Abstract: Techniques are described here for prompt generation. An example method can include determining, using a first machine learning model, a characteristic of an item based at least in part on a textual description of the item. The method can further include receiving a first input indicating a qualifier describing a theme for the image. The method can further include generating, using the first machine learning model, a prompt for a second machine learning model based at least in part on the characteristic and the background. The method can further include generating, using the second machine learning model, the image based at least in part on the prompt, the image associated with the theme and showing the item and the background.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for predicting an emotion based on speech and text derived from the speech. An example method includes capturing speech and generating hidden vectors based on the speech and text derived from the speech. The example method further includes generating a word aligned hidden vector based on the speech hidden vector and text hidden vector. The example method further includes generating a hidden vector based on the word aligned hidden vector and the text hidden vector. The example method further includes, after further processing of the final vector, generating one or more probabilities corresponding to one or more emotions. The example method finally includes determining a next action based on the generated one or more probabilities corresponding to one or more emotions.