Abstract: A sampling rate processing method performed by a computer device are disclosed. The method includes: obtaining a first audio signal recorded by a transmitting device, the first audio signal being recorded according to an initial sampling rate of the transmitting device; obtaining a second audio signal recorded by a receiving device during playing of the first audio signal, the second audio signal being recorded according to the initial sampling rate; determining a frequency response gain value of the receiving device according to a power spectrum of the first audio signal and a power spectrum of the second audio signal; determining a target sampling rate of the transmitting device according to the initial sampling rate and the frequency response gain value; and configuring the transmitting device to record audio signals according to the target sampling rate.

Abstract: An encoding parameter adjustment method is performed at a computer device. The method includes: obtaining a first audio signal, and determining a psychoacoustic masking threshold within a service frequency band in the first audio signal; obtaining a second audio signal, and determining a background environmental noise estimation value of the frequency within the service frequency band in the second audio signal; determining a masking tag corresponding to the service frequency band according to the psychoacoustic masking threshold of the first audio signal and the background environmental noise estimation value of the second audio signal; determining a masking rate of the service frequency band according to the masking tag corresponding to the frequency within the service frequency band; determining a first reference bit rate according to the masking rate of the service frequency band; and configuring an encoding bit rate of an audio encoder based on the first reference bit rate.

Abstract: This application relates to a speech coding method performed by a computer device. The method includes: obtaining initial frequency bandwidth feature information corresponding to a speech signal; performing feature compression on initial feature information corresponding to a second band in the initial frequency bandwidth feature information to obtain target feature information corresponding to a compressed band, a frequency interval of the second band being greater than a frequency interval of the compressed band; obtaining, based on the target feature information corresponding to the compressed band, a compressed speech signal corresponding to the speech signal; and coding the compressed speech signal to obtain coded speech data corresponding to the speech signal, a target sampling rate corresponding to the compressed speech signal being less than a sampling rate corresponding to the speech signal.

Abstract: Provided are gRNA that can direct a Cas enzyme to target a CTGF gene and the use thereof, which belongs to the technical field of gene editing. The gRNA may direct the Cas enzyme to perform targeted cleavage on an SMAD binding site region of a CTGF gene promoter, or the gRNA may direct the Cas enzyme to perform targeted cleavage on a CTGF gene exon 2 region. The gRNA can reduce the overexpression of the human CTGF gene via a CRISPR-Cas gene editing system. The above-mentioned gRNA is used for preparing a drug for use against fibrotic diseases.

Abstract: A method for improving speech signal intelligibility is performed at a device. A speech signal is obtained. A correspondence between the speech signal and a respective user group among different user groups having distinct voice characteristics is identified. Pre-encoding signal augmentation is performed on the speech signal with a respective pre-augmentation filtering coefficient that corresponds to the respective user group to obtain a group-specific pre-augmented speech signal. The device encodes the pre-augmented speech signal for subsequent transmission through the voice communication channel. An encoded version of the pre-augmented speech signal has reduced loss of signal quality as compared to an encoded version of the speech signal that is obtained without the pre-encoding signal augmentation.

Abstract: An audio encoding bit rate prediction model training method is performed by a computer device. The method includes: obtaining a sample audio feature parameter corresponding to each of sample audio frames in a first sample audio; performing encoding bit rate prediction on the sample audio feature parameter through an encoding bit rate prediction model, to obtain a sample encoding bit rate for each of the sample audio frames; performing audio encoding on the sample audio frames based on the corresponding sample encoding bit rates to generate sample audio data corresponding to the sample audio frames; performing audio decoding on the sample audio data, to obtain a second sample audio corresponding to the sample audio data; and training the encoding bit rate prediction model based on the first sample audio and the second sample audio until a sample encoding quality score reaches a target encoding quality score.

Abstract: An electronic device performs sub-band decomposition on a to-be-coded audio to obtain a to-be-coded low frequency signal corresponding to a low frequency band and a to-be-coded high frequency signal corresponding to a high frequency band. The device performs compression coding on the to-be-coded low frequency signal to obtain low frequency coded data of the to-be-coded low frequency signal. The device determines high frequency prediction information according to the to-be-coded low frequency signal. The device performs feature extraction on the to-be-coded high frequency signal to obtain high frequency feature information. The device determines high frequency compensation information of the to-be-coded high frequency signal according to a difference between the high frequency feature information and the high frequency prediction information.

Abstract: This application relates to a speech coding method, an electronic device, and a storage medium. The method includes: extracting a first speech frame feature corresponding to a first to-be-encoded speech frame, and obtaining a first speech frame criticality level corresponding to the first to-be-encoded speech frame based on the first speech frame feature; extracting a second speech frame feature corresponding to the subsequent speech frame, and obtaining a second speech frame criticality level corresponding to the subsequent speech frame based on the second speech frame feature; obtaining a criticality trend feature based on the first speech frame criticality level and the second speech frame criticality level, and determining, using the criticality trend feature, an encoding bit rate corresponding to the to-be-encoded speech frame; and encoding the first to-be-encoded speech frame based on the encoding bit rate to obtain an encoding result.

Abstract: This application provides a packet loss retransmission method, a computer-readable storage medium, and an electronic device. The packet loss retransmission method includes: obtaining a loudness corresponding to a target audio data packet; and in response to receiving a packet loss state indicating that the target audio data packet is lost, in accordance with a determination that the loudness corresponding to the target audio data packet meets a first threshold: retransmitting the target audio data packet. The technical solutions of this application may alleviate the problem of long data retransmission time, and improve data transmission efficiency.

