Abstract: Disclosed herein are techniques for diagnosing health conditions of a subject based on the subject's vocal biomarkers and health records, including techniques for generating one or more models (e.g., machine learning models) trained to predict a health condition in a subject. One or more techniques may include receiving speech data and health record data, analyzing the received speech data and health record data using one or more trained models, and outputting the prediction of whether the subject has any of the one or more health conditions.

Abstract: Apparatuses, systems, methods, and computer program products are disclosed for techniques for speech language model training and application. An apparatus includes a processor and a memory coupled with the processor. The memory stores code that is executable by the processor to train a first speech model in a first language, the first speech model used to determine one or more characteristics of speech data that is indicative of MCI, train a second speech model for use in a second language using at least a portion of the first speech model trained in the first language, apply the second speech model trained for use in the second language to speech data for a user captured in the second language, and determine, based on output from the second speech model trained for use in the second language, an assessment of MCI for the user.