Neural network-based loudspeaker modeling with a deconvolution filter

• Main Authors: AJAY IYER, DOUGLAS J.BUTTON
• Format: Patent
• Language: Chinese; English
• Published: 27.10.2017
• Subjects: DEAF-AID SETS; ELECTRIC COMMUNICATION TECHNIQUE; ELECTRICITY; LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKEACOUSTIC ELECTROMECHANICAL TRANSDUCERS; PUBLIC ADDRESS SYSTEMS

A technique for controlling a loudspeaker system with an artificial neural network includes filtering, with a deconvolution filter, a measured system response of a loudspeaker and a reverberant environment in which the loudspeaker is disposed to generate a filtered response, wherein the measured system response corresponds to an audio input signal applied to the loudspeaker while the loudspeaker is disposed in the reverberant environment. The techniques further include generating, via a neural network model, an initial neural network output based on the audio input signal, comparing the initial neural network output to the filtered response to determine an error value, and generating, via the neural network model, an updated neural network output based on the audio input signal and the error value. 种用于利用人工神经网络控制扬声器系统的技术包括利用反褶积滤波器对扬声器和扬声器布置在其中的混响环境的测量系统响应进行滤波，以产生滤波后的响应，其中所述测量系统响应对应于当扬声器布置在混响环境中时施加到扬声器的音频输入信号。所述技术还包括：基于音频输入信号通过神经网络模型生成初始神经网络输出；将初始神经网络输出与滤波后的响应进行比较以确定误差值；以及基于音频输入信号和误差值通过神经网络模型生成更新的神经网络输出。