Detalhes bibliográficos
| Ano de defesa: |
2023 |
| Autor(a) principal: |
Roman, Mateus Klein
 |
| Orientador(a): |
De Marchi, Ana Carolina Bertoletti
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| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade de Passo Fundo
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| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Computação Aplicada
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| Departamento: |
Instituto de Tecnologia – ITEC
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://tede.upf.br:8080/jspui/handle/tede/2622
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Resumo: |
The increasing development and improvement of computational technologies facilitated its access for different audiences, in the most varied applications. Between the applications on the rise are conversational agents, commonly known such as chatbots and/or voicebots, increasingly popular due to the features they add to existing software and hardware. The aim of these agents is to facilitate the user interaction with technology, as they are conversation-based multimodal. However, in the development of digital health solutions, as well as in other areas, it is essential to consider the aspects that enhance your use, especially long term. To achieve this, concepts such as the experience of user and how to make the solution more humanized must be analyzed. Therefore in mind, the objective of this study is to propose an agent design model multimodal conversational programs aimed at inserting records and monitoring health data. The model presents four characteristics necessary for the satisfactory development of agents, with social intelligence, style of communication, anthropomorphic characteristics and technological mapping. The model was used to develop two agent applications conversational: by text and by voice. The applications were incorporated into a m-Health app. For the evaluation, an experimental study was conducted with users. Users were divided into three groups: control group, which used the digital health application without conversational agents; voice group, which used the application with voice data entry; and, finally, textual group, which used the conversational text agent to perform recording and monitoring. You results demonstrated that the developed model presented user experience satisfactory in the conversational solution by voice and text, with evaluation predominantly positive when using voice. It is expected that the model can contribute to the creation of conversational agents in digital health applications, focused on enhancing the user experience. |
