The North Atlantic Right Whale (NARW) population is currently teetering on the brink of extinction, with a mere approximate count of 350 individuals remaining. These animals have been protected under the Endangered Species Act since 1970. Today, the survival of right whales is imperiled primarily due to vessel collisions, net entanglements, and habitat degradation. This paper presents a novel system of animal-computer interaction founded on the identification of bioacoustic signatures. Initially, NARWs' vocalizations were transformed into spectrograms, which were subsequently inputted into a Convolutional Neural Network (CNN). To enhance robustness against environmental noise, techniques such as time warping, frequency masking, and time masking were employed. The outcomes of our study indicate that the proposed system holds potential for establishing a closed-loop interaction framework between vessels and NARWs. This framework could enable vessels to adapt their speed or avoid routes frequented by NARWs. Furthermore, this article discusses the potential benefits of employing networked sensors, such as Internet of Things (IoT) devices, to augment NARW monitoring and data collection efforts.