Abstract: A method for processing information, includes: performing word segmentation on first corpus data to obtain second corpus data containing at least one word; processing, based on a first pretrained model, the at least one word contained in the second corpus data, to obtain a first eigenvector sequence corresponding to the second corpus data; processing, based on a second pretrained model, characters contained in the first corpus data, to obtain a second eigenvector sequence corresponding to the first corpus data; and obtaining a target eigenvector based on the first eigenvector sequence and the second eigenvector sequence.

Abstract: A method and a storage medium are provided for training an image recognition model. An image recognition model is trained by using a tagged image sample set. Multiple to-be-tagged image samples in a to-be-tagged image sample set are recognized by using the image recognition model to obtain a confidence level of a recognition result corresponding to each of the multiple to-be-tagged image samples. At least one to-be-tagged image sample of which the confidence level is in a preset interval is selected as at least one to-be-tagged image sample to form a first to-be-tagged image sample set. Tags of to-be-tagged image samples in the first to-be-tagged image sample set is acquired. An updated tagged image sample set is obtained by updating the tagged image sample set according to the acquired tags. The image recognition model is trained by using the updated tagged image sample set.

Abstract: A method for acquiring a sample image set, includes: acquiring a plurality of frame images continuously shot for a shooting scene; determining, as a reference image, one frame of a plurality of frame images, and determining, as non-reference images, remaining ones of the plurality of frame images other than the one determined as the reference image; performing a format conversion on the reference image and the non-reference images to obtain a format-converted reference image and format-converted non-reference images, and performing a noise addition processing on the format-converted reference image and each non-reference image respectively; aligning each noise-added non-reference image with a noise-added reference image to obtain an aligned non-reference image; annotating the format-converted reference image with pixel information to obtain a non-noise-added reference image; and acquiring the sample image set, the sample image set including the aligned non-reference image, the noise-added reference image, and

Abstract: The present disclosure relates to a method and an apparatus for processing information. The method comprises: acquiring to-be-processed information, and taking the to-be-processed information as an input of a processing model acquired by training a preset model so as to acquire target information corresponding to the to-be-processed information and output by the processing model. The preset model includes a plurality of operation modules and normalization structure corresponding to each of the plurality of operation modules, the normalization structure is configured to normalize an output of the corresponding operation module, and the processing model is acquired by removing a specified number of normalization structures according to a target probability or the number of steps for training the preset model in the process of training the preset model.

Abstract: A method, apparatus, electronic device, and storage medium for character recognition are provided. The method may perform image processing on an acquired original image to obtain a region to be recognized. The region may include a character. The method may determine an area ratio of the region to be recognized on the original image. The method may determine an angle between the region to be recognized and a preset direction. The method may determine a character density of the region to be recognized. The method may perform character recognition on the character in the region to be recognized in response to determining that the area ratio is greater than a ratio threshold, the angle is less than an angle threshold, and the character density is less than a density threshold.

Abstract: An original noisy signal of each of at least two microphones is acquired by acquiring, using the at least two microphones, an audio signal emitted by each sound source. For each frame in time domain, an estimated frequency-domain signal of each sound source is acquired according to the original noisy signal of each of the at least two microphones. A frequency collection containing a plurality of predetermined static frequencies and dynamic frequencies is determined in a predetermined frequency band range. A weighting coefficient of each frequency contained in the frequency collection is determined according to the estimated frequency-domain signal of the each frequency in the frequency collection. A separation matrix of the each frequency is determined according to the weighting coefficient. The audio signal emitted by each of the at least two sound sources is acquired based on the separation matrix and the original noisy signal.

Abstract: A method and a device for generating an emoticon are provided. A first expression tag list corresponding to a face image in a portrait is acquired by inputting the face image into an expression recognition model. Additionally, at least one label text corresponding to the face image is determined based on the first expression tag list and a correspondence between a preset text and a second expression tag list. Furthermore, an expression image corresponding to the portrait is determined, where the face image is a part of the expression image. Moreover, an emoticon is generated by labelling the expression image with the at least one label text.

Abstract: Aspects of the disclosure provide a method and device for information processing, a terminal, a server and a storage medium. The method can include that voice information is collected, and, responsive the voice information instructing a target application program to be started, instruction information configured to assist in starting the target application program is determined. The method can further include that multimedia information indicated by the instruction information is output according to the instruction information in a process of starting the target application program. Therefore, the multimedia information may be output in the process of starting the application program to improve the experience of a user in starting the application program.

Abstract: An image processing method, a device and a non-transitory computer-readable storage medium thereof are provided. The method includes that a first image of a target object, a second image of the target object, and a third image of the target object are acquired. Exposure of the first image is less than exposure of the second image. The exposure of the second image is less than exposure of the third image. Further, brightness of the first image is increased to acquire a fourth image. Moreover, ghost elimination is performed on the second image and the fourth image is taken as a first reference frame to acquire a second reference frame. Furthermore, ghost elimination is performed on the third image based on the second reference frame to acquire a fifth image.

