Biodiversity is the foundation for human survival and sustainable social development, embodying the lifeblood and foundation of the Earth’s living community. Acoustic recognition technology is emerging as a significant tool in assisting biodiversity monitoring. Characterized by acoustic data collection and advanced computational bioacoustics, acoustic technology demonstrates advantages in species identification, population research, and environmental cause exploration. This study takes the Huanglong National Scenic Area as an example, collecting over 6,000 minutes of data under two distinct human impact intensities within the protected area. Through a combination of classical acoustic index calculations, artificial intelligence species identification, and line transect surveys, it is concluded that: (1) birds exhibit diverse call time distribution characteristics under artificial intelligence technology; (2) Acoustic recognition technology outperforms traditional survey methods in terms of effectiveness; (3) The calculation of acoustic indices demonstrates responsiveness to environmental factors and its validation. This study experimentally analyzes and interprets the collected data, using Huanglong as a case study to pioneer this methodological approach, making it highly valuable and applicable for conservation management in similar protected areas.