Abstract: Methods and server systems for computing fraud risk scores for various merchants associated with an acquirer described herein. The method performed by a server system includes accessing merchant-related transaction data including merchant-related transaction indicators associated with a merchant from a transaction database. Method includes generating a merchant-related transaction features based on the merchant-related indicators. Method includes generating via risk prediction models, for a payment transaction with the merchant, merchant health and compliance risk scores, merchant terminal risk scores, merchant chargeback risk scores, and merchant activity risk scores based on the merchant-related transaction features. Method includes facilitating transmission of a notification message to an acquirer server associated with the merchant.

Abstract: Embodiments herein relate to a module which can be inserted into or removed from a computing device by a user. The module includes an input-output port which is configured for a desired specification, such as USB-A, USB-C, Thunderbolt, DisplayPort or HDMI. The port can be provided on an expansion card such as an M.2 card for communicating with a host platform. The host platform can communicate with different types of modules in a standardized way so that complexity and costs are reduced. In another aspect, with a dual port module, the host platform can concurrently send/receive power through one port and send/receive data from the other port.

Abstract: A data storage device and method for progressive fading for video surveillance systems are provided. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to store a plurality of digital video frames in the memory over time; and create free space in the memory by deleting some of the plurality of digital video frames across a plurality of subsets of digital video frames, wherein fewer digital video frames are deleted from a subset stored more recently in time than from a subset stored less recently in time. Other embodiments are provided.

Abstract: A data storage device includes interfaces for coupling the data storage device to a host system and a server system. The data storage device also includes a device memory for storing or providing data. The data storage device also includes a controller comprising a storage subsystem and a security subsystem. The storage subsystem is configured to receive a host command, receive a probe request for an exception state, generate and transmit, to the security subsystem, a report for the exception state. In response to receiving an update from the security subsystem, the storage subsystem restarts at least a portion of the controller. The security subsystem is configured to monitor and transmit a probe request to the storage subsystem, transmit the report to the server system, receive the update from the server system, and transmit the update to the storage subsystem. Methods and systems are also disclosed.

Abstract: A data storage device includes a host interface for coupling the data storage device to a host system. The data storage device also includes a device memory for storing or providing data in response to commands receive from the host system. The data storage device also includes a controller comprising a storage subsystem and a security subsystem. The storage subsystem is configured to receive a host command from the host interface, and process the host command for the device memory. The security subsystem includes a device recovery circuit configured to monitor the storage subsystem for an exception state, and reinitialize pending operations for the storage subsystem after the exception state. Methods and systems are also disclosed.

Abstract: Systems, methods, and computer-readable media are disclosed for dynamic voice search transitioning. Example methods may include receiving, by a computer system in communication with a display, a first incoming voice data indication, initiating a first user interface theme for presentation at a display, wherein the first user interface theme is a default user interface theme, and receiving first voice data. Example methods may include sending the first voice data to a remote server for processing, receiving an indication from the remote server to initiate a second user interface theme, and initiating the second user interface theme for presentation at the display.

Abstract: Techniques for enrolling a user in a system's user recognition functionality without requiring the user speak particular speech are described. The system may determine characteristics unique to a user input. The system may generate an implicit voice profile from user inputs having similar characteristics. After an implicit voice profile is generated, the system may receive a user input having speech characteristics similar to that of the implicit voice profile. The system may ask the user if the user wants the system to associate the implicit voice profile with a particular user identifier. If the user responds affirmatively, the system may request an identifier of a user profile (e.g., a user name). In response to receiving the user's name, the system may identify a user profile associated with the name and associate the implicit voice profile with the user profile, thereby converting the implicit voice profile into an explicit voice profile.

Abstract: Described are techniques for predicting when data associated with a user input is likely to be selected for deletion. The system may use a trained model to assist with such predictions. The trained model can be configured based on deletions associated with a user profile. An example process can including receiving user input data corresponding to the user profile, and processing the user input data to determine a user command. Based on characteristic data of the user command, the trained model can be used to determine that data corresponding to the user command is likely to be selected for deletion. The trained model can be iteratively updated based on additional user commands, including previously received user commands to delete user input data.

Abstract: Described are techniques for predicting when data associated with a user input is likely to be selected for deletion. The system may use a trained model to assist with such predictions. The trained model can be configured based on deletions associated with a user profile. An example process can including receiving user input data corresponding to the user profile, and processing the user input data to determine a user command. Based on characteristic data of the user command, the trained model can be used to determine that data corresponding to the user command is likely to be selected for deletion. The trained model can be iteratively updated based on additional user commands, including previously received user commands to delete user input data.

