Abstract: Systems, apparatuses, and methods are described for generating simulated synthetic voice samples for use in training voice recognition models. The simulated synthetic voice samples may be diversified and in large quantities, in order to train the voice recognition models to handle a large variety of possible voice types and commands. These voice samples may be generated based on simulated user profiles indicating different types of speaker characteristics and words. The generated synthetic voice samples mimic realist human inputs and voice traffic, and may be used to test these voice recognition models for their performance in various situations. Based on the testing, these models may be efficiently retrained to improve their performance in a wide variety of conditions.

Abstract: A computer-implemented method for supporting disease diagnosis is provided that includes: a) generating and storing a list of user-selected broad symptoms; b) using the list of user-selected broad symptoms to generate and store a list of related disease presentations or diseases; c) using at least one machine knowledge system to identify a collection of disease-specific symptoms that are related to the disease presentations or diseases of the list of related disease presentations or diseases; d) presenting to the user disease-specific symptoms belonging to the collection of disease-specific symptoms for associated user input; e) using the user input associated with the disease-specific symptoms to determine matching scores for diseases presentations or diseases of the list of related disease presentations or diseases; and f) using the matching scores for the diseases presentations or diseases to present to the user rankings or groupings for diseases corresponding to the of the list of related disease presenta