Apparatus and method for sound anomaly detection based on non-compression convolutional neural network

A sound anomaly detection method comprising:

• acquiring, by an audio unit, a noise from an inspection target;
• generating, by a data processing unit, an input value that is a feature vector matrix including a plurality of feature vectors from the noise;
• generating, by a detection unit, a restored value imitating the input value through a detection neural network that is a deep neural network learned for the input value;
• determining, by the detection unit, whether a restoration error indicating a difference between the input value and the restored value is greater than or equal to a calculated reference value;
• and
• determining, by the detection unit, that there is an anomaly in the inspection target when determining that the restoration error is greater than or equal to the reference value,
• wherein generating the restored value includes:
• calculating, by an encoder of the detection neural network, a latent value from the input value without dimension reduction, and
• calculating, by a decoder of the detection neural network, the restored value from the latent value without dimension expansion.