Abstract: Monitoring a premises may comprise receiving signals from a plurality of devices. One or more spatially static devices of the plurality of devices may be determined based on strengths of the received signals. A user activity pattern may be determined based on changes in strengths of signals received from the spatially static devices. Abnormal user activity may be determined based on the user activity pattern and a strength of at least one signal received from at least one of the spatially static devices.

Abstract: Systems, apparatuses, and methods are described for detection of an item being delivered at a premises. Based on a movement pattern shown in a video captured by a camera associated with a premises, a delivery event may be determined. A notification of the delivery event may be sent to a user device associated with the premises.

Abstract: Methods, systems, and apparatuses for improved speech recognition and transcription of user utterances are described herein. A user utterance may be processed by a speech recognition computing device. One or more acoustic features associated with the user utterance may be used to determine whether one or more actions are to be performed based on a transcription of the user utterance.

Abstract: A voice enabled device can assist a computing device, such as a server, in processing/analyzing a voice input. The voice enabled device can initiate a network communication session and transmit the voice input to the computing device. The computing device can classify the voice input as a type of communication session (e.g., conversation, etc. . . . ). Based on the type of communication session, the computing device can either remain in communication with the voice enabled device and continue to process voice input or terminate the communication after instructing the voice enabled device to process the voice input.

Abstract: Methods, apparatuses, and systems are described for allocating a plurality of frequencies for use by a plurality of network devices. Measurement data associated with the plurality of network devices may be used to determine interference data. The interference data may be used to determine an allocation of the plurality of frequencies for use by the plurality of network devices.

Abstract: A camera system may automatically identify high frequency motion regions in a field of view of the camera system. Analysis of motion events detected at different regions of a scene in the field of view, may be performed. Similar events frequently occurring at a certain region may be recorded/accumulated and compared to a threshold. Regions with high frequency activity may be determined and a user may be notified. If the user is not interested in events within the high activity regions, the regions may be ignored and notifications to the user may cease. The camera system may determine specific actions/events occurring in a region, such as a person approaching or leaving a home.

Abstract: Methods, systems, and apparatuses for improved speech recognition and transcription of user utterances are described herein. A user utterance may be processed by a speech recognition computing device. One or more acoustic features associated with the user utterance may be used to determine whether one or more actions are to be performed based on a transcription of the user utterance.

Abstract: Methods, systems, and apparatuses for predicting an end of a command in a voice recognition input are described herein. The system may receive data comprising a voice input. The system may receive a signal comprising a voice input. The system may detect, in the voice input, data that is associated with a first portion of a command. The system may predict, based on the first portion and while the voice input is being received, a second portion of the command. The prediction may be generated by a machine learning algorithm that is trained based at least in part on historical data comprising user input data. The system may cause execution of the command, based on the first portion and the predicted second portion, prior to an end of the voice input.

Abstract: Methods, systems, and apparatuses for managing a wireless network are described herein. A wireless network may include a gateway device, an access point, and a group of client devices. An analytics engine may determine a signal characteristic data for a client device, which may indicate network telemetry data for each of the client devices or associated locations during a time period. The analytics engine may utilize a trained classifier to determine that a signal characteristic indicated by the signal characteristic data for a client device satisfies a threshold.

Abstract: A camera system may automatically identify high frequency motion regions in a field of view of the camera system. Analysis of motion events detected at different regions of a scene in the field of view, may be performed. Similar events frequently occurring at a certain region may be recorded/accumulated and compared to a threshold. Regions with high frequency activity may be determined and a user may be notified. If the user is not interested in events within the high activity regions, the regions may be ignored and notifications to the user may cease. The camera system may determine specific actions/events occurring in a region, such as a person approaching or leaving a home.

Abstract: Systems, apparatuses, and methods are described for presence detection of a wireless device in a sensing region. Communication parameters determined by a computing device over one or more periods may be used to generate criteria for determining the occurrence of enter events or leave events. The criteria may comprise, for values of one or more communication parameters, rates of change associated with movement into or out of the sensing region. The criteria may be compared against subsequent data associated with the communication parameters to determine if an enter event or a leave event has occurred.

Abstract: A voice enabled device can assist a computing device, such as a server, in processing/analyzing a voice input. The voice enabled device can initiate a network communication session and transmit the voice input to the computing device. The computing device can classify the voice input as a type of communication session (e.g., conversation, etc. . . . ). Based on the type of communication session, the computing device can either remain in communication with the voice enabled device and continue to process voice input or terminate the communication after instructing the voice enabled device to process the voice input.

Abstract: A device may be configured to determine whether an audio file is a first type of audio file that is capable of being processed to recognize the voice query based on a characteristic of the audio file itself or a second type of audio file that may require speech recognition processing in order to recognize the voice query associated with the audio file. In determining whether the audio file is a first type of audio file or a second type of audio file, a query filter associated with the device may be configured to access one or more guidance queries. Using the one or more guidance queries, the device may classify the audio file as a first type of audio file or a second type of audio file based on receiving only a portion of the audio file, thereby improving the speed at which the audio file can be processed.

Abstract: Methods, systems, and apparatuses for managing a wireless network are described herein. A wireless network may include a gateway device, an access point, and a group of client devices. An analytics engine may determine a signal characteristic data for a client device, which may indicate network telemetry data for each of the client devices or associated locations during a time period. The analytics engine may utilize a trained classifier to determine that a signal characteristic indicated by the signal characteristic data for a client device satisfies a threshold.

Abstract: Systems, apparatuses, and methods are described for presence detection of a wireless device in a sensing region. Communication parameters determined by a computing device over one or more periods may be used to generate criteria for determining the occurrence of enter events or leave events. The criteria may comprise, for values of one or more communication parameters, rates of change associated with movement into or out of the sensing region. The criteria may be compared against subsequent data associated with the communication parameters to determine if an enter event or a leave event has occurred.

Abstract: Methods, systems, and apparatuses for predicting an end of a command in a voice recognition input are described herein. The system may receive data comprising a voice input. The system may receive a signal comprising a voice input. The system may detect, in the voice input, data that is associated with a first portion of a command. The system may predict, based on the first portion and while the voice input is being received, a second portion of the command. The prediction may be generated by a machine learning algorithm that is trained based at least in part on historical data comprising user input data. The system may cause execution of the command, based on the first portion and the predicted second portion, prior to an end of the voice input.

Abstract: Methods, systems, and apparatuses for improved speech recognition and transcription of user utterances are described herein. User utterances may be processed by a speech recognition computing device as well as an acoustic model. The acoustic model may be trained using historical user utterance data and machine learning techniques. The acoustic model may be used to determine whether a transcription determined by the speech recognition computing device should be overridden with an updated transcription.

Abstract: A device may be configured to determine whether an audio file is a first type of audio file that is capable of being processed to recognize the voice query based on a characteristic of the audio file itself or a second type of audio file that may require speech recognition processing in order to recognize the voice query associated with the audio file. In determining whether the audio file is a first type of audio file or a second type of audio file, a query filter associated with the device may be configured to access one or more guidance queries. Using the one or more guidance queries, the device may classify the audio file as a first type of audio file or a second type of audio file based on receiving only a portion of the audio file, thereby improving the speed at which the audio file can be processed.