End of query detection

A system comprising:

• one or more computers;
• and
• one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
• receiving audio data that corresponds to an utterance spoken by a user;
• applying, to the audio data, an end of query model that (i) is configured to determine a confidence score that reflects a likelihood that the utterance is a complete utterance and (ii) was trained using audio data from complete utterances and from incomplete utterances;
• based on applying the end of query model that (i) is configured to determine the confidence score that reflects the likelihood that the utterance is a complete utterance and (ii) was trained using the audio data from the complete utterances and from the incomplete utterances, determining the confidence score that reflects a likelihood that the utterance is a complete utterance;
• comparing the confidence score that reflects the likelihood that the utterance is a complete utterance to a confidence score threshold;
• based on comparing the confidence score that reflects the likelihood that the utterance is a complete utterance to the confidence score threshold, determining whether the utterance is likely complete or likely incomplete;
• and
• based on determining whether the utterance is likely complete or likely incomplete, providing, for output, an instruction to (i) maintain a microphone that is receiving the utterance in an active state or (ii) deactivate the microphone that is receiving the utterance.

A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:

• receiving audio data that corresponds to an utterance spoken by a user;
• applying, to the audio data, an end of query model that (i) is configured to determine a confidence score that reflects a likelihood that the utterance is a complete utterance and (ii) was trained using audio data from complete utterances and from incomplete utterances;
• based on applying the end of query model that (i) is configured to determine the confidence score that reflects the likelihood that the utterance is a complete utterance and (ii) was trained using the audio data from the complete utterances and from the incomplete utterances, determining the confidence score that reflects a likelihood that the utterance is a complete utterance;
• comparing the confidence score that reflects the likelihood that the utterance is a complete utterance to a confidence score threshold;
• based on comparing the confidence score that reflects the likelihood that the utterance is a complete utterance to the confidence score threshold, determining whether the utterance is likely complete or likely incomplete;
• and
• based on determining whether the utterance is likely complete or likely incomplete, providing, for output, an instruction to (i) maintain a microphone that is receiving the utterance in an active state or (ii) deactivate the microphone that is receiving the utterance.