Evaluation of Emotional Satisfaction Using Questionnaires in Voice-Based Human–AI Interaction

Round 1

Reviewer 1 Report

I enjoyed reading the paper. The authors have presented an interesting article about Evaluation of Emotional Satisfaction using Questionnaire in Voice-based Human-AI Interaction.

How do you think your findings can be useful applicable to other engineering disciplines?

Conslusion should be expanded.

Introduction is clear, but please explain in more detail in this chapter how the article relates to these topics:

• Examining the learning efficiency by a brain-computer interface system
• Speed control of Festo Robotino mobile robot using NeuroSky MindWave EEG headset based brain-computer interface
• A Brain–Computer Interface Project Applied in Computer Engineering
• Electroencephalogram-based brain-computer interface for internet of robotic things
• Examination and comparison of the EEG based attention test with CPT and TOVA

Author Response

Thanks for your time to review our manuscript, and for the favorable comment. Based on the reviewer’s comment, we substantially revised our manuscript. Please check our responses(in Word file) to the reviewer’s comment.

Author Response File: Author Response.docx

Reviewer 2 Report

The authors propose a study for investigating emotional satirsfaction in Voice-based Human-AI interaction.

The proposed study is interesting but there are some points that the authors should better discuss.

The authors should be better described the novelties of their study with respect to existing ones. In particular, the author should discuss limitation and cons of the examined approaches. Furthermore, the authors should provide more details and discussion about the obtained results. The Discussion section also needs to be improved by analyzing the outcome of evaluation section.

I suggest to further analyze more recent approaches about the examined topics. In particular, I suggest the following papers to further investigate emotional profile for different applications:

1) An emotional recommender system for music. IEEE Intelligent Systems.

2) Recommendation in social media networks. In 2017 IEEE Third International Conference on Multimedia Big Data (BigMM) (pp. 213-216). IEEE.

Finally, I suggest to perform a linguistic revision.

Author Response

Thanks for your time to review our manuscript, and for the favorable comment. Based on the reviewer’s comment, we substantially revised our manuscript. Please check our responses(in Word file) to the reviewer’s comment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

I think that the authors have addressed all my concerns.