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transcript/allocentric_jgxNs1WBONk.txt

@@ -0,0 +1,66 @@
+[0.000 --> 2.000]  Bella, do's we built a party?
+[2.000 --> 4.000]  No, the mirror is math science.
+[4.000 --> 6.000]  History and rambling, the mystery
+[6.000 --> 9.000]  that all started with a big bang.
+[9.000 --> 10.000]  Hey.
+[10.000 --> 11.000]  Hey.
+[11.000 --> 12.000]  Hey.
+[12.000 --> 13.000]  Everything's smoothed out with Amy.
+[13.000 --> 15.000]  Uh, no, she's still pretty mad.
+[15.000 --> 18.000]  Did you make the apology as sincere as I would have?
+[18.000 --> 21.000]  I said, children, says he's sorry.
+[21.000 --> 23.000]  Well, I have to hang it on a little thick.
+[26.000 --> 29.000]  Hey, it's time you apologize to her yourself.
+[29.000 --> 30.000]  I suppose so.
+[30.000 --> 32.000]  But if I get out of line, I'll lose my spot.
+[32.000 --> 35.000]  I'm happy to hold your place till you get back.
+[45.000 --> 46.000]  Good morning, sir.
+[46.000 --> 48.000]  What can I get started for you today?
+[48.000 --> 50.000]  It's a pleasure, sir.
+[50.000 --> 52.000]  Uh-oh. What's nice?
+[52.000 --> 53.000]  All right.
+[53.000 --> 55.000]  Three empty glasses.
+[55.000 --> 57.000]  Would you care for a pastry?
+[57.000 --> 58.000]  Nope.
+[60.000 --> 61.000]  Uh, mocha.
+[61.000 --> 63.000]  Three mocha lattes.
+[66.000 --> 68.000]  Uh, double chocolate chip muffin.
+[68.000 --> 69.000]  Yup.
+[73.000 --> 74.000]  Ah, ah, ah, ah, ah.
+[74.000 --> 76.000]  You had three palm and cartonies in these.
+[76.000 --> 77.000]  Puzzle.
+[77.000 --> 81.000]  And I love the Beatles' state for my life.
+[81.000 --> 82.000]  Something.
+[82.000 --> 84.000]  Uh.
+[84.000 --> 86.000]  What's that, son?
+[86.000 --> 88.000]  Hey, bring him Lincoln.
+[88.000 --> 89.000]  Uh-huh.
+[89.000 --> 92.000]  Do you know you, me, gone?
+[92.000 --> 93.000]  Shoot.
+[93.000 --> 94.000]  Oh, yeah.
+[94.000 --> 96.000]  Three shots.
+[96.000 --> 98.000]  Uh.
+[126.000 --> 128.000]  Uh.
+[157.000 --> 164.000]  Is that everyone I do want to war?
+[179.000 --> 181.000]  Avengers!
+[187.000 --> 188.000]  No!
+[203.000 --> 205.000]  It's not much.
+[205.000 --> 206.000]  But it's home.
+[206.000 --> 208.000]  I think it's brilliant.
+[210.000 --> 213.000]  Where have you been?
+[214.000 --> 217.000]  Harry, how wonderful to see you, dear.
+[217.000 --> 218.000]  Bed's empty?
+[218.000 --> 219.000]  No note?
+[219.000 --> 220.000]  Car gone?
+[220.000 --> 222.000]  You got a dime.
+[222.000 --> 224.000]  You could have been seen.
+[224.000 --> 227.000]  Of course, I don't blame you, Harry, dear.
+[227.000 --> 229.000]  They were starving, in, mum.
+[229.000 --> 231.000]  They were bars in his window.
+[231.000 --> 235.000]  You best hope I don't put bars on your window, Donald Weasley.
+[235.000 --> 236.000]  Come on, Harry.
+[236.000 --> 238.000]  Time for spotted breakfast.
+[244.000 --> 245.000]  Oh.
+[251.000 --> 252.000]  Lincoln!
+[274.000 --> 275.000]  What?
+[293.000 --> 294.000]  Ah!

transcript/allocentric_mhVsMmcOxQM.txt

@@ -0,0 +1,79 @@
+[0.000 --> 6.720]  Welcome to the presentation of Where Should I Look?
+[6.720 --> 9.640]  Comparing reference frames for spatial tactile cues.
+[9.640 --> 14.560]  My name is Eric Pescara and my co-authors are Anton Stubenwad to be a Svartiger, Ikunt
+[14.560 --> 18.000]  Fang and Michal Beigel.
+[18.000 --> 21.920]  When designing tactile displays on the wrist for special cues, it is important to keep
+[21.920 --> 24.240]  the natural movement of the body and mind.
+[24.240 --> 28.560]  Depending on the movement of the wrist, different reference frames can influence the output
+[28.560 --> 30.040]  of the tactile display.
+[30.040 --> 34.280]  In this paper, we compare it in allocentric reference frame with the wrist centered reference
+[34.280 --> 38.280]  frame in terms of accuracy, reaction time and cognitive load.
+[38.280 --> 41.640]  We conducted a repeated measures user study with 20 participants.
+[41.640 --> 46.520]  We used a tactile wristband with 10 evenly spaced actuators as our tactile display.
+[46.520 --> 51.680]  The data we retrieved from the experiment consisted of 120 spatial localization tasks per
+[51.680 --> 53.800]  participant per reference frame.
+[53.800 --> 57.800]  As a measure of cognitive load, we asked the participants to fill out a raw TLX survey
+[57.800 --> 59.400]  after every condition.
+[59.400 --> 62.600]  A spatial localization task was conducted as follows.
+[62.600 --> 68.560]  First, a combination of wrist rotation and actuator was drawn from a pre-determined list.
+[68.560 --> 73.400]  The participant was then instructed to turn the wrist to match the given wrist rotation.
+[73.400 --> 78.040]  Depending on the reference frame, the corresponding spatial direction was calculated.
+[78.040 --> 82.320]  The selected actuator was then activated for one second.
+[82.320 --> 85.120]  The participant then was asked to input the direction.
+[85.120 --> 89.040]  The input was stored together with the reaction time in the true direction.
+[89.040 --> 94.960]  This process was then repeated until the list of spatial localization tasks was exhausted.
+[94.960 --> 100.000]  In the evaluation, we first looked if localization accuracy was influenced by the reference frame.
+[100.000 --> 103.920]  Both reference frames had a high localization accuracy for the wrist and showed no statistical
+[103.920 --> 105.920]  difference.
+[105.920 --> 111.040]  While the wrist centered reference frame had an accuracy of 84% and an average error of 28.5
+[111.040 --> 115.760]  degrees, the allocentric reference frame was only marginally better with an accuracy
+[115.760 --> 121.040]  of 85% and an average error of 26.8 degrees.
+[121.040 --> 125.960]  When comparing reaction time, we can see a difference between the reference frames.
+[125.960 --> 131.280]  There is a statistically significant difference in reaction time with a small effect size.
+[131.280 --> 136.200]  The allocentric reference frame has a slightly faster reaction time with an average difference
+[136.200 --> 140.040]  of 240 milliseconds.
+[140.040 --> 144.880]  For measuring the effects of the wrist rotation on the participant's reaction time, we performed
+[144.880 --> 151.200]  a linear regression analysis with a wrist rotation as predictor on the reaction time.
+[151.200 --> 155.840]  While there is a clear relation between increasing reaction time and higher wrist rotation for
+[155.840 --> 161.560]  the wrist centered reference frame, the allocentric reference frame is mostly unaffected by the wrist
+[161.560 --> 164.240]  rotation.
+[164.240 --> 168.760]  For measuring the effects of the wrist rotation on the participant's accuracy, we also performed
+[168.760 --> 174.120]  a linear regression analysis with the wrist rotation as predictor of the accuracy.
+[174.120 --> 178.960]  While there is a clear relation between decreasing accuracy and higher wrist rotation for the
+[178.960 --> 183.940]  wrist centered reference frame, the allocentric reference frame is mostly unaffected by the
+[183.940 --> 186.680]  wrist rotation.
+[186.680 --> 191.600]  We looked at the data collected by the RRTLX questionnaires to analyze how the participant's
+[191.600 --> 194.800]  mental demand was affected under both conditions.
+[194.800 --> 199.160]  The RRTLX data was separately evaluated for each dimension.
+[199.160 --> 203.600]  The allocentric reference frame yielded better results in every dimension.
+[203.600 --> 208.960]  There was a statistically significant difference between the reference frames in all dimensions
+[208.960 --> 212.440]  with most dimensions only having a low effect size.
+[212.440 --> 217.840]  However, we found that the mental demand dimension had a large effect size and the performance
+[217.840 --> 222.080]  in effort dimensions had a moderate effect size.
+[222.080 --> 226.800]  The participants also described the wrist centered reference frame as far less intuitive
+[226.800 --> 228.440]  and more demanding.
+[228.440 --> 233.480]  This leads us to conclude that the mental demand of the allocentric reference frame is lower
+[233.480 --> 237.080]  than the wrist centered reference frame.
+[237.080 --> 241.160]  Linear regression was used to measure the learning effect during the experiment for both
+[241.160 --> 245.560]  conditions using trial number as predictor of our reaction time.
+[245.560 --> 250.080]  Most statistically significant evidence was found that the trial number influenced the
+[250.080 --> 253.960]  reaction time for the wrist centered reference frame.
+[253.960 --> 258.520]  We found statistically significant evidence that the trial number influenced the reaction
+[258.520 --> 260.920]  time for the allocentric condition.
+[260.920 --> 265.000]  Our participants improved the reaction time in the allocentric reference frame during
+[265.000 --> 267.320]  the experiment.
+[267.320 --> 272.680]  In conclusion, in the experiment we conducted we found evidence that an allocentric reference
+[272.680 --> 277.200]  frame outperforms a wrist centered reference frame for spatial localization tasks with a
+[277.200 --> 279.800]  wrist-one tactile variable.
+[279.800 --> 284.000]  In our experiment the participants had faster reaction times with the allocentric reference
+[284.000 --> 287.480]  frame and improved during the experiment.
+[287.480 --> 292.000]  We found evidence that the allocentric reference frame was mentally less demanding and more
+[292.000 --> 294.000]  intuitive.
+[294.000 --> 299.240]  And the allocentric reference frame was more robust against postural changes compared to
+[299.240 --> 302.360]  the wrist-centered reference frame.
+[302.360 --> 307.160]  In the future we would like to investigate the influence of different reference frames
+[307.240 --> 313.000]  for spatial localization tasks in the wild with a broad range of activities.
+[313.000 --> 317.680]  We would also like to include more than just wrist rotations in the postural changes.
+[317.680 --> 322.240]  And as there is conflicting evidence in the literature which reference frames perform
+[322.240 --> 329.280]  better in which circumstances we would like to investigate this further.
+[329.280 --> 331.160]  Thank you for your attention and have a great day.

