Abstract: A method, computer program, and computer system is provided for converting a singing first singing voice associated with a first speaker to a second singing voice associated with a second speaker. A context associated with one or more phonemes corresponding to the first singing voice is encoded, and the one or more phonemes are aligned to one or more target acoustic frames based on the encoded context. One or more mel-spectrogram features are recursively generated from the aligned phonemes and target acoustic frames, and a sample corresponding to the first singing voice is converted to a sample corresponding to the second singing voice using the generated mel-spectrogram features.

Abstract: Method and apparatus for automatically predicting lexical sememes using a lexical dictionary, comprising inputting a word, retrieving the word's semantic definition and sememes corresponding to the word from an online dictionary, setting each of the retrieved sememes as a candidate sememe, inputting the word's semantic definition and candidate sememe, and estimating the probability that the candidate sememe can be inferred from the word's semantic definition.

Abstract: A camera optical lens includes first to fourth lenses from an object side to an image side, with first and fourth lenses having negative refractive power, and a third lens having positive refractive power, and satisfies ?3.50?f1/f??2.00; 0.55?f3/f?0.75; 5.00?d3/d4?15.00; 5.00?d5/d6?35.00; ?20.00?(R3+R4)/(R3?R4)??3.00; and ?5.00?R1/R2??2.00, where f, f1, and f3 respectively denote focal lengths of the camera optical lens, the first lens, and the third lens, d3 and d5 respectively denote on-axis thicknesses of second and third lenses, d4 and d6 respectively denote a distance between second and third lenses and a distance between third and fourth lenses, R3 and R4 respectively denote curvature radii of object side and image side surfaces of the second lens, and R1 and R2 denotes curvature radii of object side and image side surfaces of the first lens, thereby having good optical performance while meeting design requirements of a wide angle and ultra-thinness.

Abstract: A camera optical lens includes first to fifth lenses from an object side to an image side, which are first and fourth lenses having positive refractive power, and second, third and fifth lenses having negative refractive power. The camera optical lens satisfies 0.90?f1/f?1.30; ?5.00?f3/f??2.50; 10.00?d1/d2?25.00; and 0?(R7+R8)/(R7?R8)?0.90, where f, f1 and f3 respectively denote focal lengths of the camera optical lens, the first lens, and the third lens, R7 denotes a curvature radius of an object side surface of the fourth lens, R8 denotes a curvature radius of an image side surface of the fourth lens, d1 denotes an on-axis thickness of the first lens, and d2 denotes an on-axis distance from an image side surface of the first lens to an object side surface of the second lens. The camera optical lens has good optical performance and satisfies design requirements of a large angle, a wide angle and ultra-thinness.

Abstract: A method, computer system, and computer readable medium are provided for automatic speech recognition. Video data and audio data corresponding to one or more speakers is received. A minimum variance distortionless response function is applied to the received audio and video data. A predicted target waveform corresponding to a target speaker from among the one or more speakers is generated based on back-propagating the output of the applied minimum variance distortionless response function.

Abstract: A camera optical lens includes a first lens having a positive refractive power, a second lens having a refractive power, a third lens having a negative refractive power, a fourth lens having a positive refractive power, and a fifth lens having a negative refractive power, which are sequentially arranged from an object side to an image side. 0.90?f1/f?1.20, 50.00?(R3+R4)/(R3?R4)?30.00, 3.00?d5/d6?10.00, and ?15.00?(R5+R6)/(R5?R6)??3.00. f denotes a focal length of the camera optical lens, f1 denotes a focal length of the first lens, R3 denotes a curvature radius of an object-side surface of the second lens, R4 denotes a curvature radius of an image-side surface of the second lens, and R5 denotes a curvature radius of an object-side surface of the third lens. The camera optical lens has good optical performance and meets the design requirements of a large aperture, a wide angle, and ultra-thinness.

Abstract: An approach to managing images in a registry constructed as a multi-layer file system are disclosed. The method comprises receiving a first request for downloading a first image, the first request comprising a download policy. The method also comprises obtaining a plurality of compositions of layers of the first image, wherein content of layers specified by each composition of layers collectively constitute content of the first image. The method also comprises selecting a composition of layers from the plurality of compositions of layers of the first image based on the download policy. The method also comprises sending content of layers specified by the selected composition of layers.

Abstract: A method for authentication data transmission and a system thereof are provided. The method is operated in a computer system that is connected to a biometric device, and a secure channel is established there-between according to a security protocol. The computer system can receive encrypted biometric feature data from the biometric device based on a request. In a secure environment built in the computer system, the biometric feature data is decrypted and biometric features can be extracted. A comparison result is generated after comparing the biometric features with feature data in a database. The comparison result can be transmitted to the biometric device. The comparison result is then encrypted in the biometric device according to the security protocol.

Abstract: A speech keyword recognition method includes: obtaining first speech segments based on a to-be-recognized speech signal; obtaining first probabilities respectively corresponding to the first speech segments by using a preset first classification model. A first probability of a first speech segment is obtained from probabilities of the first speech segment respectively corresponding to pre-determined word segmentation units of a pre-determined keyword.

