Abstract: Systems and methods for food logging are disclosed herein. In some embodiments, a food logging system converts text inputs that describe an instance of dietary intake in the form of unstructured text to a detailed description of the nutritional content of the instance in the form of structured data. The food logging system can consist of five structural components, each of which performs a specific task. Each food logging system component is associated with a defined resource that provides information and directives on how the associated component is to perform its designated task. Together, these components and associated resources constitute an apparatus that enables users to carry out detailed and accurate food logging, simply by providing textual descriptions of their dietary intake.

Abstract: A method comprises: receiving an image of a real-world environment; using a machine learning classifier, classifying the image to produce classifications associated with acoustic presets for an acoustic environment simulation, the acoustic presets each including acoustic parameters that represent sound reverberation; and selecting an acoustic preset among the acoustic presets based on the classifications.