Abstract: A method for context-based natural language processing is disclosed herein. The method comprises maintaining a plurality of dialog system rules, receiving a user request from a Dialog System Interface, receiving one or more attributes associated with the user request from the Dialog System Interface or a user device, and identifying a type of context associated with the user request based on the user request and the one or more attributes. A context label is assigned to the user request associated with the type of context. Based on the context label and the user request, a particular dialog system rule is selected from the plurality of dialog system rules. A response to the user request is generated by applying the dialog system rule to at least a part of the user request.

Abstract: Disclosed is the technology for dynamic and intelligent generation of dialog recommendations for the users of chat information systems based on multiple criteria. An example method may include receiving a speech-based user input, recognizing at least a part of the speech-based user input to generate a recognized input, and providing at least one response to the recognized input. The method may further include identifying at least one triggering event, generating at least one dialog recommendation based at least in part on the identification, and presenting the at least one dialog recommendation to a user via a user device.

Abstract: Provided are systems and methods for creating custom dialog system engines. The system comprises a dialog system interface installed on a first server or a user device and a platform deployed on a second server. The platform is configured to receive dialog system entities and intents associated with a developer profile and associate the dialog system entities with the dialog system intents to form a custom dialog system engine associated with the dialog system interface. The web platform receives a user request from the dialog system interface, activates the custom dialog system engine based on identification, and retrieves the dialog system entities and intents. The user request is processed by applying the dialog system entities and intents to generate a response to the user request. The response is sent to the dialog system interface.

Abstract: Provided is a method for user training of an information dialogue system. The method may include activating a user input subsystem, receiving a training request entered by the user, converting the training request into text by the user input subsystem, sending the text of the training request obtained as a result of the conversion to a dialogue module, processing the text of the training request by the dialogue module, forming a response to the training request by the dialogue module, and sending the response to the training request to the user. The response to the training request may be formed in a form of one or more of the following: a voice cue, a text, and an action performed by the information dialogue system.

Abstract: A method for enhancing dialog systems is disclosed herein. The method comprises maintaining an online marketplace that may include a plurality of dialog system extension elements. Each of the plurality of dialog system extension elements may include at least one of a dialog system plugin, a dialog system add-on, a dialog system update, and a dialog system upgrade. The method may further include receiving a selection of one of the plurality of dialog system extension elements from a software developer. The software developer may be associated with a dialog system. The method may continue with associating the one of the plurality of dialog system extension elements with the dialog system of the software developer.

Abstract: Natural speech dialog system and methods are disclosed. In one example, a method includes identifying a dialog system intent associated with the speech input based on at least one predetermined intent keyword, the dialog system intent having required intent parameters, determining whether data for all required intent parameters of the dialog system are available, based on the determination, selectively initiating a parameter collection dialog associated with the dialog system intent, the parameter collection dialog being operable to collect data for the required parameters not otherwise available to the dialog system intent, and based on the dialog system intent and one or more required parameters, generating an action instruction.

Abstract: Provided is a method for user training of an information dialogue system. The method may include activating a user input subsystem, receiving a training request entered by the user, converting the training request into text by the user input subsystem, sending the text of the training request obtained as a result of the conversion to a dialogue module, processing the text of the training request by the dialogue module, forming a response to the training request by the dialogue module, and sending the response to the training request to the user. The response to the training request may be formed in a form of one or more of the following: a voice cue, a text, and an action performed by the information dialogue system.

Abstract: A method for context-based natural language processing is disclosed herein. The method comprises maintaining a plurality of dialog system rules, receiving a user request from a Dialog System Interface, receiving one or more attributes associated with the user request from the Dialog System Interface or a user device, and identifying a type of context associated with the user request based on the user request and the one or more attributes. A context label is assigned to the user request associated with the type of context. Based on the context label and the user request, a particular dialog system rule is selected from the plurality of dialog system rules. A response to the user request is generated by applying the dialog system rule to at least a part of the user request.

Abstract: Disclosed is the technology for computer-based “Daily Brief” service, which includes methods and corresponding systems for proactively providing push notifications for users of chat information systems. The push notifications are dynamically generated and presented to the user based on identification of one or more triggering events, which may include predetermined time/date, current geographical location, activity of peers and friends in social media associated with the user, scheduled events, appointments, meetings, emails, instant messages, and many more. The described technology improves the interaction interface between the user and chat information system.

Abstract: Natural speech dialog system and methods are disclosed. In one example, a method includes identifying a dialog system intent associated with the speech input based on at least one predetermined intent keyword, the dialog system intent having required intent parameters, determining whether data for all required intent parameters of the dialog system are available, based on the determination, selectively initiating a parameter collection dialog associated with the dialog system intent, the parameter collection dialog being operable to collect data for the required parameters not otherwise available to the dialog system intent, and based on the dialog system intent and one or more required parameters, generating an action instruction.

