Automatic accent detection using acoustic models

A method, comprising:

• at an electronic device with one or more processors and memory:
• receiving a user input;
• determining a first similarity between a representation of the user input and a first acoustic model of a plurality of acoustic models, wherein the first acoustic model is associated with a first accent of a language;
• determining a second similarity between the representation of the user input and a second acoustic model of the plurality of acoustic models, wherein the second acoustic model is associated with a second accent of the language;
• determining whether the first similarity is greater than the second similarity;
• in accordance with a determination that the first similarity is greater than the second similarity, selecting the first acoustic model;
• in accordance with a determination that the first similarity is not greater than the second similarity, selecting the second acoustic model;
• associating the selected acoustic model with a user profile corresponding to a speaker;
• receiving a second user input from the speaker;
• and determining a representation of the second user input using the selected acoustic model associated with the user profile corresponding to the speaker.

An electronic device, comprising:

• one or more processors;
• a memory;
• and
• one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
• receiving a user input;
• determining a first similarity between a representation of the user input and a first acoustic model of a plurality of acoustic models, wherein the first acoustic model is associated with a first accent of a language;
• determining a second similarity between the representation of the user input and a second acoustic model of the plurality of acoustic models, wherein the second acoustic model is associated with a second accent of the language;
• determining whether the first similarity is greater than the second similarity;
• in accordance with a determination that the first similarity is greater than the second similarity, selecting the first acoustic model;
• in accordance with a determination that the first similarity is not greater than the second similarity, selecting the second acoustic model;
• associating the selected acoustic model with a user profile corresponding to a speaker;
• receiving a second user input from the speaker;
• and
• determining a representation of the second user input using the selected acoustic model associated with the user profile corresponding to the speaker.