Automatic environmental noise source classification model using fuzzy logic

Noise classification is very important nowadays. Fuzzy logic has been applied to many interesting problems in different areas including noise identification/recognition. With this study, we propose an automatic environmental noise source classifier based on fuzzy logic. The proposed classifier uses the feature parameters that are extracted using short-time auto-correlation function. Six commonly encountered non-stationary noise sources are chosen to recognize. These are subway, airport, inside car, inside train, restaurant, and rain. Classification accuracy of the proposed classifier ranged from 62% to 90% rates.

Research Highlights
► We propose an automatic environmental noise source classifier based on fuzzy logic.
► Feature parameters are extracted by using short-time auto-correlation function.
► We used six different non-stationary noise sources to recognize.
► We conclude that our classifier achieves the classification accuracies in the range of 62% to 90%.