Abstract: Methods, apparatus, system and computer-implemented method are provided for embedding a portion of text describing one or more entities of interest and a relationship. The portion of text describes a relationship for the one or more entity(ies) of interest, where the portion of text includes multiple separable entities describing the relationship and the entity(ies). The multiple separable entities including the one or more entity(ies) of interest and one or more relationship entity(ies). A set of embeddings for each of the separable entities is generated, where the set of embeddings for a separable entity includes an embedding for the separable entity and an embedding for at least one entity associated with the separable entity. One or more composite embeddings may be formed based on at least one embedding from each of the sets of embeddings. The composite embedding(s) may be sent for input to a machine learning model or classifier.

Abstract: Systems and methods are disclosed for tuning a generative artificial intelligence (AI) model based on a knowledge base. Instead of manually generating questions relevant to the knowledge base, providing those questions to the generative AI model, and manually reviewing the answers generated by the generative AI model in order to tune the generative AI model over many iterations, a natural language processing model may be configured to leverage the knowledge base to automatically generate questions and answers based on the knowledge base. In this manner, the natural language processing model is able to generate tuning data that may be used to automatically tune the generative AI model. The systems and methods also disclose automatic tuning of the generative AI model, including testing and feedback that may be used to improve tuning of the generative AI model.

Abstract: An information processing apparatus includes an extracting unit (133) that extracts a changing message related to a change in macro data (M), the changing message including at least one piece of first information indicating a function to be executed, and second information linked to the first information, from a user speech; a presuming unit (134) that presumes an element to be changed in the macro data (M) based on the changing message extracted by the extracting unit (133); and a changing unit (135) that changes the element to be changed in the macro data (M) presumed by the presuming unit (134), based on the changing message.

Abstract: Introduced here is a computer program that is representative of a software-implemented collaboration platform that is designed to facilitate conversations in virtual environments, document those conversations, and analyze those conversations, all in real time. The collaboration platform can include or integrate tools for turning ideas—expressed through voice—into templatized, metadata-rich data structures called “knowledge objects.” Discourse throughout a conversation can be converted into a transcription (or simply “transcript”), parsed to identify topical shifts, and then segmented based on the topical shifts. Separately documenting each topic in the form of its own “knowledge object” allows the collaboration platform to not only better catalogue what was discussed in a single ideation session, but also monitor discussion of the same topic over multiple ideation sessions.

Abstract: The present invention provides an information processing device that processes a voice-based agent interaction, and an information processing method, and provides an information processing system. The information processing device is provided with: a communication unit that receives information related to an interaction with a user through an agent residing in a first apparatus; and a control unit that controls an external agent service. The control unit collects the information that includes at least one among an image or a voice of the user, information related to operation of the first apparatus by the user, and sensor information detected by a sensor with which the first apparatus is equipped. The control unit controls calling of the external agent service.

Abstract: A discussion support device acquires, via a communication network, a plurality of comments relating to a main topic of a discussion, extracts a plurality of ideas, a plurality of favorable points, a plurality of unfavorable points, and a plurality of issues from the acquired plurality of comments, identifies a topology between the extracted plurality of ideas, plurality of favorable points, plurality of unfavorable points, and plurality of issues, and creates a facilitation structure to realize the identified topology.

Abstract: Network source identification via audio signals is provided. A system receives data packets with an input audio signal from a client device. The system identifies a request. The system selects a digital component provided by a digital component provider device. The system identifies audio chimes stored in memory of the client device. The system matches, based on a policy, an identifier of the digital component provider device to a first audio chime stored in the memory of the client device. The system determines, based on a characteristic of the first audio chime, a configuration to combine the digital component with the first audio chime. The system generates an action data structure with the digital component, an indication of the first audio chime, and the configuration. The system transmits the action data structure to the client device to cause the client device to generate an output audio signal.

Abstract: The present disclosure discloses a method for processing man-machine dialogues, which includes: acquiring a first user voice message from a client; determining a dialogue intent corresponding to the first user voice message; determining a target duplex wake-up mode corresponding to the dialogue intent based on an intent wake-up mode table, wherein the intent-wake mode table includes duplex wake-up modes corresponding to a plurality of candidate dialogue intents respectively, and the duplex wake-up modes comprise a full-duplex wake-up mode and a half-duplex wake-up mode; and sending a wake-up mode instruction corresponding to the target duplex wake-up mode to the client, such that the client processes the first user voice message according to the target duplex wake-up mode. Using the method and apparatus for carrying out the method, the wake-up mode of the client may be switched dynamically.

Abstract: An electronic device for performing speech recognition and a method therefor are provided. The method includes detecting a first text, which is preset for performing speaker recognition, by performing speech recognition on a first speech signal, performing speaker recognition on a second speech signal acquired after the first speech signal, based on the first text being detected, and executing a voice command obtained from the second speech signal, based on a result of performing the speaker recognition on the second speech signal indicating that a speaker of the second speech signal corresponds to a first speaker who registered the first text.

