Abstract—Lung sound signal is a physiological acoustic signals generated outside the human respiratory system and in the ventilation process. It contains a wealth of physiological and pathological information and has great value in research. In recent years, environmental problems, like air pollution and the weather with fog and haze, has led to a rise in the incidence of respiratory disease. To meet the growing demand for fast and accurate diagnosis of lung disease, auscultation has attracted more attention with its convenience and safety, yet it shows limitations as it depends on the experience and the hearing capacity of the physician and the limited frequency response of the stethoscope. With the development of automated lung sound diagnostic techniques and hardware, lung sound classification by computer, which make up for the defect in traditional auscultation. In this paper we introduced the concept of lung sounds, computer-based lung sound signal processing and pattern recognition techniques, and the recent development of machine learning-based lung sounds classification techniques were summarized. Finally, the research and application development trend of lung sounds classification techniques were discussed.