Abstract: Methods and apparatuses are provided for performing sequence to sequence (Seq2Seq) speech recognition training performed by at least one processor. The method includes acquiring a training set comprising a plurality of pairs of input data and target data corresponding to the input data, encoding the input data into a sequence of hidden states, performing a connectionist temporal classification (CTC) model training based on the sequence of hidden states, performing an attention model training based on the sequence of hidden states, and decoding the sequence of hidden states to generate target labels by independently performing the CTC model training and the attention model training.

Abstract: A method, computer program, and computer system is provided for synthesizing speech at one or more speeds. A context associated with one or more phonemes corresponding to a speaking 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 voice sample corresponding to the speaking voice is synthesized using the generated mel-spectrogram features.

Abstract: An apparatus and a method include receiving an input audio signal to be processed by a multi-band synchronized neural vocoder. The input audio signal is separated into a plurality of frequency bands. A plurality of audio signals corresponding to the plurality of frequency bands is obtained. Each of the audio signals is downsampled, and processed by the multi-band synchronized neural vocoder. An audio output signal is generated.

Abstract: The present disclosure relates to optical lens, and provides a camera optical lens including from an object side to an image side in sequence: a first lens having a positive refractive power, a second lens, a third lens, a fourth lens, a fifth lens, a sixth lens, a seventh lens, and an eighth lens; wherein the camera optical lens satisfies the following conditions: 0.95?f/TTL; ?4.00?f2/f??1.90; and 0.25?(R15+R16)/(R15?R16)?0.90. The camera optical lens can achieve good optical performance while meeting design requirements for a long focal length and ultra-thinness.

Abstract: A method, computer program, and computer system is provided for automated speech recognition. Audio data corresponding to one or more speakers is received. Covariance matrices of target speech and noise associated with the received audio data are estimated based on a gated recurrent unit-based network. A predicted target waveform corresponding to a target speaker from among the one or more speakers is generated by a minimum variance distortionless response function based on the estimated covariance matrices.

Abstract: Nucleic acid based vaccine constructs encoding Lyssaviral antigens are useful in preventing and treating diseases. Self-amplifying RNA molecules encoding Lyssaviral antigens provide potent and long-lasting immunity.

Abstract: A camera optical lens is provided. The camera optical lens includes, from an object side to an image side, a first lens, a second lens having a negative refractive power, a third lens, a fourth lens, a fifth lens, a sixth lens, a seventh lens, an eighth lens, and a ninth lens. The camera optical lens satisfies following conditions: 2.00?f1/f?5.50; and 2.00?d7/d8?10.00, where f denotes a focal length of the camera optical lens, f1 denotes a focal length of the first lens, d7 denotes an on-axis thickness of the fourth lens, and d8 denotes an on-axis distance from an image side surface of the fourth lens to an object side surface of the fifth lens. The camera optical lens according to the present disclosure satisfies design requirements for large-aperture, wide-angle, and ultra-thin lenses while achieving good optical performance.

Abstract: An antenna apparatus and a terminal, where the antenna apparatus includes an antenna body and at least one stub, where a feed terminal is disposed on the antenna body, one end of the stub is electrically coupled to a coupling point between the feed terminal and a first open-circuit end of the antenna body, and the other end of the stub is an open-circuit end, and an antenna body length between the coupling point and the feed terminal is a half of a wavelength corresponding to a specified operating frequency, and a length of the stub is one quarter of the wavelength corresponding to the specified operating frequency.

Abstract: A method, a computer readable medium, and a computer system are provided for singing voice conversion. Data corresponding to a singing voice is received. One or more features and pitch data are extracted from the received data using one or more adversarial neural networks. One or more audio samples are generated based on the extracted pitch data and the one or more features.

Abstract: Methods and apparatuses are provided for performing sequence to sequence (Seq2Seq) speech recognition training performed by at least one processor. The method includes acquiring a training set comprising a plurality of pairs of input data and target data corresponding to the input data, encoding the input data into a sequence of hidden states, performing a connectionist temporal classification (CTC) model training based on the sequence of hidden states, performing an attention model training based on the sequence of hidden states, and decoding the sequence of hidden states to generate target labels by independently performing the CTC model training and the attention model training.

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 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 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 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: 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.