transcript/allocentric_p0A_IRKfG-w.txt

@@ -0,0 +1,20 @@
+[0.000 --> 2.400]  Many people believe you should never say,
+[2.400 --> 4.580]  I don't know, to a question.
+[4.580 --> 6.620]  Let's say at the end of a presentation.
+[6.620 --> 9.740]  Big picture, it's 100% acceptable.
+[9.740 --> 13.180]  If you don't know the answer, don't try to BS them.
+[13.180 --> 15.860]  They will smell blood in the water.
+[15.860 --> 17.980]  What matters is how you say it.
+[17.980 --> 21.320]  I've seen ultra-confident speakers handle this
+[21.320 --> 22.940]  in one of three ways.
+[22.940 --> 24.860]  First, you can say, I don't know,
+[24.860 --> 27.260]  but I'll look into it and get back to you
+[27.260 --> 28.860]  and make sure you follow up.
+[28.920 --> 31.660]  Second, I don't know, but I recommend you ask,
+[31.660 --> 33.180]  John, that's his area.
+[33.180 --> 34.720]  And make sure you refer to somebody
+[34.720 --> 37.580]  who really is the best person to ask.
+[37.580 --> 40.620]  Third, tell them what you do know instead.
+[40.620 --> 44.660]  Say, I don't know about X, but here's what I can tell you.
+[44.660 --> 46.180]  Make sure whatever you say next
+[46.180 --> 48.580]  adds a genuine value to the conversation.

transcript/allocentric_rbItjWcSHbs.txt

@@ -0,0 +1,16 @@
+[0.000 --> 2.000]  Egocentric
+[2.000 --> 4.000]  Adjective
+[4.000 --> 7.000]  Selfish, self-centered
+[7.000 --> 11.000]  Egocentric
+[11.000 --> 13.000]  Adjective
+[13.000 --> 15.000]  Egotistical
+[15.000 --> 19.000]  Egocentric
+[19.000 --> 22.000]  Adjective
+[22.000 --> 28.240]  Relating to spatial representations, linked to a reference frame based on one's own location
+[28.240 --> 32.720]  within the environment, as when giving the direction as right, rather than
+[32.720 --> 38.240]  north, opposed to alo-centric.
+[38.240 --> 40.240]  Egocentric
+[40.240 --> 42.240]  Noun
+[42.240 --> 45.240]  A person who is Egocentric
+[45.240 --> 56.240]  == References ==
+[56.240 --> 58.400]  Please support us with your subscription

transcript/allocentric_tBidCJnzE4g.txt

@@ -0,0 +1,240 @@
+[0.000 --> 7.060]  Hello friends, my name is Jessica and I am an ASHA certified speech and language
+[7.060 --> 12.540]  pathologist and I am obsessed with learning about all things social
+[12.540 --> 17.140]  communication. I am also obsessed with teaching others about them which is why
+[17.140 --> 23.660]  we're here on YouTube. Yay! So today I want to talk to you about non-verbal
+[23.660 --> 30.860]  communication. Nonverbal communication can be really tricky to teach. Most of us
+[30.860 --> 36.900]  have learned these skills naturally so identifying what they are and how to
+[36.900 --> 40.540]  break them down and teach them in a strategic way can actually be quite
+[40.540 --> 45.680]  challenging. So today we are going to talk about some ways that we can teach
+[45.680 --> 53.620]  our students about non-verbal communication and non-verbal language.
+[54.660 --> 59.460]  Now first I'm going to talk to you a little bit about non-verbal
+[59.460 --> 65.740]  communication. There are seven or eight-ish types of non-verbal communication.
+[65.740 --> 78.800]  They are facial expressions, body language, gestures, tone of voice, touch, eye
+[78.800 --> 84.800]  contact and personal space. Okay, you like those gestures? I just made them up on
+[84.800 --> 90.120]  the fly. Alright, so those are the seven areas of nonverbal communication. I
+[90.120 --> 95.320]  said eight because personal hygiene or personal appearance, sorry, can also be
+[95.320 --> 100.560]  considered a type of nonverbal communication. How we are choosing to appear
+[100.560 --> 105.720]  physically does communicate a lot about us. Okay, so let's break this down a
+[105.720 --> 110.200]  minute and now you know the different kinds of nonverbal communication. Let's
+[110.200 --> 116.100]  talk about what nonverbal communication is. It is any kind of communication that
+[116.100 --> 122.680]  occurs without words. It is not verbal, right? See how that works? So like I said,
+[122.680 --> 127.840]  it includes the following areas, facial expressions, body language, gestures, tone
+[127.840 --> 133.000]  of voice, touch, eye contact, personal space and physical appearance if you
+[133.000 --> 139.800]  want to click that. It is very common for individuals to struggle with nonverbal
+[139.800 --> 145.000]  communication. If your child has been diagnosed with autism, that means or your
+[145.000 --> 149.600]  student, that means that they have some trouble understanding and using nonverbal
+[149.600 --> 155.080]  communication. So the skill is extremely important to teach and learn because
+[155.080 --> 160.800]  learning how to understand nonverbal communication helps us to interact
+[160.800 --> 166.840]  socially with others and it helps us to communicate better with others. Okay, so
+[166.840 --> 173.760]  now we're going to break down each of the seven or eight sections of nonverbal
+[173.760 --> 176.720]  communication. We're going to break them down. We're going to talk about them.
+[176.720 --> 180.680]  We're going to define them and I'm going to give you some ideas on how you can
+[180.680 --> 185.440]  teach your student to understand each of these different kinds of nonverbal
+[185.440 --> 189.920]  communication. So the first one we're going to talk about is facial expressions. I
+[189.920 --> 193.720]  am looking off my computer if you keep seeing my eyes start away. I just full
+[193.720 --> 199.000]  disclosure. I need my notes because I want this to be good and helpful for you and
+[199.000 --> 206.360]  I can't do that if I'm doing this all my memory. So I hope you understand. Also,
+[206.360 --> 211.080]  before we dive in and I go any further, thank you for being here. Thank you for
+[211.080 --> 215.400]  taking the time to learn something new that will hopefully help you teach your
+[215.400 --> 220.640]  students a skill that they're struggling with. That is just absolutely awesome
+[220.640 --> 224.520]  and amazing and I thank you for choosing to spend your time with me. So before I
+[224.520 --> 227.880]  go any further, if you've not already gotten something to take notes with, I
+[227.880 --> 233.240]  would really recommend getting some pen and some paper and jotting down some
+[233.240 --> 236.480]  things to help you remember what we're talking about. Okay, so let's jump in.
+[236.480 --> 240.920]  The first type of nonverbal communication we're going to talk about is facial
+[240.920 --> 252.000]  expressions. Right? There are six main facial expressions that people make. Now,
+[252.000 --> 260.360]  each facial expression is related to an emotion. Each type of facial expression
+[260.360 --> 266.280]  has a very specific characteristics that will help you know what emotion the
+[266.280 --> 271.680]  person is feeling. Okay, so let's think about this. We're going to break it down a
+[271.680 --> 278.600]  little bit more. There are six types of facial expressions. Happy, sad, angry,
+[278.600 --> 285.440]  fear, disgust, and surprised. Scientists tell us that these are the basic
+[285.440 --> 294.000]  emotions that we all experience. Every other emotion is a root or a different
+[294.000 --> 300.960]  form of these basic emotions. So our facial expressions, we can say we're happy.
+[300.960 --> 315.360]  Sad, angry, scared, disgusted. We're surprised. Okay, each of these six basic
+[315.360 --> 321.960]  emotions have very distinct characteristics of the face. Okay, so going back
+[321.960 --> 330.040]  through them. When you feel happy, you have a wide smile and open now. You can
+[330.040 --> 335.880]  see that some teeth. You can see wrinkles around the eyes and the cheeks are
+[335.880 --> 343.840]  raised and the eyes are slightly squinted. Did you see all this in my face?
+[343.840 --> 349.680]  Can you see them? Can you see my wrinkles? My high-raised cheeks? My teeth? My smile?
+[349.680 --> 357.480]  I'm happy. I'm happy to be here. So that is happy. Second facial expression that
+[357.480 --> 364.400]  we can see is sad. Okay, the corners of the lips pointed down.
+[364.400 --> 375.680]  Inner eyebrows are raised up. My eyebrows apparently don't move like that. But you
+[375.680 --> 383.400]  know it's a face when you see one. Okay, next. Angry. There's tension in the face.
+[383.400 --> 390.480]  There's these closed, V-shaped eyebrows. The mouth, if the mouth is open, it's
+[390.480 --> 396.120]  square shaped. Square shaped, if you can understand that. If the mouth is closed,
+[396.120 --> 403.200]  there's tightness in the chin and jaws. Do you see all those characteristics?
+[403.440 --> 415.440]  Alright, fear. Slanted and raised eyebrows. Eyes are open very wide. Just saw a bug
+[415.440 --> 420.660]  crawl across my table. I don't know. Right? You know what fear looks like.
+[420.660 --> 428.360]  Disgust. A wrinkled nose. Lowered eyebrows. The mouth is tight and curved downward in the upper
+[428.360 --> 436.520]  lips go up. Big one across my table. I bug really didn't go across my table just
+[436.520 --> 442.760]  now. I'm just using that as an example. And last is surprised. Raised and curved
+[442.760 --> 450.120]  eyebrows. Horizontal wrinkles on the forehead. Open lips. Dropped jaw. Eyes open wide.
+[450.840 --> 458.440]  You see my wrinkles? Horizontal? Eyes. Mouth. I have a surprised face. So like I said,
+[459.400 --> 466.280]  I start by teaching my students these physical characteristics to look for when trying to
+[466.280 --> 475.080]  interpret a facial expression. Now an interesting tip is students with autism. We know that they struggle
+[475.160 --> 481.080]  with eye contact. So part of the reason that they struggle with understanding emotions is because
+[481.080 --> 488.040]  they are focusing on this lower third of the face. So a lot of these cues, like we talked about,
+[488.040 --> 494.760]  the horizontal wrinkles. This wrinkles around my eyes. Those are occurring in the top third of my face.
+[494.760 --> 501.400]  So a child or individual who does not focus on this top third is missing a lot of cues that's
+[501.400 --> 508.520]  going to help them learn to read and understand facial expressions. So to teach facial expressions,
+[508.520 --> 515.400]  to teach my students how to understand them, we again, I go over each of those definitions,
+[515.400 --> 522.520]  model them like I did for you. And they try and draw them so that they're having, you know,
+[522.520 --> 527.640]  an interactive process. And then we'll probably look at maybe some video clips or some pictures
+[527.640 --> 535.160]  or things to talk about those basic facial expressions. Again, really focus on this top third of
+[535.160 --> 540.840]  the face because we're getting a lot of cues there that if a child is not looking at somebody's
+[540.840 --> 545.960]  eyes or their top third of the face, they're going to miss those cues. Now we know there are more
+[545.960 --> 554.040]  emotions beyond happy, sad, mad, disgust, surprised, and angry. But we talk about these different
+[554.040 --> 560.680]  more complex emotions and how the same facial expressions are generally going to be used to convey
+[560.680 --> 567.800]  those complex emotions. So what we will do is we will, I'll give them a list of say, of some words.
+[567.800 --> 579.640]  For example, nervous, satisfied, amused, annoyed, love, revulsion. We're going to target, first of
+[579.640 --> 585.080]  all, some really good vocabulary words. But we're going to talk about what basic emotion,
+[585.080 --> 591.560]  these complex emotions are the most like. And then talk about kind of how the face is going to
+[592.280 --> 600.280]  model those similar facial expressions for the complex emotions as they do the basic emotions.
+[601.160 --> 608.120]  All right, gestures. Gestures are movements that we make with our bodies that are used to
+[608.120 --> 614.840]  communicate a message. We most frequently use our hands to gesture, but other parts of the bodies
+[614.840 --> 622.920]  can be used as well. Now, there are three types of gestures. Gestures that indicate nervousness,
+[622.920 --> 627.640]  such as fidgeting with objects, or my personal is playing with my hair.
+[629.640 --> 634.520]  Gestures with a specific meaning, such as a thumbs up, we know that means good job, it has a
+[634.520 --> 640.200]  meaning, and gestures that go with a verbal message, such as me, using my hands as I'm talking
+[640.200 --> 647.320]  and telling you a story. So when I'm teaching these, I focus mostly on teaching gestures with a
+[647.320 --> 654.920]  specific meaning. Think of these like gestures as a vocabulary word. We will talk about different
+[654.920 --> 660.600]  kinds of gestures, and then we will define it. For example, we will talk about the beckoning gesture,
+[661.320 --> 666.680]  and we will talk about what it means. It means come here. We will talk about the talking gesture.
+[669.000 --> 674.200]  What does that mean? She is talking and she needs to be quiet and tired of it, or we will talk about
+[674.200 --> 681.160]  a thump, or we will talk about the hitchhiking thumb. How that is different than a thumbs up.
+[682.600 --> 687.880]  Gestures like vocabulary words, we teach gestures, and I teach their meanings so that my students
+[687.880 --> 692.680]  are able to see someone using a gesture and define it like they would a vocabulary word.
+[694.840 --> 699.800]  In my non-verbal communication teaching guide, I have a whole list of different gestures
+[701.480 --> 707.000]  that you can use to know some gestures to teach. You can also find lists on the internet
+[707.000 --> 713.640]  if you're wanting to kind of DIY it yourself. All right, move and write along to touch. I believe that was
+[713.640 --> 721.400]  my gesture I used in the beginning. Touching someone is when you physically touch another person.
+[722.360 --> 729.160]  There are four different kinds of touching. There's actually five, but one of them is inappropriate,
+[729.160 --> 737.720]  so we're not going to talk about it here. There are four different kinds of touch. Functional,
+[737.720 --> 746.680]  professional, social polite, friendship, warmth, and love intimacy. Okay, let's talk about what
+[746.680 --> 753.720]  each of these are. A functional professional touch is the touching that occurs when a professional
+[753.720 --> 759.400]  must touch you to do his or her job. For example, the dentist has to touch your mouth. The hair lady
+[759.400 --> 766.360]  has to touch my hair. It's professional. I'm expecting her to touch me and she's doing it to do her job.
+[767.320 --> 774.520]  Second one is social polite, and this is touching that occurs in social routines. They're usually very
+[774.520 --> 783.880]  brief and they, let's see, sorry, I lost my spot. And they include things like a handshake, a pat on
+[783.880 --> 788.680]  the back, or a quick side hug. They're not going to last very long. We're just being polite. I'm
+[788.680 --> 794.120]  going to shake your hand and then we're done touching. Number three is friendship or warmth,
+[794.120 --> 797.960]  and this is touching that occurs between two people who are familiar with one another.
+[799.800 --> 805.880]  Now, when you teach this, or you know, you need to be very careful because this type of touch can
+[805.880 --> 811.880]  easily be confused with the next type, which is love intimacy. So you need to make sure that your
+[811.880 --> 817.880]  level of touch in this stage matches your partner so that you don't make that other person uncomfortable,
+[817.880 --> 823.160]  or you need to teach your student to make sure their level of touch matches their partners so they
+[823.160 --> 830.120]  don't make somebody uncomfortable. So friendship, warmth touching includes things like longer hugs,
+[830.120 --> 836.280]  putting your arms around the shoulders of somebody, or you know, holding hands. Well, holding
+[836.280 --> 842.040]  hands can also be in love intimacy. So if you're a good friend, you might give them a longer hug,
+[842.040 --> 848.120]  but if I hug you it's too long. Now I'm thinking, well, are we friends? Or is this like you being
+[848.120 --> 856.600]  intimate with me? So it's kind of that in between a social polite and intimacy. So the fourth one
+[856.600 --> 864.280]  is love intimacy, and this occurs between two people who are very close. This includes family,
+[864.280 --> 872.280]  very close friends, and significant others. You need to teach your students to be very careful to
+[872.280 --> 877.880]  use these touches with the appropriate people. Holding hands and touching someone's hair and
+[877.880 --> 884.040]  cuddling are all examples of love intimacy touching. So to teach this kind of nonverbal communication
+[884.040 --> 891.480]  touch, we just make a graph, and we talk about different, you know, I label, I make four different
+[891.480 --> 896.840]  squares. One is functional professional, one's social polite, friendship warmth and love intimacy,
+[896.840 --> 902.200]  and we make a list of the people who I would expect a functional professional touch with,
+[902.200 --> 908.360]  who I could expect a love intimacy touch with, who would be a good person to use friendship warmth
+[908.360 --> 913.640]  touch with, who should I use a social polite touch with. So we just sort people that we know into
+[913.640 --> 921.800]  the different categories of appropriate ways to touch them. Okay, next nonverbal communication
+[921.800 --> 932.440]  is proximics, aka personal space. So if somebody is too close to you, they're in your personal space,
+[932.440 --> 939.400]  and that's a type of nonverbal communication. Now, there are different kinds. There is a
+[942.440 --> 950.600]  scientific formula for what is appropriate as far as proximate goes. So proximics commonly called
+[950.600 --> 957.640]  personal space is the distance between you and another person. There are four levels intimate space,
+[959.160 --> 965.240]  personal space, social space, and public space. So we'll start from the middle and we'll work our
+[965.240 --> 974.040]  way out. Intimate space is anything that goes from touching your body to about 18 inches from
+[974.040 --> 980.040]  yourself. This is the space where you allow people with whom you are very close. So this could be
+[980.040 --> 985.880]  very close family members, very close friends, and significant others are probably the only people
+[985.880 --> 993.880]  you will allow in this space. Personal space is about 18 inches to four feet from your body. We will
+[993.880 --> 1001.160]  often allow friends and people we like in this space. Moving out again, we have social space. This
+[1001.160 --> 1007.160]  is four to ten feet from your body. This space is for people we don't know well, or for people with
+[1007.160 --> 1014.440]  whom we have no close relationship. Then last, the biggest ring is public space, which is what it
+[1014.440 --> 1020.360]  sounds like. Anything beyond ten feet from your body, where the rest of the public is, it contains
+[1020.360 --> 1026.200]  strangers and people who are not comfortable with. So this is important because it lets us know how
+[1026.200 --> 1032.200]  close it's appropriate to be to other people. And like I said, if somebody gets too close to me,
+[1032.200 --> 1037.080]  that makes me really uncomfortable if you're not one of my intimate people. At the same time,
+[1037.640 --> 1043.000]  if you're way out here in public space, but I think we're buds, that feels a little off to me too.
+[1043.000 --> 1049.480]  So to teach this, while I teach my students about these definitions, and then I like to get like
+[1049.480 --> 1056.840]  masking tape, and we measure this out on the ground to give an idea of what these spaces look like
+[1056.840 --> 1063.720]  visually. And then we'll do kind of that same activity that we did before, where we'll get the
+[1063.720 --> 1069.960]  four squares. And we will say, who are some people that I would allow in my intimate space?
+[1070.600 --> 1075.320]  Who are some people I would allow in my personal space? Who are people that might be in my social
+[1075.320 --> 1080.120]  space? And who are some people who would be in my public space? And we just think about
+[1081.720 --> 1087.080]  our space and our personal space and how we're sharing it and where people should be within that space.
+[1087.240 --> 1096.280]  Okay, the next type of nonverbal communication is whole body language. Our body language is the
+[1096.280 --> 1102.360]  way we position our head and our body to send a message to the people around us. When we tilt our
+[1102.360 --> 1107.400]  head to the side, it means I'm interested in what you're saying to me. If we lower our head, it
+[1107.400 --> 1112.360]  means we're probably unhappy. If our head stays upright, it means we're happy and we're in a good
+[1112.360 --> 1119.160]  mood or we're in a neutral mood that is neither happy nor unhappy. If we lean our body towards someone,
+[1119.160 --> 1123.720]  it means we're interested in what they have to say. And if we pull our body away from them,
+[1123.720 --> 1127.000]  it means we're not comfortable speaking to that person or that maybe we don't like them.
+[1127.880 --> 1134.440]  If you sit with an open posture like I am now, then it comes across as very welcoming and friendly.
+[1135.080 --> 1141.400]  If you close yourself up and you sit in the closed posture, then that is closed off. It's not as
+[1141.400 --> 1148.680]  welcoming and it doesn't look as friendly. So body language is also usually used with gestures
+[1148.680 --> 1154.280]  and facial expressions and tone of voice, all kind of combined together to give you a clue
+[1154.280 --> 1161.320]  as to what the other person is thinking. So to teach this skill, I will use video clips or maybe
+[1161.320 --> 1169.960]  look at pictures from a book and I will not do the audio if I can. Like if it's some of the
+[1169.960 --> 1174.360]  Disney shorts are really good for not having audio and you can just look at the body language.
+[1176.680 --> 1180.440]  But we'll look at the picture or the video clip and we'll describe the body language of the
+[1180.440 --> 1185.400]  person that's in it. And then we'll talk about what do we think that body language is communicating.
+[1186.600 --> 1188.040]  And we'll do that three or four times.
+[1190.760 --> 1197.720]  Okay, the next type of nonverbal communication is vocalix, which we commonly refer to as tone of voice.
+[1199.960 --> 1208.280]  This is how we use our voice, not our words, but our voice to convey a message. So think of the tone
+[1208.280 --> 1214.280]  of voice as the background to your words. Your tone of voice is going to change a lot based on
+[1214.280 --> 1219.080]  different situations. For example, you would use a different tone of voice at a football game
+[1219.080 --> 1224.520]  than you would in a nice restaurant. Your voice might also sound different in different context
+[1224.520 --> 1229.560]  when your emotions are changing. For example, your voice sounds different when you're nervous
+[1229.560 --> 1235.720]  versus in a situation where you're comfortable. And it's important to consider the context of each
+[1235.720 --> 1244.440]  situation when trying to understand the meaning of someone's voice. Vocal expression is also usually
+[1244.440 --> 1250.760]  tied to facial expressions. They go hand in hand. So this means if somebody's face looks sad,
+[1250.760 --> 1257.320]  their voice probably sounds sad too. So what I tell my students is if they have a hard time
+[1257.320 --> 1262.040]  understanding the tone of voice to also pay attention to the facial expressions and the body
+[1262.040 --> 1270.600]  language, to give them clues as to how the other person is feeling. Okay, so to teach vocalix or tone
+[1270.600 --> 1277.880]  of voice, what I will do is I will give my students a context and a facial expression and words.
+[1277.880 --> 1285.000]  And then they will practice using different tones of voice to say that word. So for example,
+[1285.880 --> 1290.600]  the context could be your brother or sister borrowed your shirt and gave it back with a stain on it.
+[1290.600 --> 1295.000]  The facial expression would be angry and the words would be thank you. Thank you.
+[1297.000 --> 1301.480]  Same words, thank you. This time your mom gave you broccoli for dinner. You hate broccoli.
+[1302.920 --> 1309.560]  Thank you. Same words again. Thank you. Your dad surprised you with a new phone. Thank you.
+[1309.800 --> 1316.120]  Thank you again. Someone hands you a tissue after you've been crying. Thank you.
+[1316.920 --> 1323.240]  So this talks about how different situations and different scenarios are going to sound different
+[1323.240 --> 1327.960]  with different tone of voice even though the words might be exactly this. Okay, now I would be
+[1327.960 --> 1333.320]  remiss to not talk about eye contact when we're talking about types of nonverbal communication.
+[1333.560 --> 1339.640]  Okay, understanding eye contact will help our students become better nonverbal communicators.
+[1340.520 --> 1345.400]  Remember how I talked about most of our students with autism focus on the lower two thirds of the
+[1345.400 --> 1353.080]  face. A lot is going on in these upper and this upper third. So teaching them why eye contact
+[1353.080 --> 1358.520]  is important or at least why looking at this upper area is important is going to help them become
+[1358.600 --> 1364.440]  a better nonverbal communicator. It also helps with connection and helps us to connect with others
+[1364.440 --> 1369.640]  and feel closer and it helps others feel closer to us. So I explain all of those things when I'm talking
+[1369.640 --> 1376.200]  about eye contact. The last one that we talked about is physical appearance. I again just kind of
+[1376.200 --> 1381.560]  briefly touch on this. I explain what physical appearance is and how you know sometimes some
+[1381.560 --> 1386.840]  things in your physical appearance you can change and some things you can't. So we talk about how you
+[1387.080 --> 1394.760]  know when you change your hair color or well okay some things like your height and your weight
+[1394.760 --> 1399.640]  and your natural hair color are things you cannot change. But you can change things like how you
+[1399.640 --> 1404.440]  dress and the accessories, how you groom yourself if you wash your hair if you cut your nails
+[1405.000 --> 1409.720]  that affects what people think about you. So if I come in and my hair is clean and my nails are
+[1409.720 --> 1415.640]  done people are going to think I'm a clean person. If I come in and I haven't washed my hair in a
+[1415.720 --> 1421.720]  week and my nails are long and dirty that's going to affect how people think of me. Also how you
+[1421.720 --> 1427.640]  know we pick our clothes based on the type of image we want to portray. I you know I'm trying to
+[1427.640 --> 1433.000]  choose something professional looking as I'm talking to you and I'm not wearing my workout clothes
+[1433.000 --> 1437.640]  that I usually wear all day long because I want you to think of me as a professional and somebody
+[1437.640 --> 1443.000]  who knows what I'm talking about. So physical appearance is a type of nonverbal communication.
+[1443.000 --> 1449.320]  So I hope you learned some new things about nonverbal communication. I hope you have a better
+[1449.320 --> 1454.840]  understanding about what it is, what makes up nonverbal communication. I hope you got some ideas
+[1454.840 --> 1459.160]  on things you can use to teach your kids how to be better nonverbal communicators.
+[1461.160 --> 1468.840]  Now I know that this was a lot of information and I have created a resource, a teaching guide
+[1469.320 --> 1476.040]  that I would love for you to have that walks you through teaching these different types of nonverbal
+[1476.040 --> 1481.880]  communication. I literally was reading off of it today as I was going over it with you so you
+[1481.880 --> 1488.920]  know what is in it and it's going to give you some words to help you teach. It's going to give you
+[1488.920 --> 1495.160]  some visuals. It's going to give you a strategy and a place to start and it's going to help you
+[1495.160 --> 1501.160]  teach these skills in a really strategic way. So if you're interested in purchasing this for me,
+[1501.160 --> 1507.960]  there is a link in the description below. Additionally, I have a whole bundle of teaching guides
+[1507.960 --> 1514.040]  that teach social communication skills. This is included in it and all of my teaching guides are
+[1514.040 --> 1519.000]  included in it. So it helps you, it's full of guides that help you teach things like taking
+[1519.000 --> 1524.360]  someone's perspective, code switching, power relationships, conversation skills, friendship
+[1524.360 --> 1531.320]  making skills. I have teaching guides to help you teach these skills to your students.
+[1531.320 --> 1538.520]  So there's a link for that in the description below as well. Thank you again, thank you for taking
+[1538.520 --> 1542.760]  your time to spend with me. Thank you for taking the time to learn something new. I hope you found
+[1542.760 --> 1547.880]  it helpful. If you'd like to keep getting videos like this or knowing when some new ones come out,
+[1547.880 --> 1552.920]  click subscribe and be a part of our community. Thanks!

transcript/allocentric_uxBeSEughAc.txt

@@ -0,0 +1,54 @@
+[0.000 --> 1.700]  I don't want you to have to.
+[1.700 --> 4.700]  You don't want to have to.
+[4.700 --> 5.700]  You don't want to have to.
+[5.700 --> 8.380]  I find the Ariana much more fragrance than the Raffialla.
+[8.380 --> 10.180]  Ariana, oh!
+[10.180 --> 12.020]  I'll keep that in mind.
+[12.020 --> 12.780]  How you doing?
+[12.780 --> 14.300]  Fine.
+[14.300 --> 17.420]  I never got a chance to thank you for holding the camp bus.
+[17.420 --> 18.320]  Oh, please, please.
+[18.320 --> 20.700]  Anytime you need a bus, I am your guy.
+[20.700 --> 22.460]  And I noticed Aaron's teeth are looking good.
+[22.460 --> 23.700]  Thanks to you.
+[23.700 --> 26.500]  I just hope she's remembering to wear her night retainer.
+[26.500 --> 27.600]  Well, you know how kids are.
+[27.600 --> 28.420]  I can't.
+[28.420 --> 30.620]  Oh, please, the minute my Kevin gets off that bus,
+[30.620 --> 32.260]  it's goodbye by play.
+[32.260 --> 33.340]  Is that for you?
+[33.340 --> 34.900]  Oh, yes.
+[34.900 --> 36.780]  When Deadrun and I got divorced, I decided
+[36.780 --> 38.340]  that I had to learn how to cook.
+[38.340 --> 38.860]  Huh.
+[38.860 --> 40.860]  The walkie world of Thai cooking.
+[40.860 --> 42.500]  I'm branching out.
+[42.500 --> 44.780]  No matter the fact, I'm taking a Thai cooking course
+[44.780 --> 45.580]  this summer.
+[45.580 --> 46.660]  Really?
+[46.660 --> 48.820]  I've always been interested in Asian cooking.
+[48.820 --> 49.660]  Really?
+[49.660 --> 50.420]  Mm-hmm.
+[50.420 --> 51.260]  Well, why don't you join me?
+[54.260 --> 57.220]  When I think about it, over the years,
+[57.220 --> 59.900]  there were less and less moments in the course of the day
+[59.900 --> 63.620]  when Ben and I actually made real eye contact.
+[63.620 --> 69.980]  If you are not going to share what he's almost asleep.
+[69.980 --> 72.340]  Maybe it was the stuff of life.
+[72.340 --> 74.660]  Who's going to take Aaron to school?
+[74.660 --> 78.180]  Who's turn is it to pick up Josh from his clarinet lessons?
+[78.180 --> 80.660]  But after a while, there was a disturbing comfort
+[80.660 --> 82.620]  and not really having to deal with each other.
+[82.620 --> 85.660]  Because somehow, you just get used to the disconnection.
+[87.340 --> 89.660]  And even at night, when we could finally come together,
+[89.660 --> 91.420]  we wound up facing forward.
+[91.420 --> 94.540]  Yeah, we were tired, but I think we were afraid
+[94.540 --> 98.140]  that if we faced each other, there'd be nothing there.
+[98.140 --> 100.420]  We're learning me-crab next week.
+[100.420 --> 103.140]  Me-crab?
+[103.140 --> 104.460]  I'll let you know.
+[104.460 --> 105.980]  OK.
+[105.980 --> 108.460]  Oh, no.
+[108.460 --> 109.380]  I'll call you.
+[109.380 --> 110.260]  Oh, you call me.
+[110.260 --> 111.260]  OK.

transcript/allocentric_wW7Z52plM0s.txt

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+[0.000 --> 12.000]  Nonverbal communication differences occur between cultures because of how different people around the world interpret actions in social interaction.
+[12.000 --> 23.000]  Understanding the cultural differences in nonverbal communication is important for those with a goal to work in international business.
+[23.000 --> 34.000]  Types of nonverbal communication vary based on culture and country, but the areas of differences tend to fall within the following eight areas.
+[34.000 --> 47.000]  Each provides an area where people doing business in other parts of the world should understand the nonverbal communication differences between cultures and how to prepare for them.
+[48.000 --> 60.000]  I contact. I contact signals confidence in the West, what can be seen as rude or challenging in parts of Asia and the Middle East.
+[60.000 --> 76.000]  Also, there are gender rules in I contact around many Eastern cultures discouraging women to make I contact with men as a conveys authority or a sexual interest.
+[78.000 --> 93.000]  Touch touch often is used frequently in communication even in a business setting with customs such as a handshake, but other cultures consider touching other people inappropriate.
+[93.000 --> 105.000]  Those who live in Asia tend to take a more conservative approach when it comes to touching with a bow typically replacing a handshake.
+[105.000 --> 111.000]  Another example of differences with touching is a patting someone in the head.
+[111.000 --> 124.000]  In the US, it is seen as endearing and shows affection with children, but in some Asian cultures touching children or adults in the head is disrespectful.
+[124.000 --> 135.000]  The US is more conservative in other areas such as not kissing on the cheek as they do in many other parts of Europe.
+[135.000 --> 145.000]  Gestures. Many business people who work internationally discipline themselves to keep hand gestures to a minimum.
+[145.000 --> 156.000]  For example, pointing at someone else is an insult in most parts of the world, but in some places it is often simply used as a reference.
+[156.000 --> 165.000]  Organizations stick out their tongue to greet people, but that doesn't fly in other parts of the world.
+[165.000 --> 174.000]  The most common gesture in the world is a nod, but even that can mean different things in other cultures.
+[174.000 --> 177.000]  Physical distance.
+[178.000 --> 188.000]  The rule of thumb here, no matter where you are in the world, is to give people more space than you think they might need.
+[188.000 --> 191.000]  Only get close if invited.
+[191.000 --> 196.000]  People in different cultures abuse physical distance differently.
+[197.000 --> 203.000]  However, it's best never to enter anyone's personal space about two feet.
+[203.000 --> 212.000]  If it's not personal intimacy, many people find such proximity and comfortable.
+[212.000 --> 215.000]  Facial expressions.
+[215.000 --> 222.000]  The good news is that facial expressions for happiness, sadness, anger and fear are universal.
+[222.000 --> 229.000]  The bad news is that not every culture is okay with using them in a business setting.
+[229.000 --> 239.000]  The Japanese, for example, try to remain a neutral facial expression, believing that showing your emotions burdens the other person.
+[239.000 --> 242.000]  Appearance.
+[242.000 --> 246.000]  Conservative attire is the safest bet.
+[246.000 --> 259.000]  For some places in the United States are fine with very relaxed appearances, while others even see an exposed shoulder or leg asked a cause for offense.
+[259.000 --> 264.000]  The best choice is to simply dress conservatively.
+[264.000 --> 271.000]  You can also loosen up your wardrobe if it becomes apparent that it is acceptable.
+[272.000 --> 274.000]  Posture.
+[274.000 --> 278.000]  Again, the traditional route is the best route.
+[278.000 --> 283.000]  Don't slouch when sitting or sit with legs crossed.
+[283.000 --> 291.000]  Face people as they speak to you and not enough to show that you are paying attention to what they say.
+[291.000 --> 296.000]  Stay mindful of where you sit in meetings.
+[296.000 --> 304.000]  In some cultures there is a strict hierarchy for who gets to sit where.
+[304.000 --> 307.000]  Parallel language.
+[307.000 --> 314.000]  Parallel language refers to communication that is avocalized but not words.
+[314.000 --> 321.000]  This includes the tone of voice, loudness, speed of speech and inflection.
+[321.000 --> 328.000]  Parallel language is the key to understand the context or meaning of the words used.
+[328.000 --> 341.000]  It's important to be mindful of these issues and to understand they are not discernible in emails and texts, so great care must be used in the words you choose.
+[341.000 --> 345.000]  High context versus low context.
+[345.000 --> 356.000]  Another way to help with understanding the cultural difference in nonverbal communication is understanding the difference between high context and low context cultures.
+[356.000 --> 363.000]  High context cultures rely more on nonverbal communication than low context cultures.
+[363.000 --> 371.000]  They use personal relationships, social hierarchies and cultural knowledge to convey meaning.
+[371.000 --> 384.000]  In low context cultures words are more important. Communication is direct. Relationships begin and end quickly and hierarchies are relaxed.
+[384.000 --> 395.000]  For those who aspire to work in an international business, understanding these nonverbal communication differences between cultures is the key to success.

transcript/allocentric_xPiRQ1G241k.txt

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+[0.000 --> 6.240]  My name is Ryan Peters. I'm a post-doctoral researcher working with Chen New at the University of Texas at Austin,
+[6.240 --> 12.240]  and today I'm presenting our paper titled, Are You With Me, Modeling Joint Attention from Child Egocentric Vision.
+[12.240 --> 18.440]  Human cognition is, in many ways, a cooperative social process.
+[18.440 --> 26.840]  And one of the key mechanisms that enables such social cognition is when we coordinate and share our attention to an object or task.
+[27.240 --> 33.080]  A huge body of work shows that such shared or joint attention is crucial for early development.
+[33.080 --> 36.720]  It's important for early language learning and other kinds of cultural transmission.
+[36.720 --> 41.560]  It predicts developmental outcomes, including language, cognitive and self-regulation abilities.
+[41.560 --> 48.760]  And because of these things, it's become a widely used diagnostic marker and target for clinical interventions.
+[48.760 --> 54.760]  From the beginning, gaze following has been seen as a kind of holy grail of joint attention.
+[54.760 --> 62.520]  Indeed, in Skype and Bruner's pioneering work, joint attention was equivalent to and operationalized as gaze following.
+[62.520 --> 70.520]  Because of that, much of the subsequent work has been designed to elicit and measure how well infants follow a social partner's gaze.
+[70.520 --> 79.160]  In nearly all this work, looking at the social partner's face has been interpreted as the primary behavioral pathway to check a partner's attentional state.
+[79.160 --> 87.560]  And therefore, face looks are deemed as a kind of indicator of awareness of being in joint attention with a social partner.
+[87.560 --> 97.800]  However, several recent studies have shown that infants rarely look at their parents' faces during naturalistic parent child activities such as toyplay or meal preparation.
+[97.800 --> 107.400]  Since infants aren't looking at their parents' faces in these studies, they instead define joint attention simply as looking at the same object at the same time.
+[107.480 --> 119.800]  Crucially, these studies still find predictive relations between patterns of joint attention and vocabulary development, suggesting that awareness may not be a necessary component of joint attention.
+[119.800 --> 128.200]  However, this implication assumes that face looks are the only pathway to achieve awareness of joint attention.
+[128.200 --> 135.800]  Here, we challenge that assumption and ask whether children can achieve awareness of joint attention without looking at their parents' face.
+[135.880 --> 142.760]  Building on recent work showing that attending to held objects plays a critical role in establishing and maintaining joint attention.
+[142.760 --> 147.240]  We hypothesize that hand eye coordination may provide an alternate pathway,
+[147.240 --> 149.640]  degaining awareness of joint attention.
+[149.640 --> 153.640]  To explore this hypothesis, we use classification approach that combines
+[153.640 --> 157.000]  head mounted eye tracking and computational modeling.
+[157.000 --> 162.840]  First, we brought parent child diets to play the set of 24 toys in a naturalistic environment.
+[162.920 --> 168.600]  Then, using the eye trackers, we collected their egocentric views and gaze data, as you see here.
+[168.600 --> 176.840]  Next, using that gaze data, we categorize the child egocentric views as belonging to a moment of joint attention or not.
+[176.840 --> 179.800]  Here are some of the child egocentric views from the dataset.
+[179.800 --> 183.320]  Half of these are from moments of joint attention and half are not.
+[183.320 --> 189.960]  Determining which is which based solely on features in a single egocentric view appears to be a non-trivial task.
+[189.960 --> 193.160]  But this is precisely what we set up to train our models to do.
+[194.520 --> 203.720]  To do so, we fed the child egocentric videos into CNN, models, and provided the ground truth classifications to train them to classify the images.
+[203.720 --> 206.440]  We then tested the models using held out data.
+[207.960 --> 211.640]  Moving on to the first set of results, we first addressed the question,
+[211.640 --> 217.640]  do children's egocentric views contain in-the-moment signals allowing for awareness of joint attention?
+[218.200 --> 223.400]  To test this, we explore whether models can classify images as joint attention or not,
+[223.400 --> 224.680]  better than chance.
+[224.680 --> 229.240]  And one sample, two tailored teetests can vary in model level, subject level,
+[229.240 --> 233.640]  and item level mean-balanced accuracy against chance confirms our hypothesis.
+[235.720 --> 239.400]  To better understand our model's performance, we also look at the ROC curve,
+[239.400 --> 244.280]  which characterizes overall model performance by plotting inverse specificity,
+[244.280 --> 249.640]  or how all the models can detect moments that are not joint attention along the x-axis,
+[249.640 --> 255.880]  against sensitivity, or how all the models can detect moments that are joint attention along the y-axis.
+[255.880 --> 262.280]  And this is done for the full range of threshold values used to binarize the confidence scores output by the models.
+[262.280 --> 267.400]  Confidence scores range from 0 to 1, and this black point in the center here
+[267.400 --> 272.200]  marks the threshold of 0.5, which we used to generate our results.
+[272.200 --> 276.680]  So at this point, frames with confidence scores above 0.5 or classwise,
+[276.680 --> 281.880]  joint tension in those with confidence scores below 0.5 or classwise as not joint attention.
+[281.880 --> 287.160]  The bottom left-hand corner marks the threshold of 1 for which every frame would be categorized as not
+[287.160 --> 291.640]  joint attention, while the top right-hand corner marks the threshold of 0 for which every frame would
+[291.640 --> 293.400]  be categorized as joint attention.
+[293.400 --> 299.480]  Finally, this dashed line along the diagonal shows performance for a random classifier.
+[299.480 --> 304.840]  So the fact that our curve lies above the diagonal confirms our models perform better than
+[304.840 --> 310.840]  chance across the full range of threshold values. The area under the curve, or the RLC AUC,
+[310.840 --> 316.680]  puts a number to the indicating there's a 67% probability that our models will produce a higher
+[316.680 --> 322.200]  confidence score for a randomly chosen joint attention frame than a randomly chosen frame from a moment
+[322.200 --> 327.880]  that is not turned attention. To explore the role of object holding, we also classify each frame as
+[327.880 --> 333.560]  belonging to different visible holding categories based on a combination of manually coded child and
+[333.560 --> 339.160]  parent object holding using the third person videos and automated object detections to determine
+[339.160 --> 345.720]  the visibility of objects in a child's egocentric use. Using these, we can compare how the model classwise
+[345.720 --> 350.680]  frames are which neither the child nor parent were holding a visible object versus frames in which
+[350.680 --> 356.440]  only the child, only the parent or both the child and parent were jointly holding the same visible object.
+[357.160 --> 362.920]  These last three holding categories all require there is only a single held visible object,
+[362.920 --> 367.560]  allowing for a clean line of reasoning as to why such views might support detection of joint
