Author Archives: Julie Cattiau

AI’s killer (whale) app

The Salish Sea, which extends from British Columbia to Washington State in the U.S., was once home to hundreds of killer whales, also known as orcas. Now, the population of Southern Resident Killer Whales, a subgroup of orcas, is struggling to survive—there are only 73 of them left. Building on our work using AI for Social Good, we’re partnering with Fisheries and Oceans Canada (DFO) to apply machine learning to protect killer whales in the Salish Sea.

According to DFO, which monitors and protects this endangered population of orcas, the greatest threats to the animals are scarcity of prey (particularly Chinook salmon, their favorite meal), contaminants, and disturbance caused by human activity and passing vessels. Teaming up with DFO and Rainforest Connection, we used deep neural networks to track, monitor and observe the orcas’ behavior in the Salish Sea, and send alerts to Canadian authorities. With this information, marine mammal managers can monitor and treat whales that are injured, sick or distressed. In case of an oil spill, the detection system can allow experts to locate the animals and use specialized equipment to alter the direction of travel of the orcas to prevent exposure.

To teach a machine learning model to recognize orca sounds, DFO provided 1,800 hours of underwater audio and 68,000 labels that identified the origin of the sound. The model is used to analyze live sounds that DFO monitors across 12 locations within the Southern Resident Killer Whales’ habitat. When the model hears a noise that indicates the presence of a killer whale, it’s displayed on the Rainforest Connection (a grantee of the Google AI Impact Challenge) web interface, and live alerts on their location are provided to DFO and key partners through an app that Rainforest Connection developed.

Our next steps on this project include distinguishing between the three sub-populations of orcas—Southern Resident Killer Whales, Northern Resident Killer Whales and Biggs Killer Whales—so that we can better monitor their health and protect them in real time. We hope that advances in bioacoustics technology using AI can make a difference in animal conservation.

How Tim Shaw regained his voice

His entire life, Tim Shaw dedicated himself to football and dreamed of playing professionally. At 23, his dream came true when he was drafted and spent six years as an NFL linebacker. Then, in 2013, Tim felt his body begin to change. It started with small muscle twitches or bicep spasms; once, a gallon of milk slipped out of his hand while he was unloading groceries. During a game when he was perfectly positioned to tackle his opponent, his arm couldn’t hang on and the player slid past. His performance kept inexplicably declining and just before the 2013 season, Tim was cut from the Titans. 


Five months later, Tim was diagnosed with Amyotrophic Lateral Sclerosis (ALS, also known as Lou Gehrig’s disease). With no known cause or cure, ALS not only impacts movement, but can make speaking, swallowing and even breathing difficult. Through our partnership with the ALS Therapy Development Institute, we met Tim and learned that the inability to communicate was one of the hardest parts of living with the disease. We showcase Tim’s journey in the new YouTube Originals learning series “The Age of A.I.” hosted by Robert Downey Jr.


For many people with ALS, losing their voice can be one of the most devastating aspects of the disease. But technology has the potential to help. Earlier this year, we announced a research project called Project Euphonia, which aims to use AI to improve communication for people who have impaired speech caused by neurologic conditions, including ALS. When we heard Tim's story, we thought we might have a way to help him regain a part of identity he'd lost—his voice. 


Current text-to-speech technology requires at least 30-40 minutes of recordings to create a high-quality synthetic voice—which people with ALS don’t always have. In Tim’s case, though, we were able to pull together a bank of voice samples from the many interviews he had done while playing for the NFL. The DeepMind, Google AI and Project Euphonia teams created tools that were able to take these recordings and use them to create a voice that resembles how Tim sounded before his speech degraded; he was even able to use the voice to read out the letter he’d recently written to his younger self. While it lacks the expressiveness, quirks and controllability of a real voice, it shows that this technology holds promise. 


"It has been so long since I've sounded like that, I feel like a new person,” Tim said when he first heard his recreated voice. “I felt like a missing part was put back in place. It's amazing." 


In the aforementioned letter, Tim told his younger self to “wake up every day and choose to make a positive impact on other people.” Our research and work with Tim makes us hopeful we can do just that by improving communication systems and ultimately giving people with impaired speech more independence. You can learn more about our project with Tim and the vital role he played in our research in “The Age of A.I.” now streaming on YouTube.com/Learning.