Tencent Technology (shenzhen) Company Limited

Alibaba Group Holding Limited

Huawei Technologies Co., Limited

Melt & Marble Ab

Fih (hong Kong) Limited

Shenzhen Futaihong Precision Industry Co., Ltd.

Biopetrolia Ab

Zte Corporation

Tencent Technology Company Limited

Tao Yu

Anastasia Krivoruchko

Florian David

Jens Nielsen

Biao Tian

Yunfeng Xu

Ming Tu

Hua Xu

Nan Wu

Yi Yang

Qi Zhao

Gang Liu

Hui Wang

Dong Yang

Xiaoyu Liu

Li Liu

Wenyan Li

Verena Siewers

Qian Yang

Congbing Li

Xiaochun Cui

Muyong Cao

Zhenkun Zhou

Qian Deng

Yuqiong Xu

Jinwei Feng

Rongxin Zhou

Jinliang Zhang

Zhaowei He

Heng Xiao

Zipan Bai

Zhigao Deng

Zhiguo Chen

Xuefei Fang

Yong-Jin Zhou

Jingbing Cui

Leonie Wenning

Shujie Lin

Jiaxu Wu

Luxin Li

Meihan Cao

Yanqing Feng

A fungal cell capable of producing high levels of fatty acids and fatty acid-derived products comprises at least one modification to the endogenous fatty acid metabolism.

Yeast cells genetically modified for downregulation of pyruvate decarboxylase activity and FBP-sensitive pyruvate kinase

This application discloses an audio signal processing method, a model training method, and related apparatus. The audio signal processing method includes inputting a first audio input signal into a machine learning model to obtain a first howling point, and obtaining a first gain value according to the first howling point, the first howling point corresponding to an effective audio signal in the first audio input signal, and the first gain value indicating a suppression parameter of the first howling point; processing the first audio input signal according to the first gain value to obtain a second audio input signal; detecting a second howling point, and obtaining a second gain value according to the second howling point, the second howling point corresponding to a frequency band of an ineffective audio signal in the second audio input signal; and processing the second audio input signal to obtain an audio output signal.

Audio signal processing method, model training method, and related apparatus

Embodiments of this disclosure provide a speech enhancement method and apparatus, an electronic device, and a computer-readable storage medium. The method includes: obtaining a clean speech sample; decomposing the clean speech sample to obtain a first sparse matrix and m base matrices, values in the first sparse matrix being all positive numbers, and m being a positive integer greater than 1; obtaining, according to the first sparse matrix and a weight matrix of a target neural network, state vectors of neurons in a visible layer of the target neural network; and updating the weight matrix according to the state vectors of the neurons in the visible layer and the clean speech sample, to obtain a deep dictionary used for speech enhancement.

Speech enhancement method and apparatus, electronic device, and computer-readable storage medium

A fungal cell is capable of producing high levels of fatty acids and fatty acid-derived products. The fungal cell comprises at least one modification to the endogenous fatty acid metabolism.

Genetically modified fungal cells for overexpression of an acetyl-CoA carboxylase and a pyruvate carboxylase

A method and an electronic device for detecting crosstalk data are provided. The method for detecting crosstalk data can detect whether an audio data stream includes crosstalk data. The method includes: receiving a first audio data block, a second audio data block, and a reference time difference, wherein the first audio data block and the second audio data block separately include a plurality of audio data segments; using a time difference between an acquisition time of an audio data segment in the first audio data block and a corresponding audio data segment in the second audio data block as an audio segment time difference; and determining that the audio data segment of the first audio data block includes crosstalk data when the audio segment time difference does not match the reference time difference.

Crosstalk data detection method and electronic device

The disclosed embodiments disclose methods, apparatuses, systems, devices and computer-readable storage media for processing speech signals. The method comprises: acquiring a real-time image by using an image capturing device, performing facial recognition by using the real-time image, and detecting a period during which a target user makes speech sounds based on a facial recognition result; locating a sound source in an audio signal received by a microphone array, and determining the orientation information of a sound source in the audio signal; and based on the period during which the target user in the real-time image makes the speech sounds and the orientation information of the sound source, performing a speech sound start and end point analysis to determine start and end time points of the speech sounds in the audio signal. The method for processing speech signals according to one embodiment can perform voice activity detection to the speech signal in noisy environments containing multiple sources of interference, thereby improving the anti-interference capability of the system.

