Modular deep learning model

A method of labeling sounds using a modular deep learning model, the method comprising:

• receiving acoustic information comprising speech from a user;
• determining a context for the acoustic information;
• converting the acoustic information into acoustic features;
• activating a sub-module associated with the context to perform calculations when the modular deep learning model is processing the acoustic features;
• inputting the acoustic features into the modular deep learning model;
• and
• generating label data for the acoustic information by processing the acoustic features using the modular deep learning model.

A computer-storage media comprising computer-executable instructions embodied thereon that when executed by a computing device cause the computer device to perform a method of labeling sounds using a modular deep learning model, the method comprising:

• receiving acoustic information comprising speech from a user;
• converting the acoustic information into acoustic features;
• determining, for a first context class, a first context for the acoustic information;
• selecting a first sub-module from a plurality of sub-modules associated with the first context class;
• activating the first sub-module associated with the first context to perform calculations when the modular deep learning model is processing the acoustic features, wherein the non-selected sub-modules associated with the first context class do not perform calculations within the modular deep learning model when the first sub-module is activated;
• inputting the acoustic features into the modular deep learning model;
• and
• generating label data for the acoustic information by processing the acoustic features using the modular deep learning model.