Training and learning model for recognizing acoustic signal

A method of training a learning model for recognizing an acoustic signal, the method comprising:

• identifying an acoustic signal comprising an acoustic event or acoustic scene and a label representing the acoustic event or acoustic scene included in the acoustic signal;
• determining an acoustic feature of the acoustic signal;
• dividing the determined acoustic feature for each of a plurality of frequency band intervals;
• and
• training the learning model using the acoustic feature divided by each of the plurality of frequency band intervals and the label,
• wherein the dividing comprises dividing the acoustic feature into frequency band intervals of different lengths based on a frequency axis of the acoustic feature.

A recognition device for performing a method of recognizing an acoustic signal, the recognition device comprising:

• a processor,
• wherein the processor is configured to:
• identify an acoustic signal comprising an acoustic event or acoustic scene,
• determine an acoustic feature of the acoustic signal,
• divide the determined acoustic feature for each of a plurality of frequency band intervals, and
• determine the acoustic event or acoustic scene included in the acoustic signal by inputting the divided acoustic features to a trained learning model,
• wherein the processor is further configured to divide the acoustic feature into frequency band intervals of different lengths based on a frequency axis of the acoustic feature.