Abstract: A method for processing a virtual item is provided, including: providing a backpack control by the graphical user interface, wherein the backpack control is configured to display a backpack interface in response to a touch operation; in response to at least one first virtual item satisfying a preset condition in the game scene, displaying a pick-up list displaying item information of the first virtual item; determining a target first virtual item from the at least one first virtual item in response to a first touch operation on the pick-up list; displaying an alternative item list showing item information of a second virtual item, wherein the second virtual item is a virtual item in a backpack of the virtual character; and in response to a second touch operation on the alternative item list, determining a target second virtual item, and replacing the second virtual item by the target first virtual item.

Abstract: An uncovering device of a capsule coffee machine, includes a machine body; a first brewing assembly provided in the machine body, the first brewing assembly which includes a brewing head and a brewing seat, a cover body assembly, a sealing cover, a sliding groove extending from the rear side to the front side of the cover body assembly provided in the lower cover, a sliding shaft provided in the sliding cavity, a connecting rod assembly, wherein both ends of the sliding shaft are located at the opposite sides of the sliding groove; wherein one end of the connecting rod assembly is rotatably connected to the sliding shaft through the sliding groove, another end of the connecting rod is rotatably connected to the brewing seat or the brewing head of the first brewing.

Abstract: The present disclosure relates to the technical field of gaming, and provides a gaming live stream control method and device, a computer storage medium, and an electronic apparatus. The gaming live stream control method is applicable to a live stream server or a cloud gaming server, and comprises: acquiring a gaming frame corresponding to a live stream room; receiving a show-controls request sent by a live stream audience member, wherein the show-controls request is used to instruct the live stream server or the cloud gaming server to specify controls information comprised in a gaming live stream frame to be transmitted to the live stream audience member; determining, according to the show-controls request, controls information to be shown, and generating the gaming live stream frame according to the gaming frame and the controls information; and transmitting the gaming live stream frame to the live stream audience member.

Abstract: A method for controlling game object is provided. The method includes: in response to grouping trigger operation, providing a grouping control, wherein the grouping control includes at least one grouping sub-control, each of the at least one grouping sub-control corresponds to an object group, and the object group includes at least one game object; in response to first grouping selection operation, determining a first grouping sub-control in the at least one grouping sub-control; and in response to second grouping selection operation, determining a second object group, and combining at least one game object in a first object group corresponding to the first grouping sub-control into the second object group.

Abstract: A game object control method is provided in embodiments of the present disclosure. The method includes: at least one target game object is determined in at least one game object, in response to object selecting operation. A grouping control is provided in response to object grouping trigger operation. The grouping control includes at least one grouping sub-control. A target grouping sub-control is determined in the at least one grouping sub-control, in response to a group selecting operation, and the at least one target game object is determined as a target group corresponding to the target grouping sub-control. In the present embodiment, by means of a grouping control and a group selecting operation, a group of a target game object can be determined as a target group corresponding to a target grouping sub-control, thereby quick grouping of the at least one game object to improve the operation efficiency of games is realized.

Abstract: The present disclosure relates to an information processing method in a game, which is applied to a mobile terminal for displaying a human-computer interaction interface in a touch screen and includes: obtaining an input fingerprint of a touch medium by means of the touch screen, and calculating similarity between the input fingerprint and a target fingerprint, wherein a mapping relationship exists between target fingerprints and a optional virtual object (S110); in response to detecting that the similarity is greater than a threshold value, obtaining action information of the touch medium on the touch screen, and determining a target virtual object according to the action information (S120); and controlling the optional virtual object corresponding to the target fingerprint to attack the target virtual object (S130).

Abstract: A method and device for selecting a game object and a storage medium are provided. The method includes: in response to an object selection operation acting on a first display area on a graphical user interface, selecting multiple game objects in a game scene; and displaying an object selection control in a second display area of the graphical user interface. Multiple game objects are selected by an object selection operation. A first game object indicator and/or a second game object indicator is further displayed in an object selection control, and respectively corresponds to different game objects or types of game objects.

