In the field of robotics, researchers have been exploring ways to improve communication between humans and robots. One approach is to use verbal explanations to help robots explain their decision-making processes to humans. Studies have shown that using natural language explanations can significantly enhance transparency and accuracy in communication between humans and robots. However, the choice of words and tone of voice are crucial in conveying meaning effectively.
The article highlights the importance of optimally choosing when to provide verbal feedback to humans. The authors suggest that using written language instead of natural language explanations can help convey the same message more clearly. Additionally, they note that the tone of verbal feedback can unintentionally communicate emotion, and humans often reinforce their speech with non-verbal gestures.
To address these challenges, the article proposes a learning architecture that is easy for humans to parse and explain. Post-hoc approaches learn using existing methods, and then convert the learned models back into feedback signals for the human.
In simple terms, verbal explanations can help robots communicate more effectively with humans. However, it’s important to choose the right words and tone of voice to ensure that the message is conveyed clearly and accurately. By using written language or non-verbal gestures, we can improve the communication between humans and robots even further.
Key Takeaways
- Verbal explanations can significantly enhance transparency and accuracy in human-robot communication.
- The choice of words and tone of voice are crucial in conveying meaning effectively.
- Using written language instead of natural language explanations can help convey the same message more clearly.
- Non-verbal gestures often reinforce spoken communication, and can impact how humans understand robot intentions.
