Abstract: An array substrate of a display device includes a pixel electrode layer on a substrate, which includes active pixel electrodes in an active display region; outermost active pixel electrodes include a first active pixel electrode including a first pixel electrode edge and a second pixel electrode edge; in a first direction, the first pixel electrode edge is between the second pixel electrode edge and a frame region. One of the array substrate and an opposite substrate of the display device includes a common electrode layer including a first extended common electrode which includes a first extended portion extending beyond the first active pixel electrode; a first extended portion edge of the first extended portion and a first substrate edge of the substrate respectively extend in a second direction; in the first direction, the first extended portion edge is located between the first substrate edge and the first pixel electrode edge.

Abstract: A method and apparatus for predicting a mouth-shape feature, and an electronic device are provided. A specific implementation of the method comprises: recognizing a phonetic posterior gram (PPG) of a phonetic feature; and performing a prediction on the PPG by using a neural network model, to predict a mouth-shape feature of the phonetic feature, the neural network model being obtained by training with training samples and an input thereof including a PPG and an output thereof including a mouth-shape feature, and the training samples including a PPG training sample and a mouth-shape feature training sample.

Abstract: A method for processing a speech includes: acquiring an original speech; extracting a spectrogram from the original speech; acquiring a speech synthesis model, where the speech synthesis model comprises a first generation sub-model and a second generation sub-model; generating a harmonic structure of the spectrogram, by invoking the first generation sub-model to process the spectrogram; and generating a target speech, by invoking the second generation sub-model to process the harmonic structure and the spectrogram.

Abstract: A microchannel heat exchanger structure with a nozzle and a working method thereof. The microchannel heat exchanger structure with a nozzle, includes a first heat exchange portion, a second heat exchange portion, and at least one nozzle portion between the first heat exchange portion and the second heat exchange portion, the first heat exchange portion having a high-pressure heat exchange channel, a first micro-fin array being provided inside the high-pressure heat exchange channel, and the second heat exchange portion having a low-pressure heat exchange channel, the high-pressure heat exchange channel and the low-pressure heat exchange channel being in communication through at least one nozzle disposed in the nozzle portion. The heat exchanger structure has a good heat exchange effect and can achieve a better heat flux during heat exchange.

Abstract: The disclosure provides a speech synthesis method, and an electronic device. The technical solution is described as follows. A text to be synthesized and speech features of a target user are obtained. Predicted first acoustic features based on the text to be synthesized and the speech features are obtained. A target template audio is obtained from a template audio library based on the text to be synthesized. Second acoustic features of the target template audio are extracted. Target acoustic features are generated by splicing the first acoustic features and the second acoustic features. Speech synthesis is performed on the text to be synthesized based on the target acoustic features and the speech features, to generate a target speech of the text to be synthesized.

Abstract: A method, device and computer storage medium for generating a speech packet which relates to the technical field of speech are disclosed. The method may include: providing a speech recording interface to a user; obtaining speech data entered by the user after obtaining an event of triggering speech recording on the speech recording interface; uploading the speech data to a server side in response to determining that the speech data meets requirements for training a speech synthesis model; receiving a downloading address of the speech packet generated by the server side after training the speech synthesis model with the speech data. An ordinary user may customize a personalized speech packet through the speech recording interface provided by the client, without using professional recording equipment, which may substantially reduce the production cost of the speech packet.

Abstract: A method for speech synthesis includes obtaining text to be synthesized and an identifier of a speaker, the text being written in a first language; obtaining pronunciation information of each character in the text; generating linguistic features of the text by performing feature extraction on the pronunciation information of each character in the text based on the first language; and obtaining a target speech in a second language other than the first language, by performing speech synthesis based on the linguistic features and the identifier of the speaker.

Abstract: The present disclosure discloses an interactive voice-control method and apparatus, a device and a medium. The method includes: obtaining a sound signal at a voice interaction device and recognized information that is recognized from the sound signal; determining an interaction confidence of the sound signal based at least on at least one of an acoustic feature representation of the sound signal and a semantic feature representation associated with the recognized information; determining a matching status between the recognized information and the sound signal; and providing the interaction confidence and the matching status for controlling a response of the voice interaction device to the sound signal.

Abstract: The present application discloses a training method and an apparatus for a speech synthesis model, electronic device, and storage medium. The method includes: taking a syllable input sequence, a phoneme input sequence and a Chinese character input sequence of a current sample as inputs of an encoder of a model to be trained, to obtain encoded representations of these three sequences at an output end of the encoder; fusing the encoded representations of these three sequences, to obtain a weighted combination of these three sequences; taking the weighted combination as an input of an attention module, to obtain a weighted average of the weighted combination at each moment at an output end of the attention module; taking the weighted average as an input of a decoder of the model to be trained, to obtain a speech Mel spectrum of the current sample at an output end of the decoder.

Abstract: The present application discloses a method and an apparatus for training a speech spectrum generation model, as well as an electronic device, and relates to the technical field of speech synthesis and deep learning. A specific implementation is as follows: inputting a first text sequence into the speech spectrum generation model to generate an analog spectrum sequence corresponding to the first text sequence, and obtain a first loss value of the analog spectrum sequence according to a preset loss function; inputting the analog spectrum sequence corresponding to the first text sequence into an adversarial loss function model, which is a generative adversarial network model, to obtain a second loss value of the analog spectrum sequence; and training the speech spectrum generation model based on the first loss value and the second loss value.