Abstract: This application provides a speech recognition and apparatus and a neural network training method and apparatus, and relates to the field of Artificial Intelligence (AI) technologies. The neural network training method is performed by an electronic device and includes: obtaining sample data, the sample data including a mixed speech spectrum and a labeled phoneme thereof; extracting a target speech spectrum from the mixed speech spectrum by using a first subnetwork; adaptively transforming the target speech spectrum by using a second subnetwork, to obtain an intermediate transition representation; performing phoneme recognition based on the intermediate transition representation by using a third subnetwork; and updating parameters of the first subnetwork, the second subnetwork, and the third subnetwork according to a result of the phoneme recognition and the labeled phoneme.

Abstract: A method, computer system, and computer readable medium are provided for activating speech recognition based on keyword spotting (KWS). Waveform data corresponding to one or more speakers is received. One or more direction features are extracted from the received waveform data. One or more keywords are determined from the received waveform data based on the one or more extracted features. Speech recognition is activated based on detecting the determined keyword.

Abstract: The present disclosure discloses a multi-path image processing apparatus. An image merging circuit is configured to receive image frames that at least one of the image frames has a largest row number, generate redundant pixel row for each of the image frames that has a row number smaller than the largest row number such that the row number of each of the image frames equals to the largest row number, generate redundant pixel columns for each of the image frames having the number thereof determined by a size of a largest operation window, and merge each two of the image frames through the redundant columns thereof to generate a merged image frame. An image processing circuit performs image processing procedure on the merged image frame to generate a processed merged image frame, wherein at least a part of the image processing procedure is operated according to the largest operation window. An image segmentation circuit segments the processed merged image frame to generate processed image frames.

Abstract: A firmware updating system and method are provided. The firmware updating method includes configuring a host to digitally sign a firmware to be updated, and configuring an electronic device to perform an authorization verification on an update tool, and only the update tool that passes the verification has an update permission. The update tool uses an encryption algorithm to encrypt the firmware to be updated that includes a digital signature. After the encryption is completed, the host sends the update tool to the electronic device through the update tool. The electronic device then uses a decryption algorithm to decrypt the received firmware to obtain the firmware to be updated including the digital signature, and write the firmware to be updated into a firmware storage area to be updated. The electronic device then verifies the digital signature in the firmware to be updated.

Abstract: A method, computer program, and computer system for separating a target voice from among a plurality of speakers is provided. Video data associated with the plurality of speakers and audio data associated with each of the one or more speakers are received. Video feature data is extracted from the received video data. The target voice is identified from among the plurality of speakers based on the received audio data and the extracted video feature data.

Abstract: A method and apparatus include receiving a text input that includes a sequence of text components. Respective temporal durations of the text components are determined using a duration model. A spectrogram frame is generated based on the duration model. An audio waveform is generated based on the spectrogram frame. Video information is generated based on the audio waveform. The audio waveform is provided as an output along with a corresponding video.

Abstract: An antenna apparatus includes a feeding antenna inside an electronic device and one or more antenna elements, such as a floating metal antenna, disposed on a rear cover of the electronic device. The floating metal antenna and a feeding antenna inside the electronic device may form a coupling antenna structure. The feeding antenna may be an antenna fastened on an antenna support (which may be referred to as a support antenna). The feeding antenna may alternatively be a slot antenna formed by slitting on a metal middle frame of the electronic device. The antenna apparatus may be implemented in limited design space, thereby effectively saving antenna design space inside the electronic device. The antenna apparatus may generate excitation of a plurality of resonance modes, so that antenna bandwidth and radiation characteristics can be improved.

Abstract: This application relates to a method of extracting an inter channel feature from a multi-channel multi-sound source mixed audio signal performed at a computing device.

Abstract: A method, computer program, and computer system is provided for converting a singing first singing voice associated with a first speaker to a second singing voice associated with a second speaker. A context associated with one or more phonemes corresponding to the first singing voice is encoded, and the one or more phonemes are aligned to one or more target acoustic frames based on the encoded context. One or more mel-spectrogram features are recursively generated from the aligned phonemes and target acoustic frames, and a sample corresponding to the first singing voice is converted to a sample corresponding to the second singing voice using the generated mel-spectrogram features.

Abstract: A method of sharing a function of a device, the method including detecting at least one device from among a plurality of devices through a first device connected to the plurality of devices through a plurality of networks, wherein the detecting is performed by a second device in the plurality of devices; interworking the second device with a third device in the detected at least one device, through the first device; and using, by the second device, a function of the third device through the first device.

Abstract: The techniques described herein improve methods to equip a computing device to conduct automatic speech recognition (“ASR”) in talker-independent multi-talker scenarios. In some examples, permutation invariant training of deep learning models can be used for talker-independent multi-talker scenarios. In some examples, the techniques can determine a permutation-considered assignment between a model's estimate of a source signal and the source signal. In some examples, the techniques can include training the model generating the estimate to minimize a deviation of the permutation-considered assignment. These techniques can be implemented into a neural network's structure itself, solving the label permutation problem that prevented making progress on deep learning based techniques for speech separation. The techniques discussed herein can also include source tracing to trace streams originating from a same source through the frames of a mixed signal.