| 摘要 |
A method for testing an audio device with a trained neural network includes a loopback connector connecting the output port of the audio device to the input port of the audio device. A test signal is transmitted through the audio port and received at the input port. The test signal is converted into a frequency spectrum for analysis. The frequency spectrum is provided as input to a trained neural network, the neural network being previously trained to recognize the frequency spectrum pattern created by a properly working, or ideal, audio device. The neural network is trained by connecting the input port to the output port of an audio device from which the training is to occur. Prior to converting signals to a frequency spectrum, the waveform characteristics of the signal may be iteratively evaluated and recording levels adjusted so that the signal received has characteristics that can be tested by the neural network. The analyzed signal may be a portion of the signal received after analog to digital converters in the audio device have stabilized. The neural network generates a confidence level based on comparing the pattern of the tested audio device's frequency spectrum to the frequency spectrum of a working audio device. A pass value may be predetermined so that the tested audio device is reported as passing or failing the test by comparing the confidence level value generated by the system with the predetermined pass value.
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