Abstract: Disclosed is the technology for computer-based “Daily Brief” service, which includes methods and corresponding systems for proactively providing push notifications for users of chat information systems. The push notifications are dynamically generated and presented to the user based on identification of one or more triggering events, which may include predetermined time/date, current geographical location, activity of peers and friends in social media associated with the user, scheduled events, appointments, meetings, emails, instant messages, and many more. The described technology improves the interaction interface between the user and chat information system.

Abstract: A method for enhancing dialog systems is disclosed herein. The method may include maintaining an online marketplace that may have a plurality of dialog system extension elements. The plurality of dialog system extension elements may include at least one of a dialog system plugin, a dialog system add-on, a dialog system update, and a dialog system upgrade. The method may further include receiving a selection of one of the plurality of dialog system extension elements from an end user. The end user may be associated with a dialog system. The method may continue with associating the one of the plurality of dialog system extension elements with the dialog system of the end user.

Abstract: A method for enhancing dialog systems is disclosed herein. The method comprises maintaining an online marketplace that may include a plurality of dialog system extension elements. Each of the plurality of dialog system extension elements may include at least one of a dialog system plugin, a dialog system add-on, a dialog system update, and a dialog system upgrade. The method may further include receiving a selection of one of the plurality of dialog system extension elements from a software developer. The software developer may be associated with a dialog system. The method may continue with associating the one of the plurality of dialog system extension elements with the dialog system of the software developer.

Abstract: A method for enhancing dialog systems is disclosed herein. The method may include maintaining an online marketplace that may have a plurality of dialog system extension elements. The plurality of dialog system extension elements may include at least one of a dialog system plugin, a dialog system add-on, a dialog system update, and a dialog system upgrade. The method may further include receiving a selection of one of the plurality of dialog system extension elements from an end user. The end user may be associated with a dialog system. The method may continue with associating the one of the plurality of dialog system extension elements with the dialog system of the end user.

Abstract: Natural speech dialog system and methods are disclosed. In one example, a method includes identifying a dialog system intent associated with the speech input based on at least one predetermined intent keyword, the dialog system intent having required intent parameters, determining whether data for all required intent parameters of the dialog system are available, based on the determination, selectively initiating a parameter collection dialog associated with the dialog system intent, the parameter collection dialog being operable to collect data for the required parameters not otherwise available to the dialog system intent, and based on the dialog system intent and one or more required parameters, generating an action instruction.

Abstract: Embodiments of the disclosure generally relate to a dialog system allowing for automatically reactivating a speech acquiring mode after the dialog system delivers a response to a user request. The reactivation parameters, such as a delay, depend on a number of predetermined factors and conversation scenarios. The embodiments further provide for a method of operating of the dialog system. An exemplary method comprises the steps of: activating a speech acquiring mode, receiving a first input of a user, deactivating the speech acquiring mode, obtaining a first response associated with the first input, delivering the first response to the user, determining that a conversation mode is activated, and, based on the determination, automatically re-activating the speech acquiring mode within a first predetermined time period after delivery of the first response to the user.

Abstract: Invoking an agent during a dialog between a user and an automated assistant. Some implementations are directed to receiving, during a human-to-automated assistant dialog, natural language input of the user that indicates a desire to engage an agent, but that fails to indicate a particular agent to be engaged. Those implementations are further directed to selecting a particular agent from a plurality of available agents, and transmitting an invocation request to the selected particular agent. In some implementations an agent selection model can be utilized in selecting the particular agent, such as a machine learning model. The machine learning model can be trained to enable generation of output that indicates, for each of a plurality of available agents (and optionally intent(s) for those agents), a probability that the available agent (and optionally intent) will generate appropriate responsive content.

Abstract: Natural speech dialog system and methods are disclosed. In one example, a method includes identifying a dialog system intent associated with the speech input based on at least one predetermined intent keyword, the dialog system intent having required intent parameters, determining whether data for all required intent parameters of the dialog system are available, based on the determination, selectively initiating a parameter collection dialog associated with the dialog system intent, the parameter collection dialog being operable to collect data for the required parameters not otherwise available to the dialog system intent, and based on the dialog system intent and one or more required parameters, generating an action instruction.

Abstract: Embodiments of the disclosure generally relate to a dialog system allowing for automatically reactivating a speech acquiring mode after the dialog system delivers a response to a user request. The reactivation parameters, such as a delay, depend on a number of predetermined factors and conversation scenarios. The embodiments further provide for a method of operating of the dialog system. An exemplary method comprises the steps of: activating a speech acquiring mode, receiving a first input of a user, deactivating the speech acquiring mode, obtaining a first response associated with the first input, delivering the first response to the user, determining that a conversation mode is activated, and, based on the determination, automatically re-activating the speech acquiring mode within a first predetermined time period after delivery of the first response to the user.

Abstract: Disclosed is the technology for dynamic and intelligent generation of dialog recommendations for the users of chat information systems based on multiple criteria. An example method may include receiving a speech-based user input, recognizing at least a part of the speech-based user input to generate a recognized input, and providing at least one response to the recognized input. The method may further include identifying at least one triggering event, generating at least one dialog recommendation based at least in part on the identification, and presenting the at least one dialog recommendation to a user via a user device.