Abstract: Embodiments of the present disclosure provide a method and device for playing a video. The method comprises: in the process of playing a video, displaying a first subtitle in a subtitle component displayed in a playback interface of the video, and playing a first audio corresponding to the first subtitle; in response to a first trigger operation of a user on the subtitle component, displaying a first pop-up window, the first pop-up window being used to switch display of the first subtitle to the second subtitle; in response to a second trigger operation of the user on the first pop-up window, switching to display the second subtitle in the subtitle component, and playing a second audio corresponding to the second subtitle. The video playback method and device provided by the embodiments of the present disclosure can solve the issues that users cannot understand subtitles and audios in the process of watching videos, thereby improving the users' experience.

Abstract: Embodiments of the present disclosure relate to feature crossing for machine learning. According to example embodiments of the present disclosure, a method comprises determining a semantic correlation relationship between a plurality of feature categories, the semantic correlation relationship indicating respective degrees of semantic correlation between respective pairs of feature categories among the plurality of feature categories; obtaining at least two features classified in at least two of the plurality of feature categories for machine learning; and performing feature crossing on the at least two features based on the semantic correlation relationship.

Abstract: A method is proposed for sample processing. A first group of data are received, here data in the first group of data comprises a sample and a classification of the sample, and the classification belonging to a first group of classifications in a plurality of classifications associated with the data. A plurality of data with the classification are selected from the first group of data. A first and a second loss function are determined for training a classification model that represents an association relationship between samples and classifications of the samples based on a plurality of samples comprised in the plurality of data and the classification, the first and second loss functions represent classification accuracy and a feature distribution for the classification model. The classification model is trained based on the first and second loss functions. Therefore, the accuracy of the classification model may be increased.

Abstract: Embodiments of the present disclosure relate to validation of unsupervised adaptive models. According to example embodiments of the present disclosure, unlike methods validating with the seen target data, the present disclosure synthesizes new samples by mixing the target samples and pseudo labels. The accuracy between model predictions of mixed samples and the mixed labels are measured for model selection, and the accuracy score may be called PseudoMix. PseudoMix enjoys the combined inductive bias of previous methods. Experiments demonstrate that PseudoMix can keep state-of-the-art performance across different validation settings.

Abstract: Disclosed are a temperature measurement circuit and method. The circuit includes a first temperature sensing circuit, a second temperature sensing circuit and a data processing unit. The first temperature sensing circuit is configured to generate a first measurement signal for characterizing a temperature based on an inputted first current signal, a magnitude of the first current signal being correlated to temperature. The second temperature sensing circuit is configured to generate a second measurement signal for characterizing the temperature based on an inputted second current signal, the second current signal being independent of temperature. The data processing unit is configured to determine a current temperature based on a first characteristic parameter corresponding to the first measurement signal and a second characteristic parameter corresponding to the second measurement signal.

Abstract: Generating a multi-dimensional video using a multi-dimensional video generative model for, including, but not limited to, at least one of static portrait animation, video reconstruction, or motion editing. The method including providing data into the multi-dimensionally aware generator of the multi-dimensional video generative model, and generating the multi-dimensional video from the data by the multi-dimensionally aware generator.

Abstract: The present disclosure describes techniques for guaranteeing online services based on predicting failures of storage devices. Statistical data may be extracted on a regular basis by each of a plurality of storage devices. Each of the plurality of storage devices may comprise a set of NAND dies. Each of the set of NAND dies may be configured to measure and track a set of metrics indicating characteristics of each NAND die. Prediction data indicating potential failures of the plurality of storage devices may be generated. The prediction data may be shared with a host on a periodic basis. A strategy of decommissioning an aged storage device and adding a new storage device based on the prediction data may be created by the host. The data migration to the new storage device may be implemented.

Abstract: The present disclosure provides a data processing method and apparatus, an electronic device, and a storage medium. The data processing provided by the present disclosure includes: receiving a first request message from a first device, where the first request message includes a first address aligned with a first data length and a first size in a unit of the first data length; converting the first address into a second address aligned with a second data length, where the second data length is greater than the first data length; converting the first size into a second size in a unit of the second data length; and sending a second request message to a second device, where the second request message includes the second address and the second size.

Abstract: The present disclosure provides systems and methods for video generation corresponding to a user input. Given a user input, a story video with content relevant to the user input can be generated. One aspect includes a computing system comprising a processor and memory. The processor can be configured to execute a program using portions of the memory to receive the user input, generate a story text based on the user input, generate a plurality of story images based on the story text, and output a story including the story text and a story video having content corresponding to the story text, wherein the story video includes the plurality of story images. Additionally or alternatively, the story video can include audio data and a plurality of generated animated videos, each animated video corresponding to a story image in the plurality of story images.

Abstract: A method of generating a stylized 3D avatar is provided. The method includes receiving an input image of a user, generating, using a generative adversarial network (GAN) generator, a stylized image, based on the input image, and providing the stylized image to a first model to generate a first plurality of parameters. The first plurality of parameters include a discrete parameter and a continuous parameter. The method further includes providing the stylized image and the first plurality of parameters to a second model that is trained to generate an avatar image, receiving, from the second model, the avatar image, comparing the stylized image to the avatar image, based on a loss function, to determine an error, updating the first model to generate a second plurality of parameters that correspond to the first plurality of parameters, based on the error, and providing the second plurality of parameters as an output.

Abstract: The present disclosure describes techniques for implementing instant corruption detection and recovery. A plurality of streams may be created in a storage device. Each of the plurality of streams may contain a sequence of metadata nodes of a same type. Each of the plurality of streams may maintain an initial state, a sequence of delta modifications to the initial state, and an actual state for each of the sequence of metadata nodes. A checking and recovery function associated with a particular stream among the plurality of streams may be determined. The checking and recovery function may comprise checking logic configured to detect corruptions by checking modification operations associated with metadata nodes in the particular stream. The checking and recovery function may further comprise recovery logic configured to perform recoveries from the corruptions. The checking and recovery function associated with the particular stream may be implemented in the storage device.

Abstract: A system includes a first hardware architecture and computational storage. The computational storage includes a second hardware architecture, and memory storing instructions that, when executed by the second hardware architecture, causes the system to perform a first set of operations. The first set of operations include receiving instructions from the first hardware architecture, performing one or more computations on data stored in the second hardware architecture, based on the received instructions, and transmitting a result to the first hardware architecture, based on the one or more performed computations.

Abstract: A method for adaptive mapping for data compression includes determining an input/output (I/O) request pattern, dynamically switching between a segment mapping mode and a flat hash table mapping mode based on the determined I/O request pattern, updating a shared mapping table for the segment mapping mode and the flat hash table mapping mode, and adjusting an entry of the mapping table based on the determined I/O request pattern and a status of the entry.

Abstract: Example aspects include techniques for implementing real-time and low-latency synthesis of audio. These techniques may include generating a frame by sampling audio input in increments equal to a buffer size of until a threshold corresponding to a frame size used to train a machine learning (ML) model is reached, detecting feature information within the frame, determining, by the ML model, control information for audio reproduction based on the feature information. In addition, the techniques may include generating filtered noise information by inverting the noise magnitude control information using an overlap and add technique, generating, based on the control information, additive harmonic information by combining a plurality of scaled wavetables, and rendering audio output based on the filtered noise information and the additive harmonic information.

Abstract: Provided are a video processing method and apparatus, an electronic device, a storage medium and a program product. The method includes steps described below. A to-be-processed video is acquired, and a first face key point of a first target object in the to-be-processed video is recognized, where the first face key point corresponds to a mask key point in a three-dimensional human face mask effect; and the three-dimensional human face mask effect is added to video frames of the to-be-processed video to obtain a target video, where the mask key point in the three-dimensional human face mask effect moves with the corresponding first face key point.

Abstract: A method for accessing blocks of a solid state drive is described. A starting position is received, where the starting position identifies a first block of a contiguous block region within a namespace of the solid state drive. The contiguous block region is to be accessed according to a single input/output operation and the namespace comprises two dimensions of logical address space with respective indices for indexing blocks within a corresponding dimension of the logical address space. A first dimensional identifier that identifies a size of the contiguous block region in a first dimension of the namespace is received. A second dimensional identifier that identifies a size of the contiguous block region in a second dimension of the namespace is received. Blocks of the contiguous block region are accessed in response to the single input/output operation according to the starting position, the first dimensional identifier, and the second dimensional identifier.

Abstract: The present disclosure describes techniques for controllable music generation. The techniques comprise extracting latent vectors from unlabelled data, the unlabelled data comprising a plurality of music note sequences, the plurality of music note sequences indicating a plurality of pieces of music; clustering the latent vectors into a plurality of classes corresponding to a plurality of music styles; generating a plurality of labelled latent vectors corresponding to the plurality of music styles, each of the plurality labelled latent vectors comprising information indicating features of a corresponding music style; and generating a first music note sequence indicating a first piece of music in a particular music style among the plurality of music styles based at least in part on a particular labelled latent vector among the plurality of labelled latent vectors, the particular labelled latent vector corresponding to the particular music style.

Abstract: Implementations of the present disclosure relate to methods, devices, and computer program products of extracting a feature for multimedia data that comprises a plurality of medium types. In a method, a first feature is determined for a first medium type in the plurality of medium types by masking a portion in a first medium object with the first medium type. A second feature is determined for a second medium type other than the first medium type in the plurality of medium types. The feature is generated for the multimedia data based on the first and second features. With these implementations, multiple medium types are considered in the feature extraction, and thus the feature may fully reflect various aspects of the multimedia data in an accurate way.