Comparative Assessment of Embedded Devices for Natural Language Processing for Biomedical Applications in Spanish

In this work, a comparative evaluation of embedded devices for Natural Language Processing (NLP) in biomedical applications in Spanish is carried out, specifically in text-to-speech and speech-to-text algorithms. Several embedded devices have been selected to achieve this, including Jetson Nano, Raspberry Pi (4B, 400, and 3B+), and Latte Panda. This analysis focuses on key aspects such as execution time, CPU usage percentage, and RAM usage percentage. These criteria will allow us to compare the evaluated devices' performance and determine the most suitable NLP in biomedical applications in Spanish. This benchmarking is expected to provide valuable information to facilitate the selection of devices in future projects and applications within the NLP. This work will allow professionals and developers to make informed decisions and optimize their resources when implementing NLP solutions in the biomedical field in Spanish.