Scientists teach robot to laugh at jokes
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Researchers at Kyoto University in Japan have designed an artificial intelligence (AI) system that appropriately responds to human laughter.
The shared-laughter AI system is being used to train a robot called Erica to detect laughter from those around 'her', then decide whether to laugh and what kind of laughter would be best, differentiating between light chuckles and rip-roaring peals of laughter.
The scientists' findings - described in the journal Frontiers in Robotics and AI - could in future help make conversations between humans and robots more natural.
“We think that one of the important functions of conversational AI is empathy,” said lead author Dr Koji Inoue. “Conversation is, of course, multimodal, not just responding correctly. We decided that one way a robot can empathise with users is to share their laughter, which you cannot do with a text-based chatbot.”
In the shared-laughter model, a human initially laughs and the AI system responds with laughter as an empathetic response. This approach required designing three subsystems – one to detect laughter, a second to decide whether to laugh and a third to choose the type of appropriate laughter.
In order to test the system, the researchers gathered training data by annotating more than 80 dialogues from speed dating, a social scenario where large groups of people mingle, or interact, with each other one-on-one for a brief period of time. In this case, the matchmaking marathon involved various students from Kyoto University meeting Erica, teleoperated by several amateur actresses.
“Our biggest challenge in this work was identifying the actual cases of shared laughter, which isn’t easy, because as you know most laughter is actually not shared at all,” Inoue said. “We had to carefully categorise exactly which laughs we could use for our analysis and not just assume that any laugh can be responded to.”
The team eventually tested Erica’s new sense of humour by creating four short two to three-minute dialogues between a person and Erica with her new shared-laughter system.
In the first scenario, she only uttered social laughter, followed only by mirthful laughs in the second and third exchanges, with both types of laughter combined in the last dialogue. The team also created two other sets of similar dialogues as baseline models. In the first one, Erica never laughed. In the second, Erica uttered a social laugh every time she detected a human laugh, without using the other two subsystems to filter the context and response.
The researchers crowdsourced more than 130 people in total to listen to each scenario within the three different conditions and evaluated the interactions based on empathy, naturalness, human likeness and understanding. The shared-laughter system performed better than either baseline.
“The most significant result of this paper is that we have shown how we can combine all three of these tasks into one robot. We believe that this type of combined system is necessary for proper laughing behaviour, not simply just detecting a laugh and responding to it,” Inoue said.
The system, however, still needs development in order to ensure that the conversations with Erica accurately resemble those between real people and reflect situations like unshared laughter, which is the most common type, according to the researchers.
“Robots should actually have a distinct character and we think that they can show this through their conversational behaviours, such as laughing, eye gaze, gestures and speaking style,” Inoue added.
“We do not think this is an easy problem at all and it may well take more than 10 to 20 years before we can finally have a casual chat with a robot like we would with a friend.”
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