Abstract: The embodiments of the present disclosure relate to a sound signal processing method, device, electronic equipment and storage medium. The method is used for a head-mounted display apparatus and includes: acquiring an ambient sound signal of the head-mounted display apparatus, identifying the ambient sound signal and determining a sound category corresponding to the ambient sound signal, and displaying corresponding prompt information in the head-mounted display apparatus according to the sound category.

Abstract: The present disclosure provides a virtual scene presentation method, apparatus, device, and storage medium, the method comprising: identifying a physical object set in an environment space; determining a scene type corresponding to the environment space; obtaining a virtual scene set associated with the scene type; and presenting a virtual scene in the virtual scene set on at least part of physical objects in the physical object set.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may determine that one or more threshold criteria are satisfied, wherein the one or more threshold criteria include at least one of a first value for an uplink grant rate, a second value for a buffer size, or a third value for a packet data convergence protocol discard rate, wherein the one or more threshold criteria relate to a network condition with less than a reference uplink throughput and greater than a reference downlink throughput. The UE may transmit information identifying one or more adjusted measurement values based at least in part on the determination of the one or more threshold criteria. Numerous other aspects are described.

Abstract: Methods, systems, and devices for wireless communications are described. The described techniques provide for a user equipment (UE) using information identified via radio access technology (RAT) (e.g., Long Term Evolution (LTE)) to support communications in another RAT (e.g., New Radio (NR)). For example, the UE may receive, from a first base station operating according to a first radio access technology an indication of a high speed associated with a first wireless connection of the UE with the first base station. The UE may perform a channel estimation procedure for the first wireless connection to generate a Doppler value based on receiving the indication. The UE may apply the generated Doppler value to a frequency tracking loop or a time tracking loop for communications with a second base station via a second wireless connection, wherein the second base station is operating according to a second RAT.

Abstract: Methods, systems, and devices for wireless communications are described. Generally, a user equipment (UE) may communicate with a first network device in a first communications system (e.g., a non-standalone (NSA) system) prior to initiating a handover to a second communications system (e.g., a standalone (SA) system). In some examples, the UE may receive a first tracking reference signal (TRS) from the first network device using a first transmission configuration indicator (TCI) state. The first network device may include an indication of the first TCI state in a control message. The UE may initiate a handover from the first network device to the second network device. Subsequent to the handover, the UE may receive a second TRS from the second network device. The UE may receive the second TRS using the first TCI state based on determining that one or more antenna port configuration conditions are satisfied.

Abstract: Enhanced inter-RAT and measurement gap operations are disclosed. In one aspect, a device may generate a customized measurement gap for monitoring control signals of another network for inter-RAT procedures. In another aspect, a device may modify, such as extend or shift, a network measurement gap to generate a modified measurement gap for monitoring control signals of another network for inter-RAT procedures. The device may modify the network measurement gap to align the network's measurement gap, such as LTE measurement gap, with a measurement window of another network, such as an SMTC window of a 5G network. Other aspects and features are also claimed and described.

Abstract: Enhanced inter-RAT communication operations are disclosed. In one aspect, a device may identify one or more trigger events for monitoring control signals of another network for inter-RAT procedures, such as monitoring for one or more synchronization signal blocks (SSBs). In another aspect, the device may perform a comparison of multiple SSBs. In another aspect, the device may identify one or more release conditions for releasing local settings data associated with a customized measurement gap. In another aspect, the device may send the local settings data to a server. In another aspect, the device may send an extended signaling message indicating a timing offset between network devices.

Abstract: A method, an electronic device and a readable storage medium for creating a label marking model are disclosed. The method for creating the label marking model includes: obtaining text data and determining a word or phrase to be marked in the text data; according to the word or phrase to be marked, constructing a first training sample of the text data corresponding to a word or phrase replacing task and a second training sample corresponding to a label marking task; training a neural network model with a plurality of the first training samples and a plurality of the second training samples, respectively, until a loss function of the word or phrase replacing task and a loss function of the label marking task satisfy a preset condition, to obtain the label marking model.

Abstract: A display method, an electronic device, and a storage medium, which relate to a field of natural language processing and a field of display. The display method includes: acquiring a content to be displayed; extracting a target term from the content using a term extraction rule; acquiring an annotation information for at least one target term, responsive to an extraction of the at least one target term; and displaying the annotation information for the at least one target term and the content.

Abstract: A display method, a method of training a semantic unit detection model, an electronic device, and a storage medium, which relate to a field of artificial intelligence technology, in particular to fields of natural language processing and machine translation technologies. The display method includes: acquiring a language sequence to be displayed; dividing the language sequence to be displayed into a plurality of semantic units with semantics; and converting the plurality of semantic units into subtitles for display one by one.

Abstract: The present disclosure provides a method and an apparatus for analyzing an intention based on artificial intelligence. The method includes: receiving a query; acquiring a keyword of an intention of the query according to a preset strategy; acquiring a qualifier of the intention of the query according to the keyword based on a syntax tree; and determining the intention of the query according to the keyword and the qualifier.

Abstract: A method for information processing in a user conversation, an electronic device and a storage medium thereof, which relate to the field of artificial intelligence and the natural language processing field, are disclosed. The method may include: acquiring conversation preceding information in a conversation between a first user and a second user; acquiring a target conversation strategy employed by the first user; generating initial reply content with a pre-trained response generating model according to the target conversation strategy and the conversation preceding information; and sending the initial reply content to a client of the first user, so as to display the initial reply content on a conversation interface of the first user with the second user.

Abstract: A method, an electronic device and a readable storage medium for creating a label marking model are disclosed. According to an embodiment, the method for creating the label marking model includes: obtaining text data and determining a word or phrase to be marked in the text data; according to the word or phrase to be marked, constructing a first training sample of the text data corresponding to a word or phrase replacing task and a second training sample corresponding to a label marking task; training a neural network model with a plurality of the first training samples and a plurality of the second training samples, respectively, until a loss function of the word or phrase replacing task and a loss function of the label marking task satisfy a preset condition, to obtain the label marking model. The technical solution may improve the accuracy of the label marking model.

Abstract: A method for human-machine interaction based on a neural network is provided. The method includes: providing a user input as a first input for a neural network system; providing the user input to a conversation control system different from the neural network system; processing the user input by the conversation control system based on information relevant to the user input; providing a processing result of the conversation control system as second input for the neural network system; and generating, by the neural network system, a reply to the user input based on the first and second input.

Abstract: The present disclosure provides a method and an apparatus for analyzing an intention based on artificial intelligence. The method includes: receiving a query; acquiring a keyword of an intention of the query according to a preset strategy; acquiring a qualifier of the intention of the query according to the keyword based on a syntax tree; and determining the intention of the query according to the keyword and the qualifier.