Cracking Canine Code

What if the next time you asked Fido, “Who’s a good boy?” you could understand his response?

Kenny Zhu, professor of computer science and engineering, is using machine learning to translate dog sounds into phonetic representations and, eventually, words. His work is funded by a National Science Foundation Research Experiences for Undergraduates grant.

“Scientists have been trying to decode the noises of whales, dolphins, and chimpanzees for many years, but most of that research has been conducted by biologists or ecologists with little computer science knowledge,” Dr. Zhu says. “That’s changing, and now the use of machine learning has been introduced to analyze data. My research is in natural language processing for humans, so why not look at how animals communicate?”

To collect the sounds, Zhu downloads videos from YouTube and other sources and strips away all other noise in the audio file except for the sound of the bark. He uses machine learning to catalog the sounds, segment them into pieces like syllables, and assigns each syllable a symbol. To date, Zhu has transcribed about 10 hours of barks.

“Machine learning plays a role in everything we’re doing in this project,” he says. “It’s a great opportunity for students to learn about big data analysis and explore how machine learning can be applied in areas that it hasn’t been before.”

See a CBS 11 news report featuring Zhu and his canine collaborators.