We are currently working on CarHaVoz, an ongoing project that brings together several of the research lines we have been developing in recent years. The project is being carried out in collaboration with Universidad Politécnica de Madrid, Rey Juan Carlos University, Autonomous University of Madrid, and Complutense University of Madrid. The main goal is to explore how voice-based interaction can be integrated into intelligent systems in a natural and efficient way, particularly in contexts where accessibility and continuous monitoring play an important role. By combining techniques from signal processing, machine learning, and human-centered design, the project aims to better understand and leverage voice as a rich source of information in real-world environments.

A key component of the project is the development of HablApp, a mobile application designed to facilitate the remote collection of voice samples. The app allows families to record audio in a simple and flexible way, avoiding the need for frequent in-person sessions. It is structured around six exercises focused on prosodic and phonological features, with users completing one recording per week. After each exercise, recordings can be reviewed to ensure quality before being securely sent to university-hosted servers. This approach not only simplifies the data collection process, but also enables longitudinal studies by making it easier to gather consistent data over time.

Beyond its technical aspects, CarHaVoz highlights the importance of designing tools that adapt to users’ daily routines while still meeting research needs. The combination of intelligent processing and accessible data collection opens the door to applications in areas such as health monitoring, early detection, and assistive technologies. As the project approaches its final stages, it stands as another example of how we approach collaboration and applied research: building solutions that are both technically solid and meaningful in practice.