Dogs communicate intelligently but little is known about the phonetic properties of their vocalization communication. For the first time, this paper presents an iterative algorithm inspired by human phonetic discovery, which is based on minimal pairs that determine phonemes by distinguishing different words in human language, and is able to produce a complete alphabet of distinct canine phoneme-like units. In addition, the algorithm produces a number of canine repeated acoustic units, which may correspond to specific environments and activities of a dog, composed exclusively of the canine phoneme-like units in the alphabet. The framework outlined in this paper is expected to function not only on canines but other animal species.