Please select the most similar patent number from A, B, C and D. Which number is?
An immersive audio rendering method and system. Said method comprises: for multiple channels of audio to be mixed which is played back by a plurality of loudspeakers, acquiring first HOA-based gains and second VBAP-based gains of the channels of audio (S1); configuring mixing weights for the channels of audio, and determining weight coefficients of the first gains and the second gains according to the mixing weights (S2); and determining mixing gains of the channels of audio according to the first gains, the second gains and respective weight coefficients, and completing audio mixing processing of multiple channels of audio by means of the mixing gains (S3). Said method can more accurately locate a sound source, thereby satisfying the requirements of immersive production and playback in a small and medium venue on site.
A: An audio mixing method and an audio mixing apparatus. The method comprises: obtaining at least two audio input signals (S101); linearly superimposing the at least two audio input signals (S102); after linear superimposition, dividing the obtained mixed audio signal into at least two audio mixing signal-intensity zones according to audio intensity (S103); respectively shrinking the signal intensity of each audio mixing signal-intensity zone by using a corresponding shrinkage ratio, wherein the shrinkage ratio employed for the audio mixing signal-intensity zone having a higher signal intensity is smaller than the shrinkage ratio employed for the audio mixing signal-intensity zone having a lower signal intensity (S104); superimposing the at least two audio mixing signal-intensity zones after signal-intensity shrinkage, and then outputting the outcome (S105).
B: Disclosed in the embodiments of the present application are a network connection synchronization method and apparatus, and an electronic device and a storage medium. The network connection synchronization method comprises: after being disconnected from a first audio source end, an audio playing end establishing a connection with a second audio source end; and on the basis of a volume gain mode, which is used between the audio playing end and the second audio source end, and a first volume gain, determining a first local volume gain of the second audio source end and/or a second local volume gain of the audio playing end, wherein the first volume gain is represented as a corresponding total volume gain when a connection is established with the first audio source end, which gain is stored at the audio playing end.
C: Disclosed is a voice translation method and a device thereof, comprising: respectively acquiring second voice signals obtained by translating a first voice signal under different preset gains; comparing a semantic meaning association between each second voice signal and a pre-configured third voice signal, wherein the first voice signal is a reply signal of the third voice signal, and the second voice signal and the third voice signal belong to the same language; acquiring a second voice signal having the highest semantic meaning association with the third voice signal and a second gain corresponding thereto; determining if the second gain is identical to a first gain used in a previous translation, the first gain and the second gain belonging to the preset gains; and if so, recording and playing back the second voice signal having the highest semantic meaning association. An optimal translation is acquired by using different gains to amplify a semantic meaning association between a translation and a previous sentence, thereby facilitating use of a translation device by a user and enhancing the user experience when using the translation device.
D: Disclosed are an audio signal processing method, a model training method, and a related apparatus. A first audio input signal is input into a machine learning model to obtain a first howling point and a corresponding first gain value; the first audio input signal is processed according to the first gain value to obtain a second audio input signal; and next, the second audio input signal is tested to obtain a second howling point, and the second howling point in the second audio input signal is then processed according to a second gain value to obtain an audio output signal. Therefore, the suppression of howling in an audio input signal is realized, and the howling is suppressed in an initial phase, and a gain loop cannot be carried out any more. Due to the correspondence of the indication of a howling point in a machine learning model and the convenience of model calculation, the above-mentioned processing process is fast and does not affect an effective audio signal, thereby improving the accuracy and efficiency of audio processing.
Answer: A