Here’s a laughing robot as companion in future

Scientists are trying to make it more normal instead of just maniacally laughing at your jokes

By Kiran N. Kumar

Researchers at Kyoto University in Japan are busy building a humanoid robot with more empathic AI systems and teaching it how to laugh at your jokes giving you a realistic companion especially for an aging society.

Named Erica, the humanoid robot can hear you laugh and then decides whether to respond in a small chuckle or a more boisterous giggle.

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The research, published in the journal Frontiers in Robotics and AI, illustrates how a humanoid robot that has been synthesized with human voice, blinking of eyes while conversing with humans and even responding to your laugh equally with instant decision. The scientists are working on how to make it more normal instead of maniacally laughing at your jokes.

Japan has been the pioneer in humanoid robots and it has unveiled a series of multi-tasking robots who can double as companions at your home, especially for the elderly. Japan’s shrinking young population requires more empathic robots to keep in pace with the future needs.

Other robots such as ElliQ tackles loneliness among the elderly giving them company while Ollie’s creators claim to help stimulate patients with dementia or Alzheimer’s disease.

Besides, robots are already helping humans in tedious tasks ranging from stacking heavy boxes in a warehouse, harvesting vegetables on a vertical farm, to even unclogging your pipes. The robotics industry is estimated to be $19 billion by 2027.

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“Laughter is a non-linguistic behavior but is also dependent on the context of dialogue, including culture,” the team said. “Therefore, it is a future task to verify the generalizability of the proposed method in other languages and with large-scale data.”

Divesh Lala, one of the authors of the research paper, said:“One of the ways we show how we understand emotion or understand a situation is through laughter.”

Whenever a person imitates the other or mirrors the act, there is a possibility of a strong rapport developing between them. Similarly, Erica is being trained by researchers to mirror a human’s laugh so it can bond with people.

The team, which has been working on a laughing robot since 2016, published the results this week on creating a model of shared laughter generation for conversational robots. As part of this system, they trained models which predict if shared laughter will occur, given that the user has laughed.

Models have been trained using combinations of acoustic, prosodic features and laughter type were compared with online versions replicating a real system.

They gathered data from over 80 dialogues between male university students and the robot, and then analyzed various laughs to categorize them as “social” — like the kind where you laugh just to be polite and “mirthful” — like that genuine giggle when your best friend cracks a good joke.

“If you assume every laugh is equal, you’re going to respond to everything, but if you respond to nothing, it’s also embarrassing,” said Lala. “If a robot can distinguish between the two, it’s a useful finding.”

As the laughing algorithm is rather limited, the researchers integrated it with other features like natural language processing and back-channeling to make it more conversant and responsive to help older people fight social isolation.

Read: To Bond With Humans, Robots Are Learning to Laugh at the Right Time (September 19, 2022)

“If they talk with a robot, maybe they can practice laughing at the right time, but you got to be careful with this, you don’t want to be relying too much on the robot,” he cautions.

However, Erica model is still far from joining the real time humanoid robots, at least for a decade. “Erica doesn’t understand the kind of sense of humor, but if she reacts to the user’s laugh, maybe the user feels [like] she understands something,” said Koji Inoue, the lead author of the study. “Our target is human-like interaction.”

But that’s still limited as the study has to further explore gender aspects, timing of shared laughter and overlapping shared laughter.

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