Abstract: Methods and apparatuses are described for generating and displaying custom-selected content for a mobile application. A mobile device captures a request to launch an application and determines content cards eligible to be displayed. A user-specific content classification model is generated for selecting one of the content cards to be displayed, where the mobile device identifies historical usage characteristics and transmits the historical usage characteristics to a server, which generates the user-specific content classification model based upon the historical usage characteristics and transmits the user-specific content classification model to the mobile device. The mobile device executes the user-specific content classification model to select one or more content cards to be displayed and launches the application to display the selected content cards.

Abstract: Methods and apparatuses are described for automated execution of computer software based upon determined empathy of a communication participant. A server captures a digitized voice segment from a remote computing device. The server analyzes vocal cues of the digitized voice segment to generate a voice empathy score. The server converts speech in the digitized voice segment into text and determines empathy keywords in the text to generate a keyword empathy score. The server captures digitized images of the participant's face and analyzes physical expressions of the face to identify emotions and generate a facial empathy score. The server generates an overall empathy confidence score for the communication participant based upon the voice empathy score, the keyword empathy score, and the facial empathy score. The server generates recommended changes for the user based upon the overall empathy confidence score and executes a software application that displays the recommended changes.

Abstract: Methods and apparatuses are described for automated execution of computer software based upon determined empathy of a communication participant. A server captures a digitized voice segment from a remote computing device. The server analyzes vocal cues of the digitized voice segment to generate a voice empathy score. The server converts speech in the digitized voice segment into text and determines empathy keywords in the text to generate a keyword empathy score. The server captures digitized images of the participant's face and analyzes physical expressions of the face to identify emotions and generate a facial empathy score. The server generates an overall empathy confidence score for the communication participant based upon the voice empathy score, the keyword empathy score, and the facial empathy score. The server generates recommended changes for the user based upon the overall empathy confidence score and executes a software application that displays the recommended changes.