Abstract: A method for detecting an audio input includes: acquiring audio input signals received by at least two input signal channels of an audio input module; for each of the audio input signals, filtering the audio input signal according to a preset audio output signal of an electronic device where the audio input module is located to obtain a target signal; for each of the audio input signals, determining a comparison parameter value according to the target signal and the audio input signal; and determining a performance state of the audio input module according to the comparison parameter values.

Abstract: The present disclosure relates to an image processing method that can include that an image to be processed is acquired, at least one category is selected via category information of the image to be processed, and a thermodynamic diagram for each category in the at least one category can be determined via the category information. The method can further include that a first positioning frame set corresponding to a target object in the image to be processed is respectively determined for the thermodynamic diagram for each category in the thermodynamic diagram for the at least one category, and a second positioning frame set of the image to be processed is determined according to an unsupervised target detection algorithm. Additionally, the method can include that a target positioning frame set in the image to be processed is determined according to the first positioning frame set and the second positioning frame set.

Abstract: A method for processing a video includes: identifying a target object in a first video segment; acquiring a current video frame of a second video segment; acquiring a first image region corresponding to the target object in a first target video frame of the first video segment, and acquiring a second image region corresponding to the target object in the current video frame of the second video segment, wherein the first target video frame corresponds to the current video frame of the second video segment in terms of video frame time; and performing picture splicing on the first target video frame and the current video frame of the second video segment according to the first image region and the second image region to obtain a processed first video frame.

Abstract: A method for processing information includes that: a current audio is acquired, and a current text corresponding to the current audio is acquired; feature extraction is performed on the current audio through a speech feature extraction portion in a semantic analysis model, to obtain a speech feature of the current audio; feature extraction is performed on the current text through a text feature extraction portion in the semantic analysis model, to obtain a text feature of the current text; semantic classification is performed on the speech feature and the text feature through a classification portion in the semantic analysis model, to obtain a classification result; and recognition of the current audio is rejected in response to the classification result indicating that the current audio is to be rejected for recognition.

Abstract: At a terminal equipment side, sentence information received by the terminal equipment is acquired. A part-of-speech label sequence of text data in the sentence information for which part-of-speech labelling is to be performed is extracted. A detection result is acquired by detecting legitimacy of the part-of-speech label sequence. When the detection result indicates that the part-of-speech label sequence is illegitimate, the part-of-speech label sequence is corrected. A corrected part-of-speech label sequence is output as a result of performing part-of-speech labelling on the text data. Semantics corresponding to the sentence information is determined according to output sentence information with part-of-speech labels.

Abstract: A method and device for behavior recognition based on line-of-sight estimation are provided. The method is as follows. An image is collected. It is detected whether the image includes a face. When the image includes a face, it is determined whether the face in the image is a face with closed eyes. When the face in the image is not with closed eyes, a line-of-sight direction angle of a target to which the face belongs, and a distance between the face and an image collecting unit, are computed. It is determined whether the target has a set behavior based on the line-of-sight direction angle and the distance.

Abstract: A method and device for behavior recognition are provided. According the present disclosure, an image is collected. It is detected whether the image includes a face. When the image includes a face, it is determined whether the face in the image is a face with closed eyes. When the face in the image is not with closed eyes, a distance between the face and an image collecting unit is computed. A maximum field of vision of a target to which the face belongs is determined according to the distance and a parameter of the image collecting unit. It is determined, according to the maximum field of vision, whether the target has a set behavior.

Abstract: At least two images are acquired. At least two crop images are acquired by cropping the at least two images for face-containing images. Triangular patch deformation is performed on two neighbour images, generating a first triangular patch deformation frame image sequence and a second triangular patch deformation frame image sequence. Similarity transformation is performed on each image sequence of the first triangular patch deformation frame image sequence, acquiring a first transform frame image sequence. Similarity transformation is performed on each image sequence of the second triangular patch deformation frame image sequence, acquiring a second transform frame image sequence. The first and the second transform frame image sequences are fused, acquiring a video frame sequence corresponding to the two neighbour images. Of the at least two images, a video frame sequence generated by all neighbour images is coded, acquiring a destined video.

Abstract: The present disclosure relates to a video processing method and apparatus, and a storage medium. The method is applied to a terminal and includes: a background frame for a time static special effect is determined from video frames in a video to be processed; for each of the video frames in the video, an image area, where a target object is located is acquired from the respective video frame and the image area is fused into the background frame to generate a special effect frame with the time static special effect.

Abstract: A delay adjustment method is applied to a first electronic device, and the first electronic device is any device in a distributed device network. The method includes: a starting delay of a wakeup engine of at least one second electronic device in the network is acquired; it is determined whether a starting delay of a wakeup engine of the first electronic device needs to be adjusted according to the starting delay of the wakeup engine of the first electronic device and the starting delay of the wakeup engine of the at least one second electronic device; and responsive to that the starting delay of the first electronic device needs to be adjusted, the starting delay of the wakeup engine is adjusted, and wakeup information interaction is performed with the at least one second electronic device based on the adjusted starting delay of the wakeup engine.

Abstract: A method for controlling a recording volume, includes: determining an adjustment gain; and calibrating at least one voice interaction apparatus based on the adjustment gain, to make the at least one voice interaction apparatus have a same recording volume under a same sound pressure level.