Abstract

Language barriers in health care are a major obstacle to national and global sustainable development goals for public health, health equality, and integration. Interpreters in healthcare is a non-regulated industry, with less than 1 % of the interpreters being certified in medical interpretation in Sweden. Often the interpreter knows the patient, making it difficult for the patient to have a private conversation with the doctor. In this talk, we will look at how modern NLP and speech technology can be used to create a secure and private interpretation system. We will go through our challenges in making such a system with the first version designed to help the Ukrainian refugees seeking healthcare across the EU. We will particularly look into dealing with noisy environments and biases in open-source datasets.

Alma Lund

Machine Learning Engineer @ Mabel AI, Syntronic

Alma Lund is a machine learning engineer at Mabel AI, where she brings the AI models closer to the people who need them the most. She has a background in engineering physics and computational sciences from Chalmers University of Technology and has a strong interest in creating frameworks for sustainable and inclusive AI.

Marina Delatorre

Data Scientist @ Mabel AI

Marina Delatorre has a background as a psychologist and a PhD in Psychology. She currently works as a data scientist at Mabel AI. She uses her expertise in psychology to understand the nuances of communication in healthcare settings and ensure that speech recognition and translation models can capture the diversity of environments and people who use them.