Abstract: A computer-implemented method, a computer system and a computer program product enhance an intent classifier through training data augmentation. The method includes selecting a target sample from a plurality of samples. The method also includes determining an ambiguity level for the target sample based on confidence scores of at least two intent labels associated with the target sample. The method further includes selecting a nearest neighboring sample from a group of neighboring samples when the ambiguity level is below a threshold. The nearest neighboring sample includes a confidence score associated with an intent label. The method also includes, for every intent label, merging the confidence scores of the two samples into an overall confidence score for the intent label and modifying the ambiguity level using the overall confidence score. Lastly, the method includes labeling the target sample with the intent label when the modified ambiguity level is above the threshold.

Abstract: A method comprising: receiving an interactive voice response (IVR) tree configured to implement one or more tasks, each associated with one or more IVR node paths comprising a plurality of IVR nodes arranged in a hierarchical relationship; analyzing the IVR tree to identify one or more intent IVR nodes, each associated with one of the tasks; with respect to each of the intent IVR nodes, identifying a plurality of corresponding entity IVR nodes included within the IVR node path associated with the intent IVR node; assembling one or more task-specific chatbot skills, each comprising (i) one of the intent IVR nodes, and (ii) at least some of the plurality of corresponding entity IVR nodes, wherein each of the task-specific chatbot skills is configured to perform one of the tasks by conducting a dialog with a user; and generating a chatbot comprising at least one of the task-specific chatbot skills.

Abstract: A method comprising: receiving an interactive voice response (IVR) tree configured to implement one or more tasks, each associated with one or more IVR node paths comprising a plurality of IVR nodes arranged in a hierarchical relationship; analyzing the IVR tree to identify one or more intent IVR nodes, each associated with one of the tasks; with respect to each of the intent IVR nodes, identifying a plurality of corresponding entity IVR nodes included within the IVR node path associated with the intent IVR node; assembling one or more task-specific chatbot skills, each comprising (i) one of the intent IVR nodes, and (ii) at least some of the plurality of corresponding entity IVR nodes, wherein each of the task-specific chatbot skills is configured to perform one of the tasks by conducting a dialog with a user; and generating a chatbot comprising at least one of the task-specific chatbot skills.

Abstract: Methods, apparatus and computer program products implement embodiments of the present invention that include receiving a time domain voice signal, and extracting a single pitch cycle from the received signal. The extracted single pitch cycle is transformed to a frequency domain, and the misclassified roots of the frequency domain are identified and corrected. Using the corrected roots, an indication of a maximum phase of the frequency domain is generated.

Abstract: Methods, apparatus and computer program products implement embodiments of the present invention that include receiving a time domain voice signal, and extracting a single pitch cycle from the received signal. The extracted single pitch cycle is transformed to a frequency domain, and the misclassified roots of the frequency domain are identified and corrected. Using the corrected roots, an indication of a maximum phase of the frequency domain is generated.

Abstract: Some embodiments of the invention relate to a method and a system for detecting unwanted conversational media session data. In accordance with one aspect of the invention, a method of detecting unwanted conversation media session data according to some embodiments of the invention may include calculating two or more progressive similarity scores each with respect to a different instant during a progress of a real-time conversational media session, wherein each of said scores is associated with a similarity between the conversational media session's media data that was available at the associated instant and a reference data item corresponding to media data of a previous conversational media session, and evaluating progressive similarity between the real-time conversational media session and the reference data item based upon the two or more progressive similarity scores.

Abstract: Some embodiments of the invention relate to a method and a system for detecting unwanted conversational media session data. In accordance with one aspect of the invention, a method of detecting unwanted conversation media session data according to some embodiments of the invention may include calculating two or more progressive similarity scores each with respect to a different instant during a progress of a real-time conversational media session, wherein each of said scores is associated with a similarity between the conversational media session's media data that was available at the associated instant and a reference data item corresponding to media data of a previous conversational media session, and evaluating progressive similarity between the real-time conversational media session and the reference data item based upon the two or more progressive similarity scores.

Abstract: Some embodiments of the invention relate to a method and a system for detecting unwanted conversational media session data. In accordance with one aspect of the invention, a method of detecting unwanted conversation media session data according to some embodiments of the invention may include calculating two or more progressive similarity scores each with respect to a different instant during a progress of a real-time conversational media session, wherein each of said scores is associated with a similarity between the conversational media session's media data that was available at the associated instant and a reference data item corresponding to media data of a previous conversational media session, and evaluating progressive similarity between the real-time conversational media session and the reference data item based upon the two or more progressive similarity scores.

Abstract: Some embodiments of the invention relate to a method and a system for detecting unwanted conversational media session data. In accordance with one aspect of the invention, a method of detecting unwanted conversation media session data according to some embodiments of the invention may include calculating two or more progressive similarity scores each with respect to a different instant during a progress of a real-time conversational media session, wherein each of said scores is associated with a similarity between the conversational media session's media data that was available at the associated instant and a reference data item corresponding to media data of a previous conversational media session, and evaluating progressive similarity between the real-time conversational media session and the reference data item based upon the two or more progressive similarity scores.

