1 00:00:00,160 --> 00:00:02,440 Speaker 1: Guess what mango? What's that? Will? So I was looking 2 00:00:02,440 --> 00:00:04,480 Speaker 1: back at some stories that i'd booked Mark from this 3 00:00:04,559 --> 00:00:07,160 Speaker 1: year and there was this one, this really good one 4 00:00:07,200 --> 00:00:09,520 Speaker 1: about a bagpiper, and I felt like I needed to 5 00:00:09,520 --> 00:00:12,200 Speaker 1: share it with you. This already sounds awful, I know, 6 00:00:12,280 --> 00:00:14,280 Speaker 1: but all right. So this is from Glasgow and it's 7 00:00:14,680 --> 00:00:17,040 Speaker 1: late in the night and people are on a commuter train. 8 00:00:17,079 --> 00:00:18,880 Speaker 1: They're trying to get home from the pub or the 9 00:00:18,960 --> 00:00:22,119 Speaker 1: office or wherever, and this guy just steps onto the 10 00:00:22,120 --> 00:00:25,639 Speaker 1: car and starts wailing away on his bagpipes. Can you 11 00:00:25,640 --> 00:00:27,480 Speaker 1: imagine this? I mean they sound like one thing from 12 00:00:27,480 --> 00:00:30,280 Speaker 1: a distance, but up close. So he's been a partying 13 00:00:30,320 --> 00:00:33,160 Speaker 1: mood and he genuinely wants to keep the party going, 14 00:00:33,479 --> 00:00:36,640 Speaker 1: but you know, using his bagpipes. So he starts playing 15 00:00:36,640 --> 00:00:41,640 Speaker 1: a rousing rendition of Yellow Submarine. I mean, I guess 16 00:00:41,720 --> 00:00:44,960 Speaker 1: that's sort of upbeat. But does everyone get into it? No, 17 00:00:45,240 --> 00:00:48,400 Speaker 1: just the opposite. So the chorus comes around and you 18 00:00:48,440 --> 00:00:50,800 Speaker 1: think people are going to start breaking out singing, and 19 00:00:50,800 --> 00:00:54,480 Speaker 1: then everyone just keeps staring at him in total anchor. 20 00:00:55,160 --> 00:00:58,560 Speaker 1: It's pretty amazing, and the comments were brutal. One person 21 00:00:58,600 --> 00:01:01,120 Speaker 1: said he'd rather opt for water boarding, then hear that 22 00:01:01,240 --> 00:01:04,399 Speaker 1: noise again. But you know, remembering this Piper's tale made 23 00:01:04,400 --> 00:01:07,400 Speaker 1: me wonder, what are some of the most unusual sounds 24 00:01:07,400 --> 00:01:10,440 Speaker 1: in history? What did the Big Bang sound like? Or 25 00:01:10,440 --> 00:01:14,560 Speaker 1: taranno sources roar and what are some sounds worth blocking out? 26 00:01:14,920 --> 00:01:17,400 Speaker 1: And that's what today's episode is all about. Let's dive 27 00:01:17,440 --> 00:01:41,200 Speaker 1: in Heither podcast listeners, Welcome to Part Time Genius. I'm 28 00:01:41,200 --> 00:01:43,080 Speaker 1: Will Pearson and as always I'm joined by my good 29 00:01:43,080 --> 00:01:45,400 Speaker 1: friend man Guesh Ticketer and on the other side of 30 00:01:45,440 --> 00:01:48,400 Speaker 1: the soundproof glass singing the hit song from The Bodyguard, 31 00:01:48,640 --> 00:01:51,960 Speaker 1: a friend and producer Tristan McNeil. I really wish you 32 00:01:51,960 --> 00:01:54,360 Speaker 1: could hear it because Tristan sings like an angel, and 33 00:01:54,400 --> 00:01:56,480 Speaker 1: you know, every time I hear that song, I will 34 00:01:56,520 --> 00:01:59,640 Speaker 1: Always love You You tear up right no. But every 35 00:01:59,640 --> 00:02:01,320 Speaker 1: time I heard I think about the fact that Saddam 36 00:02:01,400 --> 00:02:04,000 Speaker 1: Hussein used it as his campaign song, like