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, computer program, and computer system is provided for converting a singing voice of a first person associated with a first speaker to a singing voice of a second person using a speaking voice of the second person associated with a second speaker. A context associated with one or more phonemes corresponding to the singing voice of a first person 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, the target acoustic frames, and a sample of the speaking voice of the second person. A sample corresponding to the singing voice of a first person is converted to a sample corresponding to the second singing voice using the generated mel-spectrogram features.

Abstract: A neural network training method is provided. The method includes obtaining an audio data stream, performing, for different audio data of each time frame in the audio data stream, feature extraction in each layer of a neural network, to obtain a depth feature outputted by a corresponding time frame, fusing, for a given label in labeling data, an inter-class confusion measurement index and an intra-class distance penalty value relative to the given label in a set loss function for the audio data stream through the depth feature, and updating a parameter in the neural network by using a loss function value obtained through fusion.

Abstract: An example system includes an electronic device and a server. The electronic device includes a display; a first communicator; and a first controller configured to: control to transmit, to the server, location data identifying locations of the electronic device. The server includes a second communicator; and a second controller configured to: control to receive the location data; identify a course of travel; link photograph images to locations on the course of travel; and control to transmit to the electronic device the course of travel and the photograph images. The first controller of the electronic device is configured to control to receive the course of travel and the photograph images and to control to display on the display, at the same time, a map image, the course of travel, and one or more of the photograph images linked to a selected location on the course of travel.

Abstract: An antenna of a mobile terminal is provided. At least two slots are disposed in a metal bezel of the mobile terminal, and the two slots divide the metal bezel into a first metal section, a second metal section, and a third metal section. A radiating element of the antenna includes the second metal section located between the two slots, a first conductor, and a second conductor. The first conductor and the second conductor are separately connected to the second metal section. A feed point is connected to the first conductor by using a matching network. A ground point is connected to the second conductor to form a loop antenna. An electrical length path of current from the feed point to the second metal section is not equal to an electrical length path of current from the ground point to the second metal section.

Abstract: Techniques and constructs can reduce the time required to determine solutions to optimization problems such as training of neural networks. Modifications to a computational model can be determined by a plurality of nodes operating in parallel. Quantized modification values can be transmitted between the nodes to reduce the volume of data to be transferred. The quantized values can be as small as one bit each. Quantization-error values can be stored and used in quantizing subsequent modifications. The nodes can operate in parallel and overlap computation and data transfer to further reduce the time required to determine solutions. The quantized values can be partitioned and each node can aggregate values for a corresponding partition.

Abstract: A method of attention-based end-to-end (A-E2E) automatic speech recognition (ASR) training, includes performing cross-entropy training of a model, based on one or more input features of a speech signal, determining a posterior probability vector at a time of a first wrong token among one or more output tokens of the model of which the cross-entropy training is performed, and determining a loss of the first wrong token at the time, based on the determined posterior probability vector. The method further includes determining a total loss of a training set of the model of which the cross-entropy training is performed, based on the determined loss of the first wrong token, and updating the model of which the cross-entropy training is performed, based on the determined total loss of the training set.

Abstract: A model training method includes obtaining an image sample set and brief-prompt information; generating a content mask set according to the image sample set and the brief-prompt information; generating a to-be-trained image set according to the content mask set; obtaining, based on the image sample set and the to-be-trained image set, a predicted image set through a to-be-trained information synthesis model, the predicted image set comprising at least one predicted image, the predicted image being in correspondence to the image sample; and training, based on the predicted image set and the image sample set, the to-be-trained information synthesis model by using a target loss function, to obtain an information synthesis model.

Abstract: An antenna system and a terminal device. The, where the antenna system includes a first feed point, a first ground point, a second feed point, a second ground point, a third ground point, a fourth ground point, a first radiator, a second radiator, a first resonance structure, and a second resonance structure, where the first feed point is coupled to the first radiator, the second feed point is coupled to the second radiator, the first radiator is coupled to the first ground point, and the second radiator is coupled to the second ground point, the first resonance structure is electromagnetically coupled to the first radiator at a first distance from the first radiator, and the second resonance structure is electromagnetically coupled to the second radiator at a second distance from the second radiator.

Abstract: A method of performing speech synthesis, includes encoding character embeddings, using any one or any combination of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), applying a relative-position-aware self attention function to each of the character embeddings and an input mel-scale spectrogram, and encoding the character embeddings to which the relative-position-aware self attention function is applied. The method further includes concatenating the encoded character embeddings and the encoded character embeddings to which the relative-position-aware self attention function is applied, to generate an encoder output, applying a multi-head attention function to the encoder output and the input mel-scale spectrogram to which the relative-position-aware self attention function is applied, and predicting an output mel-scale spectrogram, based on the encoder output and the input mel-scale spectrogram to which the multi-head attention function is applied.

