An acoustic
feedback control method for a low-time-
delay acoustic reinforcement
system comprises the following steps: constructing an acoustic reinforcement
system model, establishing a closed-loop
transfer function, and determining a
system stability condition; constructing an acoustic feedback path, generating an open-loop training
data set, and simulating an acoustic feedback
signal in a critical unstable state; extracting time-frequency characteristics of the input
signal, and designing a complex
spectral mapping target of the neural network; constructing a full-sub-band packet long-
short term memory network which comprises an
encoder, a full-band and sub-band
processing module and a decoder, training the network by adopting a mixed amplitude spectrum and complex spectrum
loss function, and optimizing a
signal reconstruction strategy to reduce time
delay; finely adjusting the network in a simulated closed-loop system to adapt to an actual acoustic environment and
nonlinear distortion, and limiting the amplitude of an output signal through hard tailoring; and deploying the fine-tuned model to a real
sound reinforcement system, and cooperatively inhibiting sound feedback with a
frequency shift method. According to the method, sound feedback can be effectively inhibited under the condition of relatively low time
delay, the quality and intelligibility of voice are improved, and the maximum stable
gain of a
sound reinforcement system is improved.