it's just 37 00:02:04,120 --> 00:02:05,880 Speaker 1: so ridiculous to me. I know, that's one of my 38 00:02:05,920 --> 00:02:08,240 Speaker 1: favorite facts of all time. So I did look it 39 00:02:08,320 --> 00:02:10,880 Speaker 1: up again recently because I wanted to see the ads again, 40 00:02:11,320 --> 00:02:14,200 Speaker 1: and the song he used was actually an Arabic cover 41 00:02:14,360 --> 00:02:17,040 Speaker 1: by a pop star from Syria, so still still the 42 00:02:17,040 --> 00:02:21,560 Speaker 1: same emotional impact, but slightly different. Well, I've already gotten 43 00:02:21,560 --> 00:02:24,320 Speaker 1: his off track, or I guess Tristan's gotten his off track. 44 00:02:24,639 --> 00:02:26,960 Speaker 1: But uh, well, I I know where episodes all over 45 00:02:27,000 --> 00:02:29,799 Speaker 1: the place. So today we're covering some of the strangest, loudest, 46 00:02:29,840 --> 00:02:32,040 Speaker 1: and most irritating sounds in history. Where do you want 47 00:02:32,080 --> 00:02:33,639 Speaker 1: to start? I think we should go back to the beginning. 48 00:02:33,720 --> 00:02:36,480 Speaker 1: So I think we should start with the actual earliest 49 00:02:36,520 --> 00:02:39,239 Speaker 1: sound in the universe. What do you think? Yeah, I 50 00:02:39,280 --> 00:02:43,000 Speaker 1: mean it sounds a little theoretical or theological, I guess. 51 00:02:43,080 --> 00:02:45,840 Speaker 1: And you know, in Hinduism there's that sound of home 52 00:02:45,880 --> 00:02:48,320 Speaker 1: that's supposed to be like the beginning, middle, and end 53 00:02:48,360 --> 00:02:52,000 Speaker 1: of time. Sound like I mean you heard in yoga 54 00:02:52,040 --> 00:02:55,080 Speaker 1: classes too. But in Christianity, I'm guessing it's like when 55 00:02:55,240 --> 00:02:57,840 Speaker 1: God flipped the light switch? Is that right? Well, before 56 00:02:57,880 --> 00:02:59,600 Speaker 1: there was light, I think there was actually the sound 57 00:02:59,680 --> 00:03:02,320 Speaker 1: of a slashing if I remember correctly, you know, since 58 00:03:02,360 --> 00:03:05,720 Speaker 1: there's water and earth referenced than that darkness. But I 59 00:03:05,760 --> 00:03:08,440 Speaker 1: was actually taking more of a scientific slant here. I 60 00:03:08,480 --> 00:03:11,080 Speaker 1: was talking about the earliest sounds in the universe, as in, 61 00:03:11,560 --> 00:03:13,919 Speaker 1: you know, the big Bang. Yeah, that makes more sense. 62 00:03:14,080 --> 00:03:17,320 Speaker 1: Although the word big bang already seems descriptive, right, I'm 63 00:03:17,360 --> 00:03:20,040 Speaker 1: guessing it just sounds like a massive crash. Well that's 64 00:03:20,040 --> 00:03:22,040 Speaker 1: what I thought too, and I think most people would assume. 65 00:03:22,040 --> 00:03:25,000 Speaker 1: But the truth is actually weirder than that. So there's 66 00:03:25,000 --> 00:03:27,400 Speaker 1: a physicist from the University of Washington. His name is 67 00:03:27,480 --> 00:03:30,200 Speaker 1: John Kramer, and back in two thousand one, he wrote 68 00:03:30,240 --> 00:03:32,880 Speaker 1: this article that described the sound of the Big Bang. 69 00:03:33,600 --> 00:03:35,440 Speaker 1: You know, the physics here is above my pay grade, 70 00:03:35,440 --> 00:03:38,640 Speaker 1: but according to the Atlantic article quote, during the first 71 00:03:38,760 --> 00:03:42,040 Speaker 1: one hundred to seven hundred thousand years after the Big Bang, 72 00:03:42,440 --> 00:03:45,240 Speaker 1: the universe was far denser than the air on Earth, 73 00:03:45,600 --> 00:03:48,360 Speaker 1: which means that the sound waves could actually move through it. 74 00:03:49,000 --> 00:03:51,320 Speaker 1: So he published this piece about how the universe kept 75 00:03:51,360 --> 00:03:54,840 Speaker 1: ringing in the slow, low frequency way until the universe 76 00:03:54,960 --> 00:03:58,480 Speaker 1: grew to you know, these massive proportions and it stopped 77 00:03:58,560 --> 00:04:01,040 Speaker 1: making the hump, and the sound would have been too 78 00:04:01,080 --> 00:04:03,560 Speaker 1: low frequency for human years to pick up on. But 79 00:04:03,880 --> 00:04:05,920 Speaker 1: then a couple of years later, this was in two 80 00:04:05,920 --> 00:04:08,720 Speaker 1: thousand three, I think, a mom who was helping her 81 00:04:08,720 --> 00:04:11,200 Speaker 1: eleven year old with a fifth grade project asked if 82 00:04:11,200 --> 00:04:14,720 Speaker 1: there's a recording of it. Anywhere, and when Kramer responded no, 83 00:04:15,160 --> 00:04:17,920 Speaker 1: he then decided to synthesize it for them. I mean, 84 00:04:18,120 --> 00:04:20,360 Speaker 1: that's awesome that we know what the Big Bang sounds 85 00:04:20,400 --> 00:04:23,880 Speaker 1: like because of a fifth grader. And it's also crazy 86 00:04:23,920 --> 00:04:26,920 Speaker 1: to me that the universe is what like fourteen billion 87 00:04:27,000 --> 00:04:29,919 Speaker 1: years old and we have indications of what it actually 88 00:04:30,000 --> 00:04:32,840 Speaker 1: sounded like from the start. I mean, that's insane. But 89 00:04:33,520 --> 00:04:35,479 Speaker 1: what's it actually sound like? Well, so, like you, I 90 00:04:35,520 --> 00:04:39,080 Speaker 1: assumed the Big Bang was gonna sound terrifically big or powerful, 91 00:04:39,240 --> 00:04:42,119 Speaker 1: but as our friend Lucas Riley puts it, it sounds 92 00:04:42,160 --> 00:04:46,280 Speaker 1: a little bit more like a motorcycle fart. I vote 93 00:04:46,279 --> 00:04:49,120 Speaker 1: don't know what that means. And also it seems gross. 94 00:04:49,839 --> 00:04:52,279 Speaker 1: But wouldn't it sound like do you? Well? Kramer has 95 00:04:52,320 --> 00:04:54,240 Speaker 1: a few versions up on his site and they're worth 96 00:04:54,320 --> 00:04:56,640 Speaker 1: checking out, and they ranged from twenty seconds to even 97 00:04:56,680 --> 00:05:00,359 Speaker 1: eight minutes long, and they're all pretty similar. So to me, 98 00:05:00,400 --> 00:05:03,960 Speaker 1: it sounded somewhere between like a video game character dying 99 00:05:04,240 --> 00:05:07,479 Speaker 1: or like an old school computer powering down or something 100 00:05:07,560 --> 00:05:09,479 Speaker 1: like that. If I don't know if that makes any sense, 101 00:05:09,640 --> 00:05:13,280 Speaker 1: or or just maybe we'll go with motorcycle fire. All 102 00:05:13,279 --> 00:05:15,720 Speaker 1: these noises I don't know what they mean, but you 103 00:05:15,760 --> 00:05:18,160 Speaker 1: do have a link to the sound, right, So I mean, 104 00:05:18,240 --> 00:05:20,719 Speaker 1: I think we should put a link of it to Facebook, 105 00:05:20,760 --> 00:05:22,840 Speaker 1: and then we can ask listeners to describe it, and 106 00:05:23,120 --> 00:05:26,159 Speaker 1: we'll send teachers to like the funniest three descriptions. Sound 107 00:05:26,160 --> 00:05:29,000 Speaker 1: good to you, sounds good to me. But now I'm curious, 108 00:05:29,120 --> 00:05:31,880 Speaker 1: how did Kramer make this sound for human years? Like 109 00:05:32,279 --> 00:05:34,160 Speaker 1: I think he said it was too low frequency for 110 00:05:34,240 --> 00:05:35,960 Speaker 1: us to actually be able to hear. Well, that's a 111 00:05:35,960 --> 00:05:38,240 Speaker 1: good question. So from the way I understand it, he 112 00:05:38,320 --> 00:05:41,080 Speaker 1: used data from satellites and and pulled something called a 113 00:05:41,120 --> 00:05:45,520 Speaker 1: cosmic microwave background. The site futurity dot org refers to 114 00:05:45,560 --> 00:05:49,000 Speaker 1: it as a fossilized fingerprint of the Big Bang, and 115 00:05:49,000 --> 00:05:51,480 Speaker 1: then he made some calculations and pulled the data into 116 00:05:51,520 --> 00:05:54,160 Speaker 1: a sound file. But you know, to create something we 117 00:05:54,240 --> 00:05:57,360 Speaker 1: could hear, Kramer had to boost a frequency a hundred 118 00:05:57,480 --> 00:06:01,000 Speaker 1: septillion times. You know how big that is. That's one 119 00:06:01,120 --> 00:06:04,800 Speaker 1: followed by twenty nine zero. And so when he played 120 00:06:04,839 --> 00:06:06,839 Speaker 1: it in his office for the first time, his sheep 121 00:06:06,880 --> 00:06:09,520 Speaker 1: dogs ran in and started how like they were not 122 00:06:09,839 --> 00:06:14,719 Speaker 1: fans of this. Maybe their creationists. I love that, but 123 00:06:15,440 --> 00:06:17,200 Speaker 1: it reminds me of when I started playing the violin 124 00:06:17,240 --> 00:06:20,720 Speaker 1: in third grade and I was so awful, but when 125 00:06:20,720 --> 00:06:23,000 Speaker 1: I screeched and played, my puff would just run and 126 00:06:23,040 --> 00:06:25,800 Speaker 1: face me. And that's just howl along. And I think 127 00:06:25,800 --> 00:06:28,040 Speaker 1: both my family and my dog were so relieved when 128 00:06:28,080 --> 00:06:31,960 Speaker 1: I finally quit. About it sounds familiar, but I love 129 00:06:32,040 --> 00:06:34,800 Speaker 1: this idea of cataloging sounds. And we've got the Big 130 00:06:34,800 --> 00:06:38,039 Speaker 1: Bang on file now, which is awesome. And there's actually 131 00:06:38,040 --> 00:06:40,040 Speaker 1: a guy who's gone around New Jersey catalog and all 132 00:06:40,080 --> 00:06:43,080 Speaker 1: the sounds of New Jersey for future generations. This just 133 00:06:43,120 --> 00:06:46,359 Speaker 1: sounds like a joke. That's true. Yeah, it's real. His 134 00:06:46,440 --> 00:06:49,480 Speaker 1: name's are Bernie wagon Blast. That's just a joke, right, 135 00:06:50,040 --> 00:06:54,159 Speaker 1: that's also true, Okay, But he's visiting every county trying 136 00:06:54,160 --> 00:06:57,120 Speaker 1: to capture something that feels rare about each place. So 137 00:06:57,240 --> 00:07:00,520 Speaker 1: he'll like tape the rumble of the King dakr roller coasters. 138 00:07:00,560 --> 00:07:04,280 Speaker 1: It's going up for the sound inside this old covered bridge, 139 00:07:04,600 --> 00:07:06,839 Speaker 1: or even like the music of ice skates cutting and 140 00:07:06,880 --> 00:07:09,920 Speaker 1: gliding across the ice and an old historic rink. Yeah, 141 00:07:10,000 --> 00:07:12,840 Speaker 1: it's really beautiful and poetic, and it's like a sound 142 00:07:12,880 --> 00:07:16,200 Speaker 1: library of New Jersey. But there's this even more ambitious 143