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.

Abstract: Various implementations relate to techniques, for controlling smart devices, that are low latency and/or that provide computational efficiencies (client and/or server) and/or network efficiencies. Those implementations relate to generating and/or utilizing cache entries, of a cache that is stored locally at an assistant client device, in control of various smart devices (e.g., smart lights, smart thermostats, smart plugs, smart appliances, smart routers, etc.). Each of the cache entries includes a mapping of text to one or more corresponding semantic representations.

Abstract: A computer implemented method for analyzing media content includes a step of providing a plurality of narrative files formatted in human readable format. Each narrative file includes a script and/or dialogues tagged with character names along with auxiliary information. Each script includes a plurality of portrayals performed by an associated actor or character. Linguistic representations of content of the narrative files in both abstract and semantic forms is determined. The linguistic representations are connected to higher order representations and mental states. The linguistic representations are connected to behavior and action. Interplay between language constructs and demographics of content creators is analyzed. Content representations towards individuals/groups are adapted to reflect heterogeneity in preferences.

Abstract: A method for processing multiple intents from an audio stream in a virtual reality application may include multiple steps, including: receiving a stream of words as a first utterance; processing the first utterance before the stream of words is fully received; based on the processing, determining a first intent from the first utterance before the stream of words is fully received; determining occurrence of a pause after the first utterance; and receiving a second stream of words as a second utterance, the second stream being received after the determined pause.

Abstract: Typical graphical user interfaces and predefined data fields limit the interaction between a person and a computing system. An oral communication device and a data enablement platform are provided for ingesting oral conversational data from people, and using machine learning to provide intelligence. At the front end, an oral conversational bot, or chatbot, interacts with a user. On the backend, the data enablement platform has a computing architecture that ingests data from various external data sources as well as data from internal applications and databases. These data and algorithms are applied to surface new data, identify trends, provide recommendations, infer new understanding, predict actions and events, and automatically act on this computed information. The chatbot then provides audio data that reflects the information computed by the data enablement platform. The system and the devices, for example, are adaptable to various industries.

Abstract: A speech interface device is configured to defer encryption of audio data on-device until a time when the encryption operation is not competing with other computationally-intensive operations for responding to the audio data. For example, audio data based on sound captured in an environment of the speech interface device can be stored in volatile memory of the speech interface device, without encrypting it, until a set of processing operations (e.g., ASR processing, NLU processing, audio event processing, etc.) performed based on the audio data have stopped. Based on a determination that these processing operations for responding to the audio data have stopped, the logic may encrypt the audio data to generate encrypted data, and the encrypted data can be stored in non-volatile memory of the speech interface device for uploading to a remote system when a connection is available.