Addressee Detection Using Facial and Audio Features in Mixed Human–Human and Human–Robot Settings: A Deep Learning Framework-Reference-Cited by-同舟云学术

Addressee Detection Using Facial and Audio Features in Mixed Human–Human and Human–Robot Settings: A Deep Learning Framework

Published:2023-04 Issue:2 Volume:9 Page:25-38
ISSN:2333-942X
Container-title:IEEE Systems, Man, and Cybernetics Magazine
language:
Short-container-title:IEEE Syst. Man Cybern. Mag.

Author:

Tesema Fiseha B.¹^ORCID,Gu Jason²^ORCID,Song Wei³^ORCID,Wu Hong⁴,Zhu Shiqiang⁵,Lin Zheyuan⁶,Huang Min⁶,Wang Wen⁷,Kumar Rajesh⁸^ORCID

Affiliation:

1. Postdoctoral Fellow, Zhejiang Lab, Hangzhou, Zhejiang Province, P.R. China

2. Engineering Institute of Canada, Halifax, NS, Canada

3. Principal Investigator, Zhejiang Lab, Hangzhou, Zhejiang Province, P.R. China

4. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, P.R. China

5. Director of Zhejiang Lab, Hangzhou, Zhejiang Province, P.R. China

6. Engineer, Zhejiang Lab, Hangzhou, Zhejiang Province, P.R. China

7. Assistant Researcher, Zhejiang Lab, Hangzhou, Zhejiang Province, P.R. China

8. Associate professor, Yangtze Delta Region Institute (Huzhou), UESTC, Huzhou, China

Funder

Ten Thousand Talents Program

Zhejiang Lab Postdoctoral Start-Up Fund

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Human Factors and Ergonomics,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/6745853/10104106/10104108.pdf?arnumber=10104108

Reference49 articles.

1. A comparison of addressee detection methods for multiparty conversations;op den akker;Proc 13th Semdial Workshop Semantics Pragmatics Dialogue,0

2. Combining Residual Networks with LSTMs for Lipreading

3. Speaker Localisation Using Audio-Visual Synchrony: An Empirical Study

4. Evaluation of Multi-Party Reality Dialogue Interaction