics (TOG, 40_(1), Article 7, 1–16. https://doi.org/10.1145/3439795

Velagaleti, S. B., Choukaier, D., & Nuthakki, R. (2024). Empathetic Algorithms: The Role of AI in Understanding and Enhancing Human Emotional Intelligence. Journal of Electrical and Computer Engineering. Retrieved from:

https://www.proquest.com/openview/ebdccf03c2979c138444061f01dd87df/1?pq-origsite=gscholar&cbl=4433095

Wen, Q., Li, J., & Xu, P. (2024). Personality-affected emotion generation in dialog systems. _Proceedings of the ACM on Interactive, Mobile, Wearable, and Ubiquitous Technologies, 8_(1), Article 7, 1–24. https://doi.org/10.48550/arXiv.2404.07229

Yadav, A., & Vishwakarma, D. K. (2020). Sentiment analysis using deep learning architectures: A review. Artificial Intelligence Review. Retrieved from Springer. https://doi.org/10.1007/s10462-019-09794-5

Yu, J., Dickinger, A., So, K. K. F., & Egger, R. (2024). Artificial intelligence-generated virtual influencer: Examining the effects of emotional display on user engagement. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2023.103560

Vega Alvarez, E., & Huang Chang, Y. (2024). Blended Learning, and Its Impact on English Speaking Skills in Pronunciation in Group 11-4 of Liceo de Santo Domingo, I Quarter 2024. Ciencia Y Reflexión, 3(2), 159–173. https://doi.org/10.70747/cr.v3i2.18

Chavarría Hidalgo, C. (2024). Calculation of productive capacity: From theory to practice. Ciencia Y Reflexión, 3(2), 194–214. https://doi.org/10.70747/cr.v3i2.20

Agrela Rodrigues, F. de A., Moreira da Silveira, F., Moreira de Lima, M. R., & Pinto Uchôa , K. S. (2024). Identificando a Inteligência em Crianças: Traços Físicos e Comportamentais. Ciencia Y Reflexión, 3(2), 21–51. https://doi.org/10.70747/cr.v3i2.5

Publicado
2025-02-14
Cómo citar
Ocana Flores , H. I. (2025). Creating an Adaptive Voice and Language Model Capable of Emotional Response and Self-Profiling to Emulate User Personality. Ciencia Latina Revista Científica Multidisciplinar, 9(1), 3454-3471. https://doi.org/10.37811/cl_rcm.v9i1.16093
Sección
Ciencias y Tecnologías