Abstract: A communications terminal includes a multiple-input multiple-output antenna system. The multiple-input multiple-output antenna system includes a first antenna module, a second antenna module, and a first ground structure. The first antenna module includes a first radiator configured to form a first MIMO antenna and a second radiator configured to form a GPS antenna, and a first slit is provided between the first radiator and the second radiator. The second antenna module includes a third radiator configured to form a low frequency antenna and a fourth radiator configured to form a second MIMO antenna. The second radiator is connected to the third radiator. One end of the first ground structure is connected to the second radiator or the third radiator, and another end is connected to a ground plane of the communications terminal.

Abstract: Methods and apparatuses are provided for performing acoustic to word (A2W) speech recognition training performed by at least one processor. The method includes initializing, by the at least one processor, one or more first layers of a neural network with phone based Connectionist Temporal Classification (CTC), initializing, by the at least one processor, one or more second layers of the neural network with grapheme based CTC, acquiring, by the at least one processor, training data and performing, by the at least one processor, A2W speech recognition training based the initialized one or more first layers and one or more second layers of the neural network using the training data.

Abstract: An image white balance processing method is provided. The image white balance processing method includes: calculating color coordinate points; when it is determined that the color coordinate points are in a first given region, calculating a plurality of weighted averages according to a plurality of coordinate components and a plurality of weight values of color coordinate points of a white given image region, and when it is determined that the color coordinate points are in a second given region, calculating a plurality of averages according to a plurality of coordinate components of color coordinate points of a green given image region; calculating an estimated coordinate point; and calculating a plurality of white balance gains according to the number of a plurality of white given image regions and green given image regions, the plurality of weighted averages, and the estimated coordinate point to compensate for the plurality of given image regions.

Abstract: The embodiments of the present disclosure disclose a computer-implemented method, a system, and a computer program product for distributing data on multiple servers to multiple nodes in a cluster. In the method, each of M servers is instructed to divide data thereon into N data segments. M and N are integers greater than one. The M servers are instructed to send N×M data segments on the M servers to N nodes in a cluster concurrently. For each of the M servers, the N data segments are sent respectively to the N nodes. When any given node in the cluster receives a data piece of a data segment from a server of the M servers, the given node is instructed to transmit the received data piece to remaining nodes in the cluster other than the given node.

Abstract: An example system includes an electronic device and a server. The electronic device includes a display; a first communicator; and a first controller configured to: control to transmit, to the server, location data identifying locations of the electronic device. The server includes a second communicator; and a second controller configured to: control to receive the location data; identify a course of travel; link photograph images to locations on the course of travel; and control to transmit to the electronic device the course of travel and the photograph images. The first controller of the electronic device is configured to control to receive the course of travel and the photograph images and to control to display on the display, at the same time, a map image, the course of travel, and one or more of the photograph images linked to a selected location on the course of travel.

Abstract: Provided is a system and method for increasing file transmission speed of a server, and a method for replicating a data object over a plurality of nodes. The system includes a server communicatively coupled to a plurality of nodes. The server may detect a plurality of nodes. The server may determine that a data object stored by the server is to be replicated to the plurality of nodes. The server may divide the data object into a plurality of data pieces. The server may send a different data piece to each node of the plurality of nodes. Each node may receive the different data piece from the server. Each node may send a copy of the received data piece to all other nodes. Each node may receive copies of all other data pieces from the other nodes. Each node may replicate a full copy of the data object.

Abstract: The invention provides, inter alia, improved replicons and vectors encoding them, where the replicons provide sustained expression of an encoded protein. These replicons comprise flavivirus replicases and heterologous protein coding sequences, wherein the heterologous protein coding sequences are flanked by separation sequences for improved efficacy. These nucleic acids provided by the invention, including self-replicating RNAs provided by the invention, are useful in methods of protein expression, such as for vaccines (e.g., for methods of immunization), as well as expression of therapeutic proteins, such as antibodies (e.g., for methods of treatment).

Abstract: Compounds useful as components of immunogenic compositions for the induction of an immunogenic response in a subject against viral infection, methods for their use in treatment, and processes for their manufacture are provided herein. The compounds comprise a nucleic acid construct comprising a sequence which encodes a Zika virus antigen. A particular embodiment is a nucleic acid-based vaccine construct encoding a polypeptide comprising a full-length Zika virus prME antigen. A particular embodiment is a self-replicating RNA molecule comprising a construct encoding a polypeptide comprising a full-length Zika virus prME antigen.

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: An electronic apparatus controls a peripheral device by using a relay apparatus. The electronic apparatus includes an interface connected to the peripheral device; a communication unit that performs communication with the relay apparatus; a receiver that receives a control signal for controlling the electronic apparatus; and a controller that, when the control signal is received, performs an operation based on the control signal, and controls the communication unit to transmit information about the performed operation and information about the peripheral device to the relay apparatus in order to control the peripheral device to perform an operation that corresponds to the performed operation.