Abstract: This application discloses an intent recognition optimization processing method, apparatus, device and storage medium, and relates to the field of internet technology. The implementation scheme of specific method includes: acquiring a first intent set and at least one original corpus; acquiring a first recognition result of each original corpus, where the first recognition result of any one of the original corpus includes a first intent corresponding to the original corpus recognized by the intent recognition model; acquiring a second recognition result of each original corpus, where the second recognition result of any one of the original corpus includes a second intent corresponding to the original corpus obtained through artificial recognition; and performing optimization processing on the first intent set to obtain a second intent set according to the first recognition result and the second recognition result of each original corpus.

Abstract: This application discloses an intent recognition optimization processing method, apparatus, device and storage medium, and relates to the field of internet technology. The implementation scheme of specific method includes: acquiring a first intent set and at least one original corpus; acquiring a first recognition result of each original corpus, where the first recognition result of any one of the original corpus includes a first intent corresponding to the original corpus recognized by the intent recognition model; acquiring a second recognition result of each original corpus, where the second recognition result of any one of the original corpus includes a second intent corresponding to the original corpus obtained through artificial recognition; and performing optimization processing on the first intent set to obtain a second intent set according to the first recognition result and the second recognition result of each original corpus.

Abstract: An image is received from a light capture device associated with the smart display device. A determination is made as to whether to activate voice recognition of a recording device associated with the smart display device based on a face being in the image. In response to determining to activate the voice recognition of the recording device associated with the smart display device based on the face being in the image, the voice recognition of the recording device associated with the smart display device is activated.

Abstract: An image associated with a smart display device is received from a light capture device. Characteristics of the image received from the light capture device are identified. A determination is made as to whether to deactivate a display of the smart display device based on the characteristics of the image. In response to determining to deactivate the display of the smart display device based on the characteristics of the image, the display of the smart display device is deactivated.

Abstract: A signal corresponding to sound associated with the smart display device is received from a sound capture device. A machine learning model analyzes characteristics of the signal received from the sound capture device to determine whether to deactivate a display of the smart display device. In response to determining to deactivate the display of the smart display device based on the analysis, the display of the smart display device is deactivated.

Abstract: Embodiments of the inventive system and methods are directed to a computer program that employs a drag-and-drop user interface for debugging dialogue states, tracking dialogue context, understanding dialogue utterances, and managing dialogue sessions of a conversational agent. Each dialogue element is defined in a “node” that can be dragged and dropped into a canvas of the user interface. A debugging window allows a user to visually debug and/or search the code associated with each dialogue element as well as execute each dialogue element of the conversational agent in sequence at a pace that is suitable to the user.

Abstract: Embodiments of the invention provide a natural language understanding (NLU) system that performs relatively complex task automations via verbal or voice instructions. Normally, task automations have a trigger condition, and a series of one or more actions that would require a user's selection of an option via manual input. This is because the underlying machine logic requires knowledge and classification capabilities from multiple domains that conventional personal assistants are not capable of. Embodiments of the inventive system and methods provide a solution to this complex task by analyzing trigger and action domains, pinpointing appropriate APIs, extracting corresponding API parameters, and automatically fulfilling API calls for the user. The system is configured to parse natural language commands into API calls. It analyzes both the trigger and action APIs and prompts a user for any missing information if necessary.

Abstract: An image associated with a smart display device is received from a light capture device. Characteristics of the image received from the light capture device are identified. A determination is made as to whether to deactivate a display of the smart display device based on the characteristics of the image. In response to determining to deactivate the display of the smart display device based on the characteristics of the image, the display of the smart display device is deactivated.

Abstract: An image is received from a light capture device associated with the smart display device. A determination is made as to whether to activate voice recognition of a recording device associated with the smart display device based on a face being in the image. In response to determining to activate the voice recognition of the recording device associated with the smart display device based on the face being in the image, the voice recognition of the recording device associated with the smart display device is activated.

Abstract: A signal corresponding to sound associated with the smart display device is received from a sound capture device. A machine learning model analyzes characteristics of the signal received from the sound capture device to determine whether to deactivate a display of the smart display device. In response to determining to deactivate the display of the smart display device based on the analysis, the display of the smart display device is deactivated.

Abstract: Embodiments of the inventive system and methods are directed to a computer program that employs a drag-and-drop user interface for managing dialogue states, tracking dialogue context, understanding dialogue utterances, and managing dialogue sessions. Each dialogue element is defined in a “node” that can be dragged and dropped into a canvas of the user interface. An embodiment provides wiring mechanisms to freely link nodes. Dialogue utterances are contained in messages that flow through the wires linking different nodes until exiting the canvas to an end user. An executable image of a conversational agent is then generated by compiling the source code associated with the nodes based on their connections. A conversational agent can be deployed in an electronic device such as a home device, which configured to perform an action in response to a user verbal command or request using the conversational agent deployed therein.

Abstract: According to one embodiment, in response to a text stream originated from a user at an electronic device (e.g., home device), a natural language processing (NLP) operation is performed on the text stream. An object described by the text stream is determined based on the NLP operation. One or more colors associated with the object are determined. A light control command is then transmitted from the electronic device to each of the smart lights to control a color of the smart light based on the one or more colors associated with the object, such that the smart lights are lit with the colors associated with the object. The text stream may be converted from a voice stream using a speech recognition process.

Abstract: Embodiments of the inventive system and methods are directed to a computer program that employs a drag-and-drop user interface for managing dialogue states, tracking dialogue context, understanding dialogue utterances, and managing dialogue sessions. Each dialogue element is defined in a “node” that can be dragged and dropped into a canvas of the user interface. An embodiment provides wiring mechanisms to freely link nodes. Dialogue utterances are contained in messages that flow through the wires linking different nodes until exiting the canvas to an end user. An executable image of a conversational agent is then generated by compiling the source code associated with the nodes based on their connections. A conversational agent can be deployed in an electronic device such as a home device, which configured to perform an action in response to a user verbal command or request using the conversational agent deployed therein.

Abstract: Embodiments of the inventive system and methods are directed to a computer program that employs a drag-and-drop user interface for debugging dialogue states, tracking dialogue context, understanding dialogue utterances, and managing dialogue sessions of a conversational agent. Each dialogue element is defined in a “node” that can be dragged and dropped into a canvas of the user interface. A debugging window allows a user to visually debug and/or search the code associated with each dialogue element as well as execute each dialogue element of the conversational agent in sequence at a pace that is suitable to the user.

Abstract: According to one embodiment, in response to a text stream originated from a user at an electronic device (e.g., home device), a natural language processing (NLP) operation is performed on the text stream. An object described by the text stream is determined based on the NLP operation. One or more colors associated with the object are determined. A light control command is then transmitted from the electronic device to each of the smart lights to control a color of the smart light based on the one or more colors associated with the object, such that the smart lights are lit with the colors associated with the object. The text stream may be converted from a voice stream using a speech recognition process.

Abstract: Embodiments of the invention provide a natural language understanding (NLU) system that performs relatively complex task automations via verbal or voice instructions. Normally, task automations have a trigger condition, and a series of one or more actions that would require a user's selection of an option via manual input. This is because the underlying machine logic requires knowledge and classification capabilities from multiple domains that conventional personal assistants are not capable of. Embodiments of the inventive system and methods provide a solution to this complex task by analyzing trigger and action domains, pinpointing appropriate APIs, extracting corresponding API parameters, and automatically fulfilling API calls for the user. The system is configured to parse natural language commands into API calls. It analyzes both the trigger and action APIs and prompts a user for any missing information if necessary.