Abstract: Techniques for ensuring content output to a user conforms to a quality of the user's speech, even when a speechlet or skill ignores the speech's quality, are described. When a system receives speech, the system determines an indicator of the speech's quality (e.g., whispered, shouted, fast, slow, etc.) and persists the indicator in memory. When the system receives output content from a speechlet or skill, the system checks whether the output content is in conformity with the speech quality indicator. If the content conforms to the speech quality indicator, the system may cause the content to be output to the user without further manipulation. But, if the content does not conform to the speech quality indicator, the system may manipulate the content to render it in conformity with the speech quality indicator and output the manipulated content to the user.

Abstract: A data storage device and method for host-determined proactive block clearance are provided. In one embodiment, a data storage device is provided comprising a memory and a controller. The controller is configured to receive a command from a host that specifies a parameter of an upcoming burst mode; and in response to receiving the command, proactively perform a garbage collection operation according to the parameter to create available storage space in the memory to store data from the host during the upcoming burst mode. Other embodiments are possible, and each of the embodiments can be used alone or together in combination.

Abstract: The disclosed technology relates to intent driven network management. A system is configured to maintain an inventory store comprising records for a set of network entities in a network, wherein each network entity in the set of network entities is associated with a record in the inventory store. The system receives a user intent statement comprising an action and a flow filter representing network data flows on which the action is to be applied and queries, based on the flow filter, the inventory store to identify a plurality of network entities in the set of network entities to which the user intent statement applies. The system generates a plurality of network policies that implement the user intent statement based on the plurality of network entities and the action and enforces the plurality network policies.

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) is configured such that a SIM card inserted in the UE, which is invalid to camp on a network, may be allowed by the UE to camp on the network based on a preconfigured policy. The policy, for example, may require a valid SIM card to be inserted into a second SIM card slot on the UE. In some policies, the valid SIM card may also be required to camp on a network with full service in order to allow the invalid SIM card to camp on a network. In some policies, the valid SIM card may also be required to camp on a specific type of network, for example a standalone non-public network (SNPN) or a 3GPP network.

Abstract: A speech interface device is configured to receive response data from a remote speech processing system for responding to user speech. This response data may be enhanced with information such as remote NLU data. The response data from the remote speech processing system may be compared to local NLU data to improve a speech processing model on the device. Thus, the device may perform supervised on-device learning based on the remote NLU data. The device may determine differences between the updated speech processing model and an original speech processing model received from the remote system and may send data indicating these differences to the remote system. The remote system may aggregate data received from a plurality of devices and may generate an improved speech processing model.

Abstract: Features are disclosed for detecting words in audio using contextual information in addition to automatic speech recognition results. A detection model can be generated and used to determine whether a particular word, such as a keyword or “wake word,” has been uttered. The detection model can operate on features derived from an audio signal, contextual information associated with generation of the audio signal, and the like. In some embodiments, the detection model can be customized for particular users or groups of users based usage patterns associated with the users.

Abstract: The disclosed technology relates to a network agent for reporting to a network policy system. A network agent includes an agent enforcer and an agent controller. The agent enforcer is configured to implementing network policies on the system, access data associated with the implementation of the network policies on the system, and transmit, via an interprocess communication, the data to the agent controller. The agent controller is configured to generate a report including the data and transmit the report to a network policy system.

Abstract: The disclosed technology relates to intent driven network management. A system is configured to maintain an inventory store comprising records for a set of network entities in a network, wherein each network entity in the set of network entities is associated with a record in the inventory store. The system receives a user intent statement comprising an action and a flow filter representing network data flows on which the action is to be applied and queries, based on the flow filter, the inventory store to identify a plurality of network entities in the set of network entities to which the user intent statement applies. The system generates a plurality of network policies that implement the user intent statement based on the plurality of network entities and the action and enforces the plurality network policies.

Abstract: Techniques for ensuring content output to a user conforms to a quality of the user's speech, even when a speechlet or skill ignores the speech's quality, are described. When a system receives speech, the system determines an indicator of the speech's quality (e.g., whispered, shouted, fast, slow, etc.) and persists the indicator in memory. When the system receives output content from a speechlet or skill, the system checks whether the output content is in conformity with the speech quality indicator. If the content conforms to the speech quality indicator, the system may cause the content to be output to the user without further manipulation. But, if the content does not conform to the speech quality indicator, the system may manipulate the content to render it in conformity with the speech quality indicator and output the manipulated content to the user.

Abstract: Systems, methods, and devices for computer-generating responses and sending responses to communications when the recipient of the communication is unavailable are disclosed. An individual may send a message (either audio or text) to a recipient. The recipient may be unavailable to contemporaneously respond to the message (e.g., the recipient may be performing an action that makes is difficult or impractical for the recipient to contemporaneously respond to the audio message). When the recipient is unavailable, a response to the message is generated and sent without receiving an instruction from the recipient to do so. The response may be sent to the message originating individual, and content of the response may thereafter be sent to the recipient to receive feedback regarding the correctness of the response. Alternatively, the response content may first be sent to the recipient to receive the feedback, and thereafter the response may be sent to the message originating individual.