In this paper, we detail our approach to studying the vocal characteristics of caregivers in French retirement homes. To achieve this goal, we conducted recordings of 20 professional caregivers across two retirement homes. Using headset microphones connected to smartphones, we were able to capture the caregivers' speech while allowing them complete freedom of movement without compromising sound quality. The recordings consisted of three tasks: reading text, informal interviews, and professional role-play scenarios with a fictitious patient. We processed the recordings using an automatic speech recognition system, which provided word or phone sequences and their corresponding timestamps. Our analysis focused on identifying differences in emotional tone, lexical content, speech rate, fundamental frequency, and intensity between spontaneous speech conditions. Ultimately, our aim is to develop automated training tools that capture the unique vocal characteristics of professional caregivers.