Abstract: A call audio mixing processing method is provided. In the method, call audio streams from terminals of call members participating in a call are obtained. Voice analysis is performed on the call audio streams to determine voice activity corresponding to each of the terminals. The voice activity of the terminals indicate activity levels of the call members participating in the call. According to the voice activity of the terminals, respective voice adjustment parameters corresponding to the terminals are determined. According to the respective voice adjustment parameters corresponding to the terminals, the call audio streams of the terminals are adjusted. Further, mixing processing is performed on the adjusted call audio streams to obtain a mixed audio stream.

Abstract: An audio transmission method is described. A packet loss recovery capability corresponding to current encoded data of an audio signal can be determined according to a first audio encoding feature parameter corresponding to the current encoded data and a second audio encoding feature parameter corresponding to previous or subsequent encoded data of the current encoded data using a packet loss recovery capability prediction neural network model. Whether to perform redundant encoding for the current encoded data can be determined according to the packet loss recovery capability. In response to the redundant encoding being determined to be performed, the redundant encoding can be performed according to the current encoded data to generate a corresponding redundancy packet.

Abstract: A data transmission method and apparatus, a terminal, a storage medium, and a system. The data transmission method includes: obtaining audio data and transmission status information, determining a compression factor and a redundancy factor based on the transmission status information, performing time domain data compression processing on the audio data according to the compression factor to obtain compressed data, performing channel coding on the compressed data according to the redundancy factor to obtain a data transmission packet, and transmitting the data transmission packet.

Abstract: The present invention provides a method for constructing a next-generation sequencing library for detecting low-frequency mutations, and a kit thereof. The constructing method comprises steps of obtaining blunt-end DNA fragments, obtaining DNA fragments with A-tail at the 3? end, obtaining adapter-added DNA fragments using a specific nucleotide sequence and obtaining amplification products using a specific nucleotide sequence.

Abstract: A packet loss concealment method includes: receiving a speech data packet; determining a speech power spectrum of speech data in the speech data packet in response to determining, according to the speech data packet, that a packet loss occurs; performing lost frame prediction on the speech power spectrum by using a neural network model, to obtain a predicted lost frame power spectrum; and determining restored speech data according to the speech power spectrum and the predicted lost frame power spectrum.

Abstract: A sampling rate processing method performed by a computer device are disclosed. The method includes: obtaining a first audio signal recorded by a transmitting device, the first audio signal being recorded according to an initial sampling rate of the transmitting device; obtaining a second audio signal recorded by a receiving device during playing of the first audio signal, the second audio signal being recorded according to the initial sampling rate; determining a frequency response gain value of the receiving device according to a power spectrum of the first audio signal and a power spectrum of the second audio signal; determining a target sampling rate of the transmitting device according to the initial sampling rate and the frequency response gain value; and configuring the transmitting device to record audio signals according to the target sampling rate.

Abstract: A voice processing method is provided for a terminal. The method includes: performing voice speed detection on a voice obtained from a voice source, to obtain a voice speed value of the voice; obtaining a forward error correction (FEC) redundancy; adjusting the FEC redundancy according to the voice speed value to obtain a target redundancy; performing voice encoding on the voice to obtain a voice encoded packet; performing FEC encoding on the voice encoded packet according to the target redundancy to obtain a redundancy packet; and transmitting the redundancy packet and the voice encoded packet to a receiving end.

Abstract: The present disclosure discloses a data transmission method performed by a computer device and a non-transitory computer-readable storage medium. According to the present disclosure, voice criticality analysis is performed on a to-be-transmitted audio to obtain a criticality level of each to-be-transmitted audio frame in the to-be-transmitted audio, and a corrected redundancy multiple of each to-be-transmitted audio frame is obtained according to a current redundancy multiple and a redundant transmission factor corresponding to the criticality level of each to-be-transmitted audio frame. Therefore, each to-be-transmitted audio frame is duplicated according to a corrected redundancy multiple of each to-be-transmitted audio frame, to obtain at least one redundancy data packet, and the at least one redundancy data packet is transmitted to a target terminal, which can improve the network anti-packet loss effect without causing network congestion.

Abstract: The present invention provides a method for constructing a next-generation sequencing library for detecting low-frequency mutations, and a kit thereof. The constructing method comprises steps of obtaining blunt-end DNA fragments, obtaining DNA fragments with A-tail at the 3? end, obtaining adapter-added DNA fragments using a specific nucleotide sequence and obtaining amplification products using a specific nucleotide sequence.

Abstract: This disclosure provides a network call method and apparatus, a computer device, and a storage medium, and belongs to the field of audio data processing. The method includes: performing time-frequency transformation on an acquired audio signal, to obtain a plurality of pieces of frequency domain information of the audio signal; determining a target bit rate corresponding to the audio signal according to the plurality of pieces of frequency domain information; and encoding the audio signal based on the target bit rate, and performing a network call based on the encoded audio signal.

Abstract: An audio frame loss recovery method and apparatus are disclosed. In one implementation, data from some but not all audio frames is included in a redundant frame. The audio frames whose data is not included in the redundant frame may include multiple audio frames but may not include more than two consecutive audio frames. Because not all audio frames are used in the redundant frame, the amount of information needed to be transmitted in the redundant frame is reduced. A lost audio frame during transmission may be recovered from either the redundant frame when the redundant frame incudes data of the lost frame, or from at least one neighboring frame of the lost frame derived from either the redundant frame or the successfully transmitted audio frames when the redundant frame does not include data of the lost frame.