Methods, apparatuses, systems, devices, and computer-readable storage media for processing speech signals based on horizontal and pitch angles and distance of a sound source relative to a microphone array

The present disclosure provides a decoding method and apparatus. The decoding method mainly includes: extracting pre-indexed information, storing the pre-indexed information in another file associated with a to-be-decoded file or a tail end of the to-be-decoded file, then reading the pre-indexed information before decoding is performed, and performing parallel decoding on multiple data segments in the to-be-decoded file according to the pre-indexed information. Using the foregoing storage method for the pre-indexed information may effectively reduce an I/O operation when the pre-indexed information is read, so as to avoid, to some extent, a system frame freezing phenomenon that may be caused when decoding is performed.

Method and apparatus for decoding variable-length coded file

The disclosure describes methods, clients, and electronic devices for processing audio signals. One method for processing audio signals comprises: receiving a first audio signal inputted from a first audio acquisition terminal and a second audio signal inputted from a second audio acquisition terminal, wherein the first audio acquisition terminal and the second audio acquisition terminal are located in different positions of a same location; determining a target audio signal and a reference audio signal from the first audio signal and the second audio signal; determining a filter coefficient corresponding to the target audio signal based on the reference audio signal; and eliminating, from the target audio signal, a crosstalk signal determined based on the filter coefficient and the reference audio signal. The effect that a speech path can output speech signals with less interference is achieved.

Method, client, and electronic device for processing audio signals

The present disclosure discloses an information processing method, including the steps of acquiring at least one executable file of a specified type; extracting a first operation instruction from the at least one executable file of the specified type; determining the first operation instruction as a feature instruction if a preset policy is met; extracting a feature value of the feature instruction; constructing a virus classification model based on the feature value of the feature instruction for obtaining a virus structural feature parameter; extracting a second operation instruction from at least one to-be-analyzed file when the at least one to-be-analyzed file is identified according to the virus classification model; and identifying the to-be-analyzed file as a virus file if the feature value of the second operation instruction corresponds to the virus structural feature parameter.

Method, server, and computer storage medium for identifying virus-containing files

A sound processing method and an interactive device are provided. The method includes determining a sound source position of a sound object relative to an interactive device based on a real-time image of the sound object; and performing a sound enhancement on sound data of the sound object based on the sound source position. The above solution solves an existing problem that noises cannot be effectively cancelled in a noisy environment is solved, thus achieving the technical effects of effectively suppressing the noises and improving the accuracy of voice recognition.

Sound processing method and interactive device

The present invention generally relates to a genetically modified fungal cell capable of producing a very long, chain fatty acid (VLCFA) and/or a VLCFA derivative. The genetically modified fungal cell comprises at least one exogenous gene encoding a fatty acyl-CoA reductase, and at least one gene encoding an elongase, and/or at least one gene encoding a fatty acid synthase.

Fungal cells and methods for production of very long chain fatty acid derived products

Systems and methods for enhancing reverberated audio signals are disclosed. In one embodiment, a method is disclosed comprising receiving an audio signal; partitioning a frequency domain representation of the audio signal into a plurality of sub-band vectors; inputting each sub-band vector into a corresponding deep neural network; calculating, using the corresponding deep neural networks, a plurality of output vectors for each sub-band; concatenating the plurality of output vectors to generate a clean audio feature matrix; and converting the clean audio feature matrix into a time-domain audio signal.

Enhancing audio signals using sub-band deep neural networks

A method of detecting respective source locations of sounds in an audio signal. The method includes receiving the audio signal via a horizontal set of microphones and a vertical set of microphones. The respective source locations of the sounds in the audio signal are determined by analyzing the audio signal. Analysis is conducted with respect to the horizontal set of microphones and with respect to the vertical set of microphones, to determine a respective horizontal direction to the respective source locations of the sounds, and determine a respective vertical direction to the respective source locations of the sounds. The distance is calculated between the respective source locations of the sounds and the horizontal set of microphones and the vertical set of microphones.

Method and apparatus for sound source location detection

The present disclosure provides a virus signature matching method, including: obtaining an inputted target file; loading a virus signature database, and successively extracting signature function identifiers from the virus signature database, the virus signature database comprising the signature function identifiers and virus signature type identifiers corresponding to the signature function identifiers; obtaining signature functions corresponding to the signature function identifiers, and checking the target file by invoking the signature functions, to obtain corresponding check results; and obtaining a virus signature type identifier corresponding to the target file according to the check results. In addition, a virus signature matching apparatus is further provided. The foregoing virus signature matching method and apparatus can improve virus scanning and removing efficiency.

Virus signature matching method and apparatus

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Shenzhen, China

Tao Yu