Abstract: Systems and methods are described for determining whether to activate a voice activated device based on a speaking cadence of the user. When the user speaks with a first cadence the system may determine that the user does not intend to activate the device and may accordingly not to trigger a voice activated device. When the user speaks with a second cadence the system may determine that the user does wish to trigger the device and may accordingly trigger the voice activated device.

Abstract: Systems and methods are described for determining whether to activate a voice activated device based on a speaking cadence of the user. When the user speaks with a first cadence the system may determine that the user does not intend to activate the device and may accordingly not to trigger a voice activated device. When the user speaks with a second cadence the system may determine that the user does wish to trigger the device and may accordingly trigger the voice activated device.

Abstract: Systems and methods are described for determining whether to activate a voice activated device based on a speaking cadence of the user. When the user speaks with a first cadence the system may determine that the user does not intend to activate the device and may accordingly not to trigger a voice activated device. When the user speaks with a second cadence the system may determine that the user does wish to trigger the device and may accordingly trigger the voice activated device.

Abstract: Systems and methods are described for determining whether to activate a voice activated device based on a speaking cadence of the user. When the user speaks with a first cadence the system may determine that the user does not intend to activate the device and may accordingly not to trigger a voice activated device. When the user speaks with a second cadence the system may determine that the user does wish to trigger the device and may accordingly trigger the voice activated device.

Abstract: Systems and methods are described for determining whether to activate a voice activated device based on a speaking cadence of the user. When the user speaks with a first cadence the system may determine that the user does not intend to activate the device and may accordingly not to trigger a voice activated device. When the user speaks with a second cadence the system may determine that the user does wish to trigger the device and may accordingly trigger the voice activated device.

Abstract: The proposed system defines a predictive real-time Service Level Agreements (SLAs) monitoring system by (a) a detailed analysis of traffic flows with reduced monitor-data flow across network; and (b) a suitable combination of offline and real-time processing of historical and current traffic data. In order to be able to undertake a detailed analysis without significantly impacting the network throughput, the system analyzes the historical traffic patterns of a typical Provider's network to determine a set of critical SLAs. An in-depth analysis of traffic is performed by creating a unique network parent probe for every critical SLA and the parent probe spawns an optimal number of intelligent master and slave probes based on a regionalization procedure. The online overload monitoring system analyzes the gathered data from the master and slave probes to (a) forecast future violations of the SLA under consideration based on multiple forecast models and (b) generate operator SLA violation alarms.

Abstract: The proposed system defines a comprehensive video license distribution system to achieve the zero-reject of requests from subscribers, maximizing the usage of licenses and minimizing the churn rate by (a) using symbolic and numeric features of movies; (b) planning video license distribution of different license kinds to a predictable group of subscribers based on the analysis of subscriber video viewing patterns; (c) exclusive handling of unpredictable behavior of subscribers; (d) the effective trading of favor points; (e) intelligent timing and selection of subscriber specific previews; and (f) the detailed analysis of subscriber complaints.

Abstract: The proposed system defines a predictive real-time Service Level Agreements (SLAs) monitoring system by (a) a detailed analysis of traffic flows with reduced monitor-data flow across network; and (b) a suitable combination of offline and real-time processing of historical and current traffic data. In order to be able to undertake a detailed analysis without significantly impacting the network throughput, the system analyzes the historical traffic patterns of a typical Provider's network to determine a set of critical SLAs. An in-depth analysis of traffic is performed by creating a unique network parent probe for every critical SLA and the parent probe spawns an optimal number of intelligent master and slave probes based on a regionalization procedure. The online overload monitoring system analyzes the gathered data from the master and slave probes to (a) forecast future violations of the SLA under consideration based on multiple forecast models and (b) generate operator SLA violation alarms.