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: 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: 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: Provided is a method for user training of an information dialog 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 dialog module, processing the text of the training request by the dialog module, forming a response to the training request by the dialog 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 dialog system.

Abstract: Disclosed are computer-implemented methods and systems for dynamic selection of speech recognition systems for the use in Chat Information Systems (CIS) based on multiple criteria and context of human-machine interaction. Specifically, once a first user audio input is received, it is analyzed so as to locate specific triggers, determine the context of the interaction or predict the subsequent user audio inputs. Based on at least one of these criteria, one of a free-diction recognizer, pattern-based recognizer, address book based recognizer or dynamically created recognizer is selected for recognizing the subsequent user audio input. The methods described herein increase the accuracy of automatic recognition of user voice commands, thereby enhancing overall user experience of using CIS, chat agents and similar digital personal assistant systems.

Abstract: Disclosed are computer-implemented methods and systems for dynamic selection of speech recognition systems for the use in Chat Information Systems (CIS) based on multiple criteria and context of human-machine interaction. Specifically, once a first user audio input is received, it is analyzed so as to locate specific triggers, determine the context of the interaction or predict the subsequent user audio inputs. Based on at least one of these criteria, one of a free-diction recognizer, pattern-based recognizer, address book based recognizer or dynamically created recognizer is selected for recognizing the subsequent user audio input. The methods described herein increase the accuracy of automatic recognition of user voice commands, thereby enhancing overall user experience of using CIS, chat agents and similar digital personal assistant systems.

Abstract: Provided is a method for user communications with an information dialog system, which may be used for organizing user interactions with the information dialog system based on a natural language. The method may include activating a user input subsystem in response to a user entering a request; receiving and converting the request of the user into text by the user input subsystem; sending the text obtained as a result of the conversion of the request to a dialog module; processing, by the dialog module, the text; forming, by the dialog module, the response to the request; sending the response to the user; and displaying and/or reproducing the formed response, where, after the displaying and/or the reproducing of the formed response, the user input subsystem is automatically activated upon entering a further request or a clarification request by the user.

Abstract: Disclosed are computer-implemented methods and systems for dynamic selection of speech recognition systems for the use in Chat Information Systems (CIS) based on multiple criteria and context of human-machine interaction. Specifically, once a first user audio input is received, it is analyzed so as to locate specific triggers, determine the context of the interaction or predict the subsequent user audio inputs. Based on at least one of these criteria, one of a free-diction recognizer, pattern-based recognizer, address book based recognizer or dynamically created recognizer is selected for recognizing the subsequent user audio input. The methods described herein increase the accuracy of automatic recognition of user voice commands, thereby enhancing overall user experience of using CIS, chat agents and similar digital personal assistant systems.

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 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: Disclosed are computer-implemented methods and systems for dynamic selection of speech recognition systems for the use in Chat Information Systems (CIS) based on multiple criteria and context of human-machine interaction. Specifically, once a first user audio input is received, it is analyzed so as to locate specific triggers, determine the context of the interaction or predict the subsequent user audio inputs. Based on at least one of these criteria, one of a free-diction recognizer, pattern-based recognizer, address book based recognizer or dynamically created recognizer is selected for recognizing the subsequent user audio input. The methods described herein increase the accuracy of automatic recognition of user voice commands, thereby enhancing overall user experience of using CIS, chat agents and similar digital personal assistant systems.

Abstract: Provided is a method for user communications with an information dialogue system, which may be used for organizing user interactions with the information dialogue system based on a natural language. The method may include activating a user input subsystem in response to a user entering a request; receiving and converting the request of the user into text by the user input subsystem; sending the text obtained as a result of the conversion of the request to a dialogue module; processing, by the dialogue module, the text; forming, by the dialogue module, the response to the request; sending the response to the user; and displaying and/or reproducing the formed response, where, after the displaying and/or the reproducing of the formed response, the user input subsystem is automatically activated upon entering a further request or a clarification request by the user.

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.