Abstract: A speech-processing system receives both text data and natural-understanding data (e.g., a domain, intent, and/or entity) related to a command represented in the text data. The system uses the natural-understanding data to vary vocal characteristics in determining spectrogram data corresponding to the text data based on the natural-understanding data.

Abstract: A collection of digital video files may contain a large amount of unstructured information in the form of spoken words encoded within audio tracks. The audio tracks are transcribed into digital text. Attributes are extracted from the digital text and mapped to a particular subject matter aspect. Attribute to aspect mappings provide a useful organization for the unstructured information. Furthermore, sentiment scores and trends for one or more aspects may be determined and displayed.

Abstract: A method, computer program product, and computing system for monitoring a plurality of conversations within a monitored space to generate a conversation data set; processing the conversation data set using machine learning to: define a system-directed command for an ACI system, and associate one or more conversational contexts with the system-directed command; detecting the occurrence of a specific conversational context within the monitored space, wherein the specific conversational context is included in the one or more conversational contexts associated with the system-directed command; and executing, in whole or in part, functionality associated with the system-directed command in response to detecting the occurrence of the specific conversational context without requiring the utterance of the system-directed command and/or a wake-up word/phrase.

Abstract: This relates to systems and processes for using a virtual assistant to arbitrate among and/or control electronic devices. In one example process, a first electronic device samples an audio input using a microphone. The first electronic device broadcasts a first set of one or more values based on the sampled audio input. Furthermore, the first electronic device receives a second set of one or more values, which are based on the audio input, from a second electronic device. Based on the first set of one or more values and the second set of one or more values, the first electronic device determines whether to respond to the audio input or forego responding to the audio input.

Abstract: The present disclosure provides a system, a method, an electronic device, and a storage medium for identifying risk event based on social information.

Abstract: Disclosed are method and apparatus for correcting voice dialogue, including: recognizing first text information of a dialogue speech input by a user, including a first semantic keyword determined from a plurality of candidate terms; feeding back a first result with the first semantic keyword to the user based on the first text information; feeding back the plurality of candidate terms to the user in response to the user's selection of the first semantic keyword from the first result; and receiving a second semantic keyword input by the user, correcting the first text information based on the second semantic keyword, determining corrected second text information, and feeding back a second result with the second semantic keyword to the user based on the second text information. The problem of true ambiguity can be solved, while improving the fault tolerance and processing capability of the dialogue apparatus for corresponding errors.

Abstract: Techniques for conversation recovery in a dialog management system are described. A system may determine, using dialog models, that a predicted action to be performed by a skill component is likely to result in an undesired response or that the skill component is unable to respond to a user input of a dialog session. Rather than informing the user that the skill component is unable to respond, the system may send data to the skill component to enable the skill component to determine a correct action responsive to the user input. The data may include an indication of the predicted action and/or entity data corresponding to the user input. The system may receive, from the skill component, response data corresponding to the user input, and may use the response data to update a dialog context for the dialog session and an inference engine of the dialog management system.

Abstract: Configurable core domains of a speech processing system are described. A core domain output data format for a given command is originally configured with default content portions. When a user indicates additional content should be output for the command, the speech processing system creates a new output data format for the core domain. The new output data format is user specific and includes both default content portions as well as user preferred content portions.

Abstract: A search is performed based on a voice input combined with user selection of entities displayed on a display screen as well as real-world entities. A voice input is received from the user by a media device, as well as a selection of a first entity being displayed on the media device. A conjunction spoken in the voice input triggers the media device to wait for selection of a second entity before performing the search. After receiving selection of the second entity, a search query is constructed based on the voice input, the first entity, and the second entity. The search query is transmitted to a database and, in response, the media device receives at least one identifier of a least one content item. The at least one identifier is then generated for display to the user.

Abstract: A computer-implemented method of responding to a conversational event is presented. The method comprises receiving a conversational event at a conversational computing interface. Based on the received conversational event, an applicable generation rule of a plurality of candidate generation rules is selected. The applicable generation rule is configured with one or more parameters. A computer-executable plan is then selected based on the selected generation rule. The one or more parameters are passed from the selected generation rule to one or more additional generation rules. The one or more additional generation rules configured with the one or more parameters are recursively applied to extend the selected computer-executable plan. One or more candidate responses to the conversational event are output via the conversational computing interface based on the recursive application of the one or more additional generation rules configured with the one or more parameters.

Abstract: Embodiments of the present disclosure disclose an audio content recognition method and apparatus, an electronic device and a non-transitory computer-readable medium. A specific implementation of the method includes: obtaining a voice fragment collection and a non-voice fragment collection by segmenting audio; determining a type and language information of each voice fragment in the voice fragment collection; obtaining, for each voice fragment in the voice fragment collection, a first recognition result by performing voice recognition on the voice fragment based on the type and the language information of the voice fragment. In the implementation, speaking and music fragments in the audio are recognized by different models, so that two audio contents may both have better recognition effects. Moreover, audio of different language contents is recognized by using different models, thereby further improving a voice recognition effect.