Gabriel Skantze talks about how he works with human robot communication, and about how the social robot revolution makes it necessary to communicate with humans in a human ways through speech and facial expressions. This is necessary as we expand the number of people that interact with robots as well as the types of interaction.
Gabriel gives us more insight into the many challenges of implementing spoken communication for co-bots, where robots and humans work closely together. They need to communicate about the world, the objects in it and how to handle them.
We also get to hear how having an embodied system using the Furhat robot head helps the interaction between humans and the system.
Having an expressive face like the Furhat adds many improvements to how a system can communicate with people. It also improves the human engagement and understanding of what the system tries to communicate significantly.
Gabriel then talks about the how they use AI and machine learning to understand speech. Understanding an individual speaker’s way to speak, thus adapting a robot to its user can improve their communication.
As the Furhat system is used out in the field, we get valuable insights from real world situations. One such case is guiding travellers at an airport to improve their experience and make travelling more efficient for everyone.
This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.
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