Methods for natural language model training in natural language understanding (nlu) systems

A computer-implemented method, comprising:

• receiving a voice query;
• determining that the voice query comprises audio input of a user belonging to a grouping classification;
• determining the voice query comprises an obsequious portion comprising an obsequious expression;
• identifying a non-obsequious portion of the voice query, wherein the obsequious portion of the voice query does not describe the non-obsequious portion of the voice query;
• and
• based at least in part on determining that the received voice query comprises the audio input of the user that belongs to the grouping classification and that the received voice query comprises the obsequious portion, causing output of data in relation to the voice query.

A computer-implemented system, comprising:

• control circuitry;
• and
• input/output circuitry configured to:
• receive a voice query;
• wherein the control circuitry is configured to:
• determine that the voice query comprises audio input of a user belonging to a grouping classification;
• determine the voice query comprises an obsequious portion comprising an obsequious expression;
• identify a non-obsequious portion of the voice query, wherein the obsequious portion of the voice query does not describe the non-obsequious portion of the voice query;
• and
• based at least in part on determining that the received voice query comprises the audio input of the user that belongs to the grouping classification and that the received voice query comprises the obsequious portion, cause output of data in relation to the voice query.