In general, computer-generated speech and interaction patterns are very rigid and people may not want to communicate with them. And between people, such as children playing with each other, they conduct more verbal communication and are often more successful. In the study, the researchers teamed up with children and robots to allow them to play platform games. One player told the character to go and another player told the character to jump. They developed this system by listening to the child's voice and extracting some basic features: loudness, byte length, and frequency. For example, some children may respond quickly, but when they jump, they may be prolonged. The other children responded with a bit of hesitation, but they were faster and louder when they said they were going. When the child's speaking style is confirmed, the robot can choose verbal responses from slightly different sound files, and the tone and speed of speech are also slightly changed. In one case, it chooses the style of speech that is closest to the child. In other cases, it basically can choose any style other than children. Each child plays synchronous and asynchronous multiplayer games with the robot. The results showed that children with a similar choice of speaking style robots have higher participation and scores. And when they play an out-of-synch version, the child scores lower and is less active. In further analysis, it was found that this difference only affects older children. This means that people’s willingness to cooperate is through socially learned skills.
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