Abstract: A deep well grounding electrode and a deep well grounding electrode monitoring system. The deep well grounding electrode comprises a feeding rod, a feeding head, a steel casing, a temperature measurement optical cable, an exhaust pipe, and a drainage cable; the steel casing is located in the well body; the feeding head is located at the bottom of the steel casing; the feeding rod, the temperature measurement optical cable, the exhaust pipe, and the drainage cable are located in the steel casing; the temperature measurement optical cable extends from a bottom end of the feeding rod to a monitoring module; the exhaust pipe extends from the bottom end of the feeding rod to the ground; and one end of the drainage cable is welded on the feeding rod, the other end extends to the monitoring module, and the drainage cable is fixed to the feeding rod by bolts.

Abstract: The present disclosure provides a method and an apparatus for managing navigation broadcast, and a device, related to an Intelligent transportation technology field. A specific implementation solution includes: obtaining a geographical identifier of a user; obtaining a statement-conversion template set corresponding to the geographical identifier based on the geographical identifier of the user; converting a standard navigation broadcast statement based on the statement-conversion template set to generate a geographical navigation broadcast statement; and performing navigation broadcast based on the geographical navigation broadcast statement. Thereby, the navigation broadcasts are matched with respective regions, users in different regions are provided with diversified and personalized navigation broadcasts.

Abstract: A neural network processing method, a neural network processing unit (NPU) and a processing device are provided. The method includes: obtaining by a quantizing unit in the NPU float type input data, quantizing the float type input data to obtain quantized input data, and providing the quantized input data to an operation unit; performing by the operation unit of the NPU a matrix-vector operation and/or a convolution operation to the quantized input data to obtain an operation result of the quantized input data; and performing by the quantizing unit inverse quantization to the operation result output by the operation unit to obtain an inverse quantization result.

Abstract: According to embodiments of the present disclosure, a method, apparatus, device, and computer readable storage medium for voice interaction are provided. The method includes: determining a text corresponding to the voice signal based on a voice feature of a received voice signal. The method further includes: determining, based on the voice feature and the text, a matching degree between a reference voice feature of an element in the text and a target voice feature of the element. The method further includes: determining a first possibility that the voice signal is an executable command based on the text. The method further includes: determining a second possibility that the voice signal is the executable command based on the voice feature.

Abstract: Provided are compositions comprising recombinant DNA polymerases that include amino acid substitutions, insertions, deletions, and/or exogenous features that confer modified properties upon the polymerase for enhanced single molecule sequencing. Such properties include increased resistance to photodamage, and can also include enhanced metal ion coordination, reduced exonuclease activity, reduced reaction rates at one or more steps of the polymerase kinetic cycle, decreased branching fraction, altered cofactor selectivity, increased yield, increased thermostability, increased accuracy, increased speed, increased readlength, and the like. Also provided are nucleic acids which encode the polymerases with the aforementioned phenotypes, as well as methods of using such polymerases to make a DNA or to sequence a DNA template.

Abstract: A method for training a data processing model includes: acquiring sample data; acquiring an initial data processing model, the initial data processing model including a plurality of forward nodes for outputting a plurality of intermediate results corresponding to the sample data; determining a plurality of time-dependent features corresponding to the plurality of forward nodes; acquiring a data processing model to be trained by processing the initial data processing model based on the plurality of time-dependent features; and training the data processing model to be trained using the sample data and the plurality of intermediate results.

Abstract: A method, apparatus, device, and computer readable storage medium for recognizing and decoding a voice based on a streaming attention model are provided. The method may include generating a plurality of acoustic paths for decoding the voice using the streaming attention model, and then merging acoustic paths with identical last syllables of the plurality of acoustic paths to obtain a plurality of merged acoustic paths. The method may further include selecting a preset number of acoustic paths from the plurality of merged acoustic paths as retained candidate acoustic paths. Embodiments of the present disclosure present a concept that acoustic score calculating of a current voice fragment is only affected by its last voice fragment and has nothing to do with earlier voice history, and merge acoustic paths with the identical last syllables of the plurality of candidate acoustic paths.

Abstract: The disclosure provides a method and an apparatus for allocating memory, and an electronic device. Multiple frames of speech data are received and input to a neural network model. The neural network model is configured to ask for multiple data tensors when processing the multiple frames of speech data, and the multiple data tensors share a common memory.

Abstract: According to embodiments of the disclosure, a method and an apparatus for processing a speech signal, and a computer-readable storage medium are provided. The method includes obtaining a set of speech feature representations of a speech signal received. The method also includes generating a set of source text feature representations based on a text recognized from the speech signal, each source text feature representation corresponding to an element in the text. The method also includes generating a set of target text feature representations based on the set of speech feature representations and the set of source text feature representations. The method also includes determining a match degree between the set of target text feature representations and a set of reference text feature representations predefined for the text, the match degree indicating an accuracy of recognizing of the text.