Abstract: Some embodiments of the invention relate to a method and a system for detecting unwanted conversational media session data. In accordance with one aspect of the invention, a method of detecting unwanted conversation media session data according to some embodiments of the invention may include calculating two or more progressive similarity scores each with respect to a different instant during a progress of a real-time conversational media session, wherein each of said scores is associated with a similarity between the conversational media session's media data that was available at the associated instant and a reference data item corresponding to media data of a previous conversational media session, and evaluating progressive similarity between the real-time conversational media session and the reference data item based upon the two or more progressive similarity scores.

Abstract: Some embodiments of the invention relate to a method and a system for detecting unwanted conversational media session data. In accordance with one aspect of the invention, a method of detecting unwanted conversation media session data according to some embodiments of the invention may include calculating two or more progressive similarity scores each with respect to a different instant during a progress of a real-time conversational media session, wherein each of said scores is associated with a similarity between the conversational media session's media data that was available at the associated instant and a reference data item corresponding to media data of a previous conversational media session, and evaluating progressive similarity between the real-time conversational media session and the reference data item based upon the two or more progressive similarity scores.

Abstract: Some embodiments of the invention relate to a method and a system for detecting unwanted conversational media session data. In accordance with one aspect of the invention, a method of detecting unwanted conversation media session data according to some embodiments of the invention may include calculating two or more progressive similarity scores each with respect to a different instant during a progress of a real-time conversational media session, wherein each of said scores is associated with a similarity between the conversational media session's media data that was available at the associated instant and a reference data item corresponding to media data of a previous conversational media session, and evaluating progressive similarity between the real-time conversational media session and the reference data item based upon the two or more progressive similarity scores.

Abstract: Some embodiments of the invention relate to a method and a system for detecting unwanted conversational media session data. In accordance with one aspect of the invention, a method of detecting unwanted conversation media session data according to some embodiments of the invention may include calculating two or more progressive similarity scores each with respect to a different instant during a progress of a real-time conversational media session, wherein each of said scores is associated with a similarity between the conversational media session's media data that was available at the associated instant and a reference data item corresponding to media data of a previous conversational media session, and evaluating progressive similarity between the real-time conversational media session and the reference data item based upon the two or more progressive similarity scores.

Abstract: A network, such as a mobile network, is integrated with at least one application function, providing a mechanism that allows for the exchange of data between the mobile network and the application function. This mechanism is generic and aware of changing radio conditions, such as bandwidth, delay and jitter. It provides the application function with present network conditions, allowing the application function to adjust its level of service.

Abstract: Systems and methods exercise control over the Real Time Streaming Protocol (RTSP) messages in order to control the underlying streaming services. The methods and systems also minimize bandwidth allocated for each streaming flow. The systems and methods control streaming services by analyzing the RTSP associated with a particular streaming service.

Abstract: A resource allocation system for a network, the system including a traffic shaper operative to decompose a network stream into a plurality of flows, each flow representing a service or application on a network down-link, and shape network traffic by allocating a different bandwidth and delay to each flow, and a policy processor operative to control the traffic shaper and dynamically allocate at least one air interface resource to at least one network device in association with at least one of the flows.

Abstract: Systems and methods, employed with data networks, for example, cellular networks, that provide dynamic awareness of: a) shared media or cell resources; and b) link-specific disturbances, are disclosed. The systems and methods (processes), and portions thereof, operate dynamically and “on the fly”. As a result, the systems and methods can control data flows (at various rates) through the shared media, allowing for transmissions, for example, of packets, at optimal bandwidths (bit rates), while maintaining existing protocol structures.

Abstract: There are disclosed methods (processes) and systems, for: 1. establishing and defining service classes and service plans; 2. monitoring and controlling parameters related to level of service for each service class; and 3. estimating the additional resources necessary to support excessive traffic demand. These methods and systems provide visibility into the network, enabling management of the network.

Abstract: Systems and methods for dynamically managing data traffic in cellular networks are disclosed. These systems and methods conduct management of the data traffic in the form of: 1. service management, such as service provisioning and service level tuning and monitoring; 2. monitoring and controlling resources, such as bandwidth and delay; and 3. management of packet flows traffic. In doing so, there are provided methods for dynamically and automatically (continuously) adjusting the bandwidth and delay in individual shared access media or cells “on the fly”, to optimize user experience, usage and packet transmissions in the network.

Abstract: There are disclosed methods, systems, devices and articles of manufacture for processing measurements of resources, for example, bandwidth or bandwidth traffic, on the IP and cellular sides of data networks. Processing of these measurements is such that these resources, (e.g. bandwidth or bandwidth traffic), on the cellular side of the data network, can be managed (controlled) from the IP side of the data network.