Researchers at the University of Michigan are harnessing artificial intelligence (AI) to decode the nuanced communications of dogs, aiming to determine whether a bark signals playfulness or anger. Their innovative approach also explores whether AI can accurately identify a dog‘s age, gender, and breed based on its vocalizations.
The team achieved significant progress in understanding canine communication by adapting existing computer models originally designed for human speech analysis.
“Advances in AI can be used to revolutionize our understanding of animal communication,” said Rada Mihalcea, head of the University of Michigan AI Laboratory. “Our research opens a new window into how we can leverage what we built so far in speech processing to start understanding the nuances of dog barks.”
AI technology has significantly advanced in deciphering human speech subtleties, distinguishing tone, pitch, and accent. These AI-powered systems, trained on vast datasets of human voices, enable technologies like voice-recognition software. However, a comparable database for dog vocalizations does not exist.
“Animal vocalizations are logistically much harder to solicit and record,” noted Artem Abzaliev, the study’s lead author. To overcome this challenge, his team repurposed human speech research for canine communication. They collected barks, growls, and whimpers from 74 dogs of various breeds, ages, and sexes in different contexts and fed these sounds into a machine-learning model designed to analyze human speech.
Remarkably, the model effectively interpreted the dogs’ communications, achieving an average accuracy of 70% across various tests.
“This is the first time that techniques optimized for human speech have been built upon to help with the decoding of animal communication,” said Mihalcea. “Our results show that the sounds and patterns derived from human speech can serve as a foundation for analyzing and understanding the acoustic patterns of other sounds, such as animal vocalizations.”
The researchers believe their findings have significant implications for animal welfare. A better understanding of the nuances in animal vocalizations could enhance how humans interpret and respond to the emotional and physical needs of animals.
The results were presented at the Joint International Conference on Computational Linguistics, Language Resources and Evaluation. The project also involved collaboration with Mexico’s National Institute of Astrophysics, Optics and Electronics Institute.
Related Topics:
