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Hi, I'm Stanley

Yun-Shao Lin (Stanley)

PhD Student, Major in EE
BIIC lab, National Tsing Hua University, Taiwan
Email

astanley18074@gmail.com

 

Research Keywords

Multi-party Interaction Modeling, Behavioral Signal Processing, Machine Learning

 
EDUCATION
Feb 2018 - Present

Ph.D. student

National Tsing Hua University(NTHU)

Behavioral Informatics & Interaction Computation Lab (BIIC)

Ph.D. student in Electrical Engineering
Supervised by Prof. Chi-Chun (Jeremy) Lee

Sep 2016 - Feb 2018

Graduate student

National Tsing Hua University(NTHU)

Behavioral Informatics & Interaction Computation Lab (BIIC)

Graduate student in Electrical Engineering
Supervised by Prof. Chi-Chun (Jeremy) Lee

GPA: 4.23/4.3

May 2012 - Sep 2016

Bachelor's degree

National Tsing Hua University(NTHU)

B.S. in Electrical Engineering

GPA: 3.53/4.3

 

Awards / Honors

Awards/Honors

2019  - Merry Electronics - Merry Electroacoustic Thesis Award 

2018 - Yajie Miao Memorial Student Travel Grants

2018 - Interspeech Student Best Paper Award Candidate
2018 - National Tsing Hua University – President’s Scholarship
2017 - NOVATEK - Master Scholarship

2017 - FUJI XEROX - Academic Research Awards

2017 - Appier – Top Research Awards for Artificial Intelligence and Information Technology
2015 - National Tsing Hua University - Exchange Scholarship to Mainland China

Publications
 

[1] Yun-Shao Lin*, Chi-Chun Lee, “Predicting Performance Outcome with a Conversational Graph Convolutional Network for Small Group Interactions", in Proceedings of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020 - Accepted

[2] Sung-Lin Yeh, Yun-Shao Lin* and Chi-Chun Lee, "A Dialogical Emotion Decoder For Speech Emotion Recognition in Spoken Dialog", in Proceedings of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020 - Accepted

[3] Yun-Shao Lin*, Susan Shur-Fen Gau and Chi-Chun Lee, "A Multimodal Interlocutor-Modulated Attentional BLSTM for Classifying Autism Subgroups during Clinical Interviews", in IEEE Journal of Selected Topics in Signal Processing (JSTSP) - Accepted

[4] Huan-Yu Chen, Yun-Shao Lin* and Chi-Chun Lee, "Through the Eyes of Viewers: A Comment-Enhanced Media Content Representation for TED Talks Impression Recognition", in proceedings of APSIPA 2019

[5] Gao-Yi Chao, Yun-Shao Lin*, Chun-Min Chang, Chi-Chun Lee, "Enforcing Semantic Consistency for Cross Corpus Valence Regression from Speech using Adversarial Discrepancy Learning" in Proceedings of the International Speech Communication Association (Interspeech), 2019

[6] Shun-Chang Zhong, Yun-Shao Lin*, Chun-Min Chang, Yi-Ching Liu and Chi-Chun Lee, "Predicting Group Performances using a Personality Composite-Network Architecture during Collaborative Task", in Proceedings of the International Speech Communication Association (Interspeech), 2019

[7] Sung-Lin Yeh, Yun-Shao Lin*, Chi-Chun Lee, "An Interaction-Aware Attention Network for Speech Emotion Recognition in Dialogs", in Proceedings of International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019

[8] Yun-Shao Lin*, Chi-Chun Lee, "Using Interlocutor-Modulated Attention BLSTM to Predict Personality Traits in Small Group Interactions", in Proceedings of ACM International Conference on Multimodal Interaction (ICMI), 2018

[9] Yun-Shao Lin*, Susan Shur-Fen Gau, Chi-Chun Lee, "An Interlocutor-Modulated Attentional LSTM for Differentiating between Subgroups of Autism Spectrum Disorder" in Proceedings of the International Speech Communication Association (Interspeech), 2018

[10] Wei-Hao Chang, Jeng-Lin Li, Yun-Shao Lin*, Chi-Chun Lee,"A Genre-Affect Relationship Network with Task-Specific Uncertainty Weighting for Recognizing Induced Emotion in Music" in Proceedings of the IEEE International Conference on Multimedia & Expo (ICME), 2018

[11] Yun-Shao Lin*, Chi-Chun Lee, "Deriving Dyad-Level Interaction Representation using Interlocutors Structural and Expressive Multimodal Behavior Features" in Proceedings of the International Speech Communication Association (Interspeech), pp. 2366-2370, 2017

Group Monitor System
 
  • Small group specifically indicates the group with 3 to 6 members. In this project, we build an automatically tracking and visualizing system on people's behavior and apply it on small group interaction. There are 2 important goals for building the system. First, the system can quantize the member's behavior. Second, with the quantize data, it can facilitate the group interaction and also improve the efficiency of the group. There are 4 important features for this system, 

    System Feature 2 : Group Atmosphere

    Ranking the atmosphere based on members' behavior

     

    System Feature 3 : User Behavior

    Visualize user's facial, body gesture and vocal behavior

     

    System Feature 4 : Personal Report 

    Summarize User's Behavior and Predict Personality Trait

     

    System Feature 1 : Synchronized Recording

    Synchronize Recording Multi-Track Users' Behavior

     

Experience 
 
Mar 2019- Present
R&D

R&D

cooperate with E.SUN BANK
AST & TTS project

Apr 2018 – Feb 2019
R&D

R&D

cooperate with beBit, Inc.
Online User Behavior Analysis and Prediction

Sep 2018 – Jan 2019
Teaching Assistant

Teaching Assistant

National Tsing Hua University (NTHU)

Course: Speech Signal Processing

Mar 2018
Lecturer

Lecturer

Institute for Information Industry (III)

Topic: Artificial Intelligence on Medical Diagnostic Analysis and Application

Mar 2018 - Jun 2018

Teaching Assistant

Teaching Assistant

National Tsing Hua University (NTHU)

Course: Probability

Aug 2017 – Present

R&D
 

R&D

cooperate with HyXen Technology Co., Ltd.
User Behavior Analysis on Mobile Device for Advertisement

 
Skills

Programming

Python

C/C++

Matlab

Shell

Kaldi

Language

Mandarin Chinese (native)

English (proficient)

    * TOEFL: 92

    * TOEIC: 875

French (intermediate)

    * DELF A2 

 
CONTACT ME

Yun-Shao Lin

Email:

astanley18074@gmail.com

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