Abstract: A speech recognition method is provided. The method includes: obtaining a voice signal; processing the voice signal according to a speech recognition algorithm to obtain n candidate recognition results, the candidate recognition results including text information corresponding to the voice signal; identifying a target result from among the n candidate recognition results according to a selection rule selected from among m selection rules, the selection rule having an execution sequence of j, the target result being a candidate recognition result that has a highest matching degree with the voice signal in the n candidate recognition results, an initial value of j being 1; and identifying the target result from among the n candidate recognition results according to a selection rule having an execution sequence of j+1 based on the target result not being identified according to the selection rule having the execution sequence of j.

Abstract: A method is performed at a computer for automatically correcting typographical errors. The computer selects a target word in a target sentence and identifies a target word therein as having a typographical error and first and second sequences of words separated by the target word as context. After identifying, among a database of grammatically correct sentences, a set of sentences having the first and second sequences of words, each sentence including a replacement word, the computer selects a set of candidate grammatically correct sentences whose corresponding replacement words have similarities to the target word above a pre-set threshold, Finally, the computer chooses, among the set of candidate grammatically correct sentences, a fittest grammatically correct sentence according to a linguistic model and replaces the target word in the target sentence with the replacement word within the fittest grammatically correct sentence.

Abstract: A speech recognition method is provided. The method includes: obtaining a voice signal; processing the voice signal according to a speech recognition algorithm to obtain n candidate recognition results, the candidate recognition results including text information corresponding to the voice signal; identifying a target result from among the n candidate recognition results according to a selection rule selected from among m selection rules, the selection rule having an execution sequence of j, the target result being a candidate recognition result that has a highest matching degree with the voice signal in the n candidate recognition results, an initial value of j being 1; and identifying the target result from among the n candidate recognition results according to a selection rule having an execution sequence of j+1 based on the target result not being identified according to the selection rule having the execution sequence of j.

Abstract: A phase change material for a phase change memory and a preparing method thereof. The phase change material for a phase change memory has a chemical formula of Sc100-x-y-zGexSbyTez, wherein 0?x?60, 0?y?90, 0<z?65, 0<100-x-y-z<100. The phase change material for a phase change memory according to the present invention is capable of repeatedly changing phases. The Sc100-x-y-zGexSbyTez has two different resistance value states, i.e., a high resistance state and a low resistance state, and a reversible transformation between the high resistance state and the low resistance state can be achieved by being applied a pulse electrical signal thereto, which satisfies basic requirements of a storage material for the phase change memory.

Abstract: An Sb—Te—Ti phase-change thin-film material applicable to a phase-change memory and preparation thereof. The Sb—Te—Ti phase-change memory material is formed by doping an Sb—Te phase-change material with Ti, Ti forms bonds with both Sb and Te, and the Sb—Te—Ti phase-change memory material has a chemical formula SbxTeyTi100?x?y, where 0<x<80 and 0<y<100?x. When the Sb—Te—Ti phase-change memory material is a Ti—Sb2Te3 phase-change memory material, Ti atoms replace Sb atoms, and phase separation does not occur. The crystallization temperature of the Sb—Te—Ti phase-change memory material is significantly risen, retention is improved, and thermal stability is enhanced; meanwhile, the amorphous state resistance decreases, and the crystalline state resistance increases; and the Sb—Te—Ti phase-change memory material has wide application in phase-change memories.

Abstract: A method is performed at a computer for automatically correcting typographical errors. The computer selects a target word in a target sentence and identifies a target word therein as having a typographical error and first and second sequences of words separated by the target word as context. After identifying, among a database of grammatically correct sentences, a set of sentences having the first and second sequences of words, each sentence including a replacement word, the computer selects a set of candidate grammatically correct sentences whose corresponding replacement words have similarities to the target word above a pre-set threshold, Finally, the computer chooses, among the set of candidate grammatically correct sentences, a fittest grammatically correct sentence according to a linguistic model and replaces the target word in the target sentence with the replacement word within the fittest grammatically correct sentence.

