How can we leverage biometric data such as voice or facial expressions to identify users’ emotional states quickly and accurately, based on pre-established profiles?
In the first phase of the project, an application was developed to identify whether a user had a predominantly positive or negative emotional profile, using a structured battery of questions. While effective, this approach was sometimes lengthy and somewhat rigid. Nonetheless, it enabled the training of an initial model and the construction of a solid base of emotional profiles. Now, using that knowledge as a foundation, the aim is to evolve the system into a more agile and interactive solution, integrating biometric technologies to capture emotional information without relying solely on written responses or traditional forms.
The objective is to design an interactive solution that, drawing on the previously defined emotional profiles and the trained model, uses biometric data—such as voice and facial expressions—to identify a user’s emotional state in a fast and non-intrusive manner. The new tool should replace or complement the previous questionnaire, allowing perceptions to be captured with greater fluidity, naturalness and precision. It is essential that the system integrates advanced emotional recognition technologies, remains consistent with the existing foundation, and adapts to different types of real-time interaction, without compromising the rigour of the results.
The new solution will enable the emotional state and experience of users to be measured more immediately, smoothly, and adaptively, reducing the cognitive burden imposed by long and repetitive questions. This will foster more natural interactions, lower user resistance, and increase the reliability of the data collected. Furthermore, by incorporating biometrics, the system’s potential for use in more dynamic and automated contexts will be expanded, paving the way for continuous and proactive evaluation of the organisational environment. This evolution will enhance the system’s practical utility and its scalability to other sectors or applications.
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