Behavior detection
A system includes a microphone and a computing device including a processor and a memory. The memory stores instructions executable by the processor to identify a word sequence in audio input received from the microphone, to determine a behavior pattern from the word sequence, and to report the behavior pattern to a remote server at a specified time.
1 . A system, comprising:
a microphone;
a computing device including a processor and a memory, the memory storing instructions executable by the processor to:
identify a word sequence spoken by an individual in audio input received from the microphone;
determine a behavior pattern for the individual from the word sequence;
determine a tone for a plurality of words in the word sequence;
determine whether the behavior pattern is detected upon determining that the tone of the plurality of words exceeds a predetermined threshold stored in the memory;
determine an identity of the individual based upon one or more words spoken in the word sequence; and
in response to determining the behavior pattern is detected, report the behavior pattern, the one or more words in the word sequence associated with the identity of the individual, and a location of the individual to a remote server.
2 . The system of claim 1 , the instructions further including instructions to:
provide the audio input as input to a machine learning program; and
receive the behavior pattern as output from the machine learning program.
3 . The system of claim 2 , the instructions further including instructions to provide at least one of the location, an identifier of the individual, or a time of day in the input to the machine learning program.
4 . The system of claim 2 , the instructions further including instructions to receive an update to the machine learning program from the remote server.
5 . The system of claim 1 , the instructions further including instructions to determine the behavior pattern from a volume, a pitch, a tone in the word sequence, or the location at which the audio input was received.
6 . The system of claim 1 , the instructions further including instructions to identify the behavior pattern based on identifying the individual from the word sequence.
7 . The system of claim 6 , the instructions further including instructions to identify the behavior pattern based on identifying two individuals from the word sequence.
8 . The system of claim 1 , the instructions further including instructions to report the behavior pattern via a communication network to the remote server.
9 . The system of claim 1 , the instructions further including instructions to store an individual profile and identify the individual based on the audio input and the individual profile, wherein the individual profile includes at least one of an identifier, vocabulary characteristic, syntax characteristic, voice attributes, and audio data including an individual's voice.
10 . The system of claim 9 , the instructions further including instructions to determine the behavior pattern based at least in part on the individual profile.
11 . A method, comprising:
identifying a word sequence spoken by an individual in audio input received from a microphone;
determining a behavior pattern for the individual from the word sequence;
determining a tone for a plurality of words in the word sequence;
determining whether the behavior pattern is detected upon determining that the tone of the plurality of words exceeds a predetermined threshold;
determining an identity of the individual based upon one or more words spoken in the word sequence; and
in response to determining the behavior pattern is detected, reporting the behavior pattern, the one or more words in the word sequence associated with the identity of the individual, and a location of the individual to a remote server.
12 . The method of claim 11 , further comprising:
providing the audio input as input to a machine learning program; and
receiving the behavior pattern as output from the machine learning program.
13 . The method of claim 12 , further comprising providing at least one of the location, an identifier of the individual, or a time of day in the input to the machine learning program.
14 . The method of claim 12 , further comprising receiving an update to the machine learning program from the remote server.
15 . The method of claim 11 , further comprising determining the behavior pattern from a volume, a pitch, a tone in the word sequence, or the location at which the audio input was received.
16 . The method of claim 11 , further comprising identifying the behavior pattern based on identifying the individual from the word sequence.
17 . The method of claim 16 , further comprising identifying the behavior pattern based on identifying two individuals from the word sequence.
18 . The method of claim 11 , further comprising reporting the behavior pattern via a communication network to the remote server.
19 . The method of claim 11 , further comprising storing an individual profile and identify the individual based on the audio input and the individual profile, wherein the individual profile includes at least one of an identifier, vocabulary characteristic, syntax characteristic, voice attributes, and audio data including an individual's voice.
20 . The method of claim 19 , further comprising determining the behavior pattern based at least in part on the individual profile.