Abstract: A phase change material for a phase change memory and a preparing method thereof. The phase change material for a phase change memory has a chemical formula of Sc100-x-y-zGexSbyTez, wherein 0?x?60, 0?y?90, 0<z?65, 0<100-x-y-z<100. The phase change material for a phase change memory according to the present invention is capable of repeatedly changing phases. The Sc100-x-y-zGexSbyTez has two different resistance value states, i.e., a high resistance state and a low resistance state, and a reversible transformation between the high resistance state and the low resistance state can be achieved by being applied a pulse electrical signal thereto, which satisfies basic requirements of a storage material for the phase change memory.

Abstract: A phase change memory cell and a preparation method thereof. A phase change material layer having a thickness equal to the size of a single unit cell or a plurality of unit cells is adopted, the phase change material layer fundamentally expresses interfacial characteristics, and body material characteristics are weakened, such that a two-dimensional phase change memory cell storing information through change of interface resistance and having a high density, low power consumption and high speed is prepared.

Abstract: The present application discloses a method, an electronic system and a non-transitory computer readable storage medium for recognizing audio commands in an electronic device. The electronic device obtains audio data based on an audio signal provided by a user and extracts characteristic audio fingerprint features from the audio data. The electronic device further determines whether the corresponding audio signal is generated by an authorized user by comparing the characteristic audio fingerprint features with an audio fingerprint model for the authorized user and with a universal background model that represents user-independent audio fingerprint features, respectively. When the corresponding audio signal is generated by the authorized user of the electronic device, an audio command is extracted from the audio data, and an operation is performed according to the audio command.

Abstract: A cable connector comprises: an insulative housing, a front portion of the insulative housing is provided with a mating cavity, and a rear portion of the insulative housing is provided with a receiving cavity, a middle portion of the insulative housing is vertically provided with a spacing wall to separate the mating cavity from the receiving cavity in a front-rear direction, the rear portion of the insulative housing is provided with four fixing holes communicating with the receiving cavity; two circuit boards arranged and spaced apart in an up-down direction, each circuit board comprises a mating portion protruding forwardly into the mating cavity and a wire connection portion positioned in the receiving cavity; a plurality of wires electrically connected to the wire connection portions of the circuit boards; an outer molding formed in the receiving cavity by injection molding and correspondingly formed with four fixing protrusions engaging with the four fixing hole; the outer molding covers the wires there

Abstract: A method is performed at a device having one or more processors and memory. The device establishes a first-level Deep Neural Network (DNN) model based on unlabeled speech data, the unlabeled speech data containing no speaker labels and the first-level DNN model specifying a plurality of basic voiceprint features for the unlabeled speech data. The device establishes a second-level DNN model by tuning the first-level DNN model based on labeled speech data, the labeled speech data containing speech samples with respective speaker labels, wherein the second-level DNN model specifies a plurality of high-level voiceprint features. Using the second-level DNN model, registers a first high-level voiceprint feature sequence for a user based on a registration speech sample received from the user. The device performs speaker verification for the user based on the first high-level voiceprint feature sequence registered for the user.

Abstract: The present invention, pertaining to the field of speech recognition, discloses a reminder setting method and apparatus. The method includes: acquiring speech signals; acquiring time information in speech signals by using keyword recognition, and determining reminder time for reminder setting according to the time information; acquiring text sequence corresponding to the speech signals by using continuous speech recognition, and determining reminder content for reminder setting according to the time information and the text sequence; and setting a reminder according to the reminder time and the reminder content.

Abstract: An automatic speech recognition method includes at a computer having one or more processors and memory for storing one or more programs to be executed by the processors, obtaining a plurality of speech corpus categories through classifying and calculating raw speech corpus; obtaining a plurality of classified language models that respectively correspond to the plurality of speech corpus categories through a language model training applied on each speech corpus category; obtaining an interpolation language model through implementing a weighted interpolation on each classified language model and merging the interpolated plurality of classified language models; constructing a decoding resource in accordance with an acoustic model and the interpolation language model; and decoding input speech using the decoding resource, and outputting a character string with a highest probability as a recognition result of the input speech.