Abstract: A system may allow for generic end user mobile devices to be operated using a virtualized personal device framework. The virtualized personal device framework may provide for a collective intelligence network platform that allows offloading of heavy computing processes onto virtual instance in a cloud network and enables crowd sourcing services for smart cities that may provide smart emergency services in which end-users collaborate.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: A system for designing and executing control loops in a cloud environment includes a control platform implemented in the cloud environment having a data collection, analytics and events module, a policy module and an application controller module. The system includes a business process management application coupled to the control platform having a control loop designer module for designing a control loop template and a workflow engine for distributing the control loop template. The business process management application is coupled to the data collection analytics and events module of the control platform as well as the policy module in the application controller module to control platform. The control loop is activated by the control platform.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: A computerized method is disclosed including but not limited to determining on a processor, a tendency of an end user's to respond to one of a plurality of advertising data types in a video data stream wherein the plurality of advertising data types comprise at least two of audio, video, text and image data types. A computer readable medium containing a data structure is disclosed providing a functional and structural interrelationship between a processor in the system and data in the data structure.

Abstract: A system for designing and executing control loops in a cloud environment includes a control platform implemented in the cloud environment having a data collection, analytics and events module, a policy module and an application controller module. The system includes a business process management application coupled to the control platform having a control loop designer module for designing a control loop template and a workflow engine for distributing the control loop template. The business process management application is coupled to the data collection analytics and events module of the control platform as well as the policy module in the application controller module to control platform. The control loop is activated by the control platform.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for generating domain-specific speech recognition models for a domain of interest by combining and tuning existing speech recognition models when a speech recognizer does not have access to a speech recognition model for that domain of interest and when available domain-specific data is below a minimum desired threshold to create a new domain-specific speech recognition model. A system configured to practice the method identifies a speech recognition domain and combines a set of speech recognition models, each speech recognition model of the set of speech recognition models being from a respective speech recognition domain. The system receives an amount of data specific to the speech recognition domain, wherein the amount of data is less than a minimum threshold to create a new domain-specific model, and tunes the combined speech recognition model for the speech recognition domain based on the data.

Abstract: Devices, computer-readable media, and methods for submitting a modified voice input to a service based upon a user intent determined from a voice input in accordance with a voice interface of the service are disclosed. A processing system including at least one processor may obtain a voice input of a user, determine an intent from the voice input, identify a first service, from among a plurality of services, in accordance with the intent, and formulate a first modified voice input from the voice input in accordance with a voice interface of the first service, where each of the services is associated with one of a plurality of different voice interfaces. The processing system may further submit the first modified voice input to the first service, obtain a first voice response from the first service, and present a voice output to the user in accordance with the first voice response.

Abstract: Concepts and technologies disclosed herein are directed to systems, methods, and computer-readable storage media for designing, creating, and deploying composite machine learning applications in cloud environments. According to one aspect disclosed herein, a system, including a processor and memory, can present a design studio canvas upon which a user can design a composite machine learning application from at least one of a plurality of building blocks stored in a design studio catalog. The system can receive input to design, on the design studio canvas, a visual representation of the composite machine learning application. The system can save the visual representation of the composite machine learning application, and, in response to saving the visual representation of the composite machine learning application, can generate a composition dump file that includes a graph structure of the composite machine learning application.

Abstract: An automated and model driven mini-cloud deployment method comprising: instantiating a model driven orchestrator; parsing a blueprint to develop a virtual network function topology including: identifying infrastructure components required to establish at least one virtual network function; identifying at least one dependency for the at least one virtual network function; providing a sequence for calling life cycle operations; the model driven orchestrator effectuates the life cycle operations comprising: establishing a uCPE as a tenant within a network registry, configuring the uCPE, and activating the uCPE; and instantiating the at least one virtual network function on the uCPE according to the virtual network function topology.

Abstract: Devices, computer-readable media and methods are disclosed for establishing a peer-to-peer network for rerouting network traffic of a telecommunication network during a network disruption. For example, a processing system may detect a network disruption between a first device and a second device of the telecommunication network. The processing system may identify a first peering device having a connection to the first device of the telecommunication network, identify a second peering device having a connection to the second device of the telecommunication network, and establish a peer-to-peer network via at least the first peering device and the second peering device, wherein at least one of the first peering device or the second peering device is a mobile endpoint device configured to operate as a virtual network function. The processing system may then route network traffic between the first device and the second device via the peer-to-peer network.

Abstract: Methods, computer-readable media, and devices for instantiating a service provider application of a network service on a customer premises-based device are disclosed. For example, a processing system of a telecommunication network having at least one processor may receive a request for a network service, identify a set of resources for the network service, the set of resources for the network service including at least a first service provider application, and determine that a current configuration of the telecommunication network does not provide the set of resources. The processing system may further reconfigure the telecommunication network to provide the set of resources, the reconfiguring including instantiating the at least the first service provider application of the network service on a customer premises-based device, and deploying the network service to the telecommunication network that is reconfigured.

Abstract: In an embodiment, a method of providing an on demand translation service is provided. A subscriber may be charged a reduced fee or no fee for use of the on demand translation service in exchange for displaying commercial messages to the subscriber, the commercial messages being selected based on subscriber information. A multimedia signal including information in a source language may be received. The information may be obtained as text in the source language from the multimedia signal. The text may be translated from the source language to a target language. Translated information, based on the translated text, may be transmitted to a processing device for presentation to the subscriber. The received multimedia signal may be sent to a multimedia device for viewing.

Abstract: A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.

Abstract: Disclosed are systems, methods, and computer readable media for identifying an acoustic environment of a caller. The method embodiment comprises analyzing acoustic features of a received audio signal from a caller, receiving meta-data information based on a previously recorded speed of the caller, classifying a background environment of the caller based on the analyzed acoustic features and the meta-data, selecting an acoustic model matched to the classified background environment from a plurality of acoustic models, and performing speech recognition as the received audio signal using the selected acoustic model.

Abstract: The invention provides for a system, method, and computer readable medium storing instructions related to controlling a presentation in a multimodal system. The method embodiment of the invention is a method for the retrieval of information on the basis of its content for real-time incorporation into an electronic presentation. The method comprises receiving from a presenter a content-based request for at least one segment of a first plurality of segments within a media presentation and while displaying the media presentation to an audience, displaying to the presenter a second plurality of segments in response to the content-based request. The computing device practicing the method receives a selection from the presenter of a segment from the second plurality of segments and displays to the audience the selected segment.

Abstract: An automated and model driven mini-cloud deployment method comprising: instantiating a model driven orchestrator; parsing a blueprint to develop a virtual network function topology including: identifying infrastructure components required to establish at least one virtual network function; identifying at least one dependency for the at least one virtual network function; providing a sequence for calling life cycle operations; the model driven orchestrator effectuates the life cycle operations comprising: establishing a uCPE as a tenant within a network registry, configuring the uCPE, and activating the uCPE; and instantiating the at least one virtual network function on the uCPE according to the virtual network function topology.

Abstract: In one embodiment, a semantic classifier input and a corresponding label attributed to the semantic classifier input may be obtained. A determination may be made whether the corresponding label is correct based on logged interaction data. An entry of an adaptation corpus may be generated based on a result of the determination. Operation of the semantic classifier may be adapted based on the adaptation corpus.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: Disclosed are systems, methods, and computer readable media for identifying an acoustic environment of a caller. The method embodiment comprises analyzing acoustic features of a received audio signal from a caller, receiving meta-data information based on a previously recorded speed of the caller, classifying a background environment of the caller based on the analyzed acoustic features and the meta-data, selecting an acoustic model matched to the classified background environment from a plurality of acoustic models, and performing speech recognition as the received audio signal using the selected acoustic model.