Cetaceans are an important part of the ocean ecosystem and are widely distributed in seas across the world. Cetaceans are heavily reliant on acoustic signals for communication. Some Odontoceti can perceive their environments using their sonar system, including the detection, localization, discrimination, and recognition of objects. Acoustic signals are one of the most commonly used types of data for Cetacean research, and it is necessary to develop Cetacean acoustic signal detection methods. This study compared the performance of a manual method, short-time Fourier transform (STFT), and wavelet transform (WT) in Cetacean acoustic signal detection. The results showed that WT performs better in click detection. According to this research, we propose using STFT for whistle and burst-pulse marking and WT for click marking in dataset building. This research will be helpful in facilitating research on the habits and behaviors of groups and individuals, thus providing information to develop methods for protecting species and developing biological resources.