+[367.560 --> 372.120]  attention. However, that is not always the case. There are frames in which the child or parent are
+[372.120 --> 375.640]  holding two visible objects to frames in which the child and parent are each holding different
+[375.640 --> 381.000]  visible objects. So we created a separate category for frames with such conflicting holding cues.
+[381.880 --> 386.120]  Moving on to the results here, we address the question, does object holding provide in the moment
+[386.120 --> 392.680]  signals useful for detecting joint attention and our hypotheses are that models will leverage signals
+[392.680 --> 399.800]  tied to visible holding to detect moments of joint attention and signals tied to the lack of visible
+[399.800 --> 405.640]  object holding to detect moments that are not joint attention. Focusing on the first hypothesis,
+[405.640 --> 410.920]  we again look at sensitivity or how are the models detecting joint attention moments for each
+[411.000 --> 416.200]  of the visible holding categories, neither only child, only parent, both, and conflicting along the
+[416.200 --> 423.240]  xxc's here. And pairwise comparisons across the five categories reveal that models show greater
+[423.240 --> 428.360]  sensitivity for frames with visible held objects, and in particular, those in which both child and
+[428.360 --> 436.040]  parent are jointly holding an object, confirming our hypothesis. Next, focusing on the second hypothesis,
+[436.040 --> 440.520]  we again look at specificity or how well the models do at detecting moments that are not
+[440.520 --> 445.160]  joint attention for each of the holding categories, and here pairwise comparisons across the categories
+[445.160 --> 450.360]  reveal that models show greatest specificity for moments in which neither child, nor parent,
+[450.360 --> 456.520]  are holding a visible object, again, confirming our hypothesis. Finally, we can look at the RLC curves
+[456.520 --> 460.760]  for each of the holding categories, providing overall estimates of how well the models do for
+[460.760 --> 465.640]  each of the categories. And again, the point showed the values associated with the threshold at 0.5
+[465.720 --> 471.160]  used to generate our results. And as you can see, the models do better than chance for all the
+[471.160 --> 478.360]  holding categories, but they're most accurate for frames in which both child and parent are jointly
+[478.360 --> 487.640]  holding a visible audit and struggle with frames containing conflicting holding cues. So we see
+[487.640 --> 493.080]  that models are indeed able to classify joint attention better than chance, and they leverage
+[493.160 --> 499.080]  visible object holding to do this. Taken together, we think this confirms our overarching hypothesis that
+[499.080 --> 504.600]  children might be able to achieve awareness of their parent's attentional state by leveraging
+[504.600 --> 510.520]  in the moment visual signals tied to object holding. However, one major difference between our models
+[510.520 --> 515.560]  and children is that our models had a training signal. We told them what frames were and were not
+[515.560 --> 521.960]  joint attention, but what could be the training signal for children? In study 2, we address this question.
+[522.760 --> 528.920]  Based on study 1, we know that visual signals tied to object holding can be used to detect moments
+[528.920 --> 535.560]  of joint attention. Next, we wondered what if children simply assume they are in joint attention
+[535.560 --> 541.240]  when they look at an object held by themselves or their parents? In other words, what if children can
+[541.240 --> 547.000]  leverage their own attentional state in conjunction with object holding as a training signal to learn
+[547.240 --> 553.160]  to detect moments of joint attention? To explore this hypothesis, we trained three different models with
+[553.160 --> 558.200]  joint attention defined using a combination of object holding and child attention. One model was
+[558.200 --> 562.840]  trained using a dataset consisting of frames in which only the child was holding a visible object,
+[562.840 --> 567.400]  and for which frames in which the child was attending to the held object were defined as joint
+[567.400 --> 572.760]  attention and frames in which the child was not attending to the held object were defined as not
+[573.000 --> 577.800]  attention. A second model was similarly trained using only parent frames and a third model
+[577.800 --> 584.120]  was trained using either only child or only parent frames. After training, we then tested the models
+[584.120 --> 589.240]  on ground truth joint attention, exactly as was done for the models in study 1.
+[590.920 --> 594.840]  Moving on to the results, since we're asking whether models can learn to detect joint attention,
+[594.840 --> 600.280]  our primary hypothesis is that models will show greater than chance sensitivity for the trained
+[600.360 --> 606.600]  categories. However, we also wondered whether the models might be able to generalize what they
+[606.600 --> 612.280]  learned to other object holding categories and maybe even show similar patterns of sensitivity
+[612.280 --> 618.200]  across holding categories to models trained on ground truth joint attention. So here are the
+[618.200 --> 623.160]  results for each of the models and we see that all three show greater than chance sensitivity
+[623.240 --> 630.280]  for the trained categories marked in blue, red, green respectively, confirming our first hypothesis.
+[631.240 --> 636.520]  Next looking at how the models generalize to cross holding categories and how those distributions
+[636.520 --> 641.800]  compare with what we saw in study 1 in upper left hand corner here, we see that all three models
+[641.800 --> 647.240]  show striking similarities with the models from study 1. In particular, all models show greatest
+[647.240 --> 652.680]  sensitivity for frames in which both parent and child are jointly holding a visible object.
+[653.160 --> 657.800]  And lowest or nearly lowest sensitivity for frames in which neither parent nor child are holding
+[657.800 --> 663.640]  an object, confirming our second hypothesis. It's worth noting that the model trained on frames with
+[663.640 --> 668.600]  either child or parent holding shows the greatest similarity highlighting the importance of having
+[668.600 --> 675.800]  access to both types of keys. To conclude, our results broadly show that children might be able to
+[675.800 --> 681.880]  achieve awareness of joint attention by leveraging in the moment visual signals tied to object holding,
+[681.880 --> 687.080]  and children can theoretically generate their own training signal and learn to detect moments of
+[687.080 --> 691.800]  joint attention simply by assuming they're enjoyed attention when they look at an object held by
+[691.800 --> 696.360]  themselves or their parents. In other words, face looks are not the only way to gain awareness of
+[696.360 --> 703.080]  joint attention in real time in social situations. There are complementary social signals encoded in
+[703.080 --> 708.840]  bodily behaviors such as attending to objects held by oneself or a social partner. All together,
+[708.840 --> 713.480]  I think this work is a good case study demonstrating how things that we study at the social level
+[713.480 --> 719.640]  can be grounded and embedded in the sensory motor level. In other words, social and sensory motor levels
+[719.640 --> 726.040]  provide complementary rather than competing explanations. Here are my references. And to conclude,
+[726.040 --> 736.040]  I want to thank everyone at UT Austin and Indiana University who made this work.

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