-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathindex-2020.html
401 lines (326 loc) · 21.1 KB
/
index-2020.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
<!DOCTYPE html>
<html>
<head>
<title>IS4152 Affective Computing (@ NUS)</title>
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<!-- Bootstrap -->
<link href="css/bootstrap.min.css" rel="stylesheet" media="screen">
<!-- my modifications -->
<link href="css/mycss.css" rel="stylesheet">
</head>
<body>
<!-- Part 1: Wrap all page content here -->
<!-- <div class="wrap"> -->
<!-- Fixed navbar -->
<!-- <div class="navbar navbar-fixed-top">
<div class="navbar-inner">
<div class="container">
<button type="button" class="btn btn-navbar" data-toggle="collapse" data-target=".nav-collapse">
<span class="icon-bar"></span>
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</button>
<a class="brand" href="index.html">IS4152</a>
<div class="nav-collapse collapse">
<ul class="nav">
<li class="divider-vertical"></li>
<li class="active"><a href="index.html">Home</a></li>
<li><a href="#overview">Overview</a></li>
<li><a href="#schedule">Schedule</a></li>
<li><a href="#references">References</a></li> -->
<!-- <li><a href="others.html">Others</a></li> -->
<!--
<li class="dropdown">
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Dropdown <b class="caret"></b></a>
<ul class="dropdown-menu">
<li><a href="#">Action</a></li>
<li><a href="#">Another action</a></li>
<li><a href="#">Something else here</a></li>
<li class="divider"></li>
<li class="nav-header">Nav header</li>
<li><a href="#">Separated link</a></li>
<li><a href="#">One more separated link</a></li>
</ul>
</li>
-->
<!-- </ul>
</div>
</div>
</div>
</div> -->
<!-- Top Navigation Bar -->
<!-- <nav class="navbar navbar-expand-lg navbar-dark bg-dark fixed-top"> -->
<nav class="navbar navbar-expand-lg navbar-light bg-light fixed-top">
<div class="container">
<a class="navbar-brand" href="index.html">IS4152: Affective Computing</a>
<button class="navbar-toggler" type="button" data-toggle="collapse"
data-target="#navbarResponsive" aria-controls="navbarResponsive" aria-expanded="false" aria-label="Toggle navigation">
<span class="navbar-toggler-icon"></span>
</button>
<div class="collapse navbar-collapse" id="navbarResponsive">
<!-- <ul class="navbar-nav ml-auto"> -->
<ul class="navbar-nav mr-auto">
<li class="nav-item">
<a class="nav-link" href="#overview" data-target="#overview">Overview</a>
</li>
<li class="nav-item">
<a class="nav-link" href="#logistics" data-target="#logistics">Logistics</a>
</li>
<li class="nav-item">
<a class="nav-link" href="#schedule">Project</a>
</li>
<li class="nav-item">
<a class="nav-link" href="#schedule">Schedule</a>
</li>
</ul>
</div> <!-- End of div class="collapse navbar-collapse" -->
</div> <!-- End of div class="container" -->
</nav> <!-- End of Navigation Bar -->
<!-- Begin page content -->
<div class="container">
<!--
<div class="page-header">
<h1>Sticky footer with fixed navbar</h1>
</div>
<p class="lead">Pin a fixed-height footer to the bottom of the viewport in desktop browsers with this custom HTML and CSS. A fixed navbar has been added within <code>#wrap</code> with <code>padding-top: 60px;</code> on the <code>.container</code>.</p>
-->
<div class="row-fluid">
<div class="span12">
<center>
<h2>IS4152: Affective Computing</h2>
<h4>Department of Information Systems and Analytics <br> National University of Singapore </h4>
<h4>Semester 1, AY2020-2021</h4>
</center>
</div>
</div>
<div class="row">
<div class="col-md-6">
<h4> Instructor </h4>
  <a href="https://web.stanford.edu/~dco">Desmond Ong</a>, Assistant Professor
<br>
  Contact: dco (at) nus (dot) edu (dot) sg
<br>
  Office: COM2-04-29 [by-appointment only] <!-- make a you can book me? or something similar? -->
<br>
</div>
<div class="col-md-6">
<h4>Class Details </h4>
  Class Times: Fridays 10am-12pm [from August - November 2020]
<br>
  Location: COM1 Seminar Room 2 (COM1-02-04), and Online on Zoom
<br>
</div>
</div>
<br>
<div class="row-fluid">
<div class="span10 offset1">
<br>
<a name="overview">
<!-- <a class="anchor" name="overview"> -->
<h3 style="padding-top: 64px; margin-top: -64px;">Overview</h3>
</a>
<h4>Bulletin Listing</h4>
<p>
This module provides a broad introduction to the field of affective computing, focusing on the integration of psychological theories of emotion with the latest technologies. Students can look forward to learning about contemporary theories of emotion, empathy, emotion regulation; automated emotion recognition from video, speech, and text; automated affect generation in human-computer interaction; commercial affective computing technologies, including potential interaction with local startups. Students will work in groups on a semester-long project that may take several forms, such as the incorporation of emotion recognition into a prototype system, or critical evaluation of commercial affective computing technologies.
</p>
<h4>Course Overview</h4>
<p>
Everyone has emotions, and so, being able to use automated information systems to interface with people's emotions is becoming an important --- and commercially lucrative --- capability for many technology companies. This course provides a broad introduction to psychological theories of emotion and how modern technologies are used to recognize, reason about, and generate emotions, and there will be a strong emphasis on critically evaluating contemporary affective computing technologies, including a discussion on the latest developments.
<br><br>
We will begin with an introduction to scientific theories of emotion and how scientists define and measure emotions. We will then proceed with a survey of current affective computing technologies: What are the technologies that power facial emotion expression recognition, emotional speech recognition, text-based emotion analytics, as well as analytics from physiological sensors and other modalities? How do we (and how should we) design emotion-based applications, and emotional agents like chatbots, virtual characters and robots? What are the current capabilities as well as the current limitations of today's affective computing technologies, and what are the barriers to progress?
<br><br>
This course covers contemporary material that is at the forefront of modern psychology and technology. Throughout the course, we will rely mainly on reading recent academic papers, both theoretical and empirical. To solidify understanding and also to apply what they have learnt, students will work in groups to propose, design, and execute a semester-long project. Projects can take many forms, such as a critical evaluation of an existing technology or the development of new software or app that harnesses technology to gain more insight into their users' emotions.
</p>
<h4> Learning Objectives </h4>
<p>
By the end of the course:
<ul>
<li> Students will be able to discuss scientific theories of emotion, and assess the scientific validity of affective computing technologies. </li>
<li> Students will be able to discuss recent advances in affective computing technologies, including Affect Recognition technologies (from different modalities) and Affect Generation technologies. </li>
<li> Students will be able to discuss and analyse various commercial applications of affective computing. </li>
<li> Students will complete a research project that examines affective computing technologies within a certain context. </li>
</ul>
</p>
<h4> Brief outline of topics </h4>
<p>
<ul>
<li> Theories of Emotions and Emotion Measurement </li>
<li> Emotion Recognition </li>
<ul>
<li> From images (facial expression analysis) </li>
<li> From natural language text (e.g., sentiment analysis, applicable to social media like Twitter) </li>
<li> Multimodal Emotion Recognition </li>
</ul>
<li> Emotion Modelling </li>
<li> Emotion Generation </li>
<ul>
<li> Virtual Agents </li>
<li> Affective Robotics </li>
</ul>
<li> Ethical Issues in Affective Computing </li>
<li> Affective Computing Companies </li>
<ul>
<li> Large Companies and Small Startups / Multinational and Local Companies </li>
</ul>
<li> Affective Computing Applications </li>
<ul>
<li> Emotion Regulation and Mental Health </li>
<li> Affective Computing for Assistive Technologies </li>
<li> Affective Tutoring </li>
</ul>
<li> Special Topics (time permitting) </li>
</ul>
Depending on schedule availability, we may also invite guest lecturers from other departments, schools, or industry, to share their expertise with us.
</p>
<a name="logistics">
<!-- <a class="anchor" name="overview"> -->
<h3 style="padding-top: 64px; margin-top: -64px;"> Logistics </h3>
</a>
<h4> Pre-requisites </h4>
<p>
Students are assumed to have a high level of maturity and competency in programming and coding: no programming will be taught in this class. The course content will also require some familiarity with machine learning. Depending on the final course project they choose, students may require skills in machine learning, video and other data analytics, software development.
<br>
</p>
<h4> Readings </h4>
<p>
Readings will mostly consist of academic papers and excerpts from selected books. They will be made available on LumiNUS. Students are expected to do the readings for a particular week <b>before</b> class, in order to facilitate a productive and intellectually stimulating discussion in class. To incentivize keeping up with the readings, there will be short weekly quizzes.
<br><br>
In the reading list (appended at the end of the schedule), there is also a set of optional readings and other resources for the interested student (which could be relevant to class projects). A handy reference is the following Handbook, which summarizes many of the important topics in Affective Computing:
<ul>
<li> Calvo, R. A., D'Mello, S., Gratch, J. M., & Kappas, A. (Eds.). (2015). <i>The Oxford Handbook of Affective Computing</i>. Oxford University Press, USA. </li>
</ul>
The full text is available online via NUS libraries [<a href="https://linc.nus.edu.sg/record=b3481294">link</a>, then click Access via Oxford Handbooks Online]
</p>
<h4> Grading </h4>
<ul>
<li>
35% Weekly Quizzes
</li>
<li>
50% Class Project
</li>
<ul>
<li> 10% Project Proposal : Due Week 6 </li>
<li> 20% Final Project Presentation : Due Week 13 (at showcase) </li>
<li> 20% Final Project Report : Due Week 13 </li>
</ul>
<li>
15% Class Participation (including forum discussions)
</li>
</ul>
<h4> Forum Discussions </h4>
<p>
We will be using Piazza as a forum. Please use the forum to discuss questions relevant to affective computing, project implementation issues, or share/summarize relevant articles.
</p>
<h4> Quizzes </h4>
<p>
There will be weekly quizzes conducted at the start of each class, assessed on the readings of that class. Instructions will be given in class.
</p>
<h4> Expectation / Time commitment </h4>
<p>
This will be an intensive course. There is no homework. But there are many readings which are essential to your learning, quizzes to test your understanding, and a semester-long class project. How much time the class project takes up will depend on a lot of factors: your ambition, your existing skills, the learning curve for skills you need to pick up. As with all research and development projects, I assure you that if you put in the required work, you will finish the class with a final project that you will be proud of and that showcases what you have learnt.
</p>
<h4> Academic Integrity </h4>
<p>
<ul>
<li>
<b>Plagiarism is unacceptable</b>. If we find any evidence of plagiarism (for example, copying text wholesale from a website, an academic paper, or another source without proper citation) or any other forms of academic dishonesty (for example, cheating on a quiz), you will receive a zero, and you may face disciplinary action by the university.
</li>
<ul>
<li>
Exceptions: You may use portions of your Project Proposal in your Final Report, i.e., within the class (and you can do this without citing your Proposal).
</li>
</ul>
<li>
But: you may not use portions of any of your previous work outside this class (previous class papers; previous or current research projects) without the prior approval of the instructor.
</li>
<li>
Note that this also applies to code that you write. I'm a big fan of open-source code and will recommend several open-sourced resources throughout the course, but you should still cite your sources, especially if you modified or adapted a complex piece of code. If it forms a big part of your project, I expect citation in the project writeup. Otherwise, commented citations in your code will suffice. Merely citing does not license you to use copyrighted material, so do not use any copyrighted or proprietary software without appropriate permission. If in doubt, ask the instructor.
</li>
</ul>
In short: don’t steal, and cite your sources, especially if you borrow or are otherwise influenced by ideas, text, or code.
References and citation should be done in APA format.
</p>
<h4> Feedback </h4>
<p>
We welcome feedback on the course at any point. Feel free to email the instructor directly, or leave anonymous feedback by using the anonymous Google form (URL given in the syllabus on LumiNUS).
</p>
<h4> Other courses </h4>
<p>
Interested students can also check out similar courses such as CSCI534 Affective Computing, taught by <a href="https://people.ict.usc.edu/~gratch/">Jonathan Gratch</a> at USC.
</p>
<br><br>
<a name="schedule">
<h3 style="padding-top: 64px; margin-top: -64px;"> Class Project </h3>
</a>
<p>
The class project offers you an opportunity to apply what you have learnt in the class. The final outcome will vary depending on the choice of project, but will involve a substantial amount of research and/or development. Projects can take many forms, such as the incorporation of emotion recognition into a prototype software system or app, a research project implementing the latest techniques in machine learning to affective computing, a critical evaluation of an existing technology offering that might also include a discussion of how a particular technology is implemented and their ethical ramifications.
<br><br>
Students are expected to do a substantial amount of the background reading of the emotion literature in order to inform the project, or do critical research on existing technologies. You must base your project on compelling scientific prior work. Even if you decide to build something completely new that has not been studied before, there must be related work that will inform your proposed project.
<br><br>
The scope is open-ended, and you and your group members will come to a consensus as to a feasible (and mutually agreeable) project. This project will have you apply what you have learnt about the psychological theories of emotion with a keen sense of technology, and will solidify the learning objectives into a final, tangible product to be displayed in a public showcase. Unless students opt-out, final project write-ups (and any associated demos/material) will be made publically available and archived on the course webpage.
<br><br>
More information will be provided in class.
<br><br>
We assume that students (being final-year undergrads in a School of Computing) will be familiar with good coding practices, such as using version control. We expect that students will make all their final project code available via a public GitHub respoitory. Please get familiar with GitHub and version control if you are not already, and consider looking into requesting an education account at <a href="https://education.github.com/">https://education.github.com/</a>, which among other things, allows you to have private repositories (which some students may be more comfortable with for works-in-progress).
<br><br>
If you are using data (and most of the projects will), please bear in mind any restrictions about publically sharing the data. In the majority of cases, I recommend to <b>only commit CODE</b> to GitHub, and <b>not to commit any data</b> (e.g. videos) unless you have obtained the necessary permissions from the data owners or other relevant parties. When in doubt, ask the instructor. (Do not even commit data to a private repository, because you might make it public in the future).
</p>
<h4> Class Project Template </h4>
<p>
We will be following the Affective Computing and Intelligent Interaction (ACII) conference format for the project proposals and final reports. The ACII template can be found <a href="http://acii-conf.org/wp-content/uploads/2019/01/ACII2019_author_kit.zip">here</a>. (If the link is broken, there is a local copy <a href="ACII2019_author_kit.zip">here</a>)
</p>
<h4>List of projects</h4>
<h5>Semester 1, AY2020-2021 Projects</h5>
<i>* Showcased at <a href="https://isteps.comp.nus.edu.sg/event/17th-steps">17th STePS</a> (SoC Term Project Showcase) on 17 Nov 2020.</i>
<ul>
<li>
Sentiment Analysis Dashboard for 2020 US Presidential Election
<ul> <li> <small>Cheng Lin Pak, Choon Kiat Kang, David Choo, Jia Yun Teo [ <a href="https://github.com/k-choonkiat/IS4152-twitter">github</a> ]</small> </li> </ul>
</li>
<li>
Investigating Transfer Learning of Affective Computing Models
<ul> <li> <small>Kong Yan San, Jonathan Soh, Jing Lin, Deng Jingyuan [ <a href="https://github.com/JonathanSohWeiWen/IS4152-Project">github</a> ]</small> </li> </ul>
</li>
<li>
Multi-task BERT for Emotion Recognition from Textual Conversations
<ul> <li> <small>Varsha Suresh [ <!-- <a href="https://github.com/XXX"> -->github<!-- </a> --> ]</small> </li> </ul>
</li>
<li>
Multi-Agent Appraisals for Emergent Emotions in Reinforcement Learning Agents
<ul> <li> <small>Joel Huang, Gnanapoongkothai Annamalai [ <a href="https://github.com/joel-huang/appraisal-rl">github</a> ]</small> </li> </ul>
</li>
<li>
Emotional Speech Synthesis in English Using GST-Tacotron 2
<ul> <li> <small>E-Liang Tan, Natalie Loke, Wei Jie Tan [ <a href="https://github.com/taneliang/gst-tacotron2">github</a> ] [ <a href="https://github.com/taneliang/tacotron2">github2</a> ]</small> </li> </ul>
</li>
</ul>
<br>
</div>
</div>
<div class="row-fluid">
<div class="offset1">
<a name="schedule">
<h3 style="padding-top: 64px; margin-top: -64px;">Schedule</h3>
</a>
<iframe width="1000px" height="800px" style="border: none" src="https://docs.google.com/spreadsheets/d/e/2PACX-1vS9CWUC8sQ-TNuBrGEs93uCrZbgWg8_MR8JLfFv7mjbc4lIs5sBCyfgGYUt6jQwi--XptIYxHwUcSBz/pubhtml?gid=0&single=true&widget=true&headers=false"></iframe>
<br><br><br><br>
</div>
</div>
<div class="row-fluid">
<div class="offset1">
</div>
</div>
</div> <!-- end page container -->
<div class="push"></div>
</div> <!-- end page wrap -->
<script src="js/jquery.js"></script>
<script src="js/bootstrap.min.js"></script>
<script>
$(".nav li").click(function(x) {
$(".nav li").removeClass("active");
$(this).addClass("active");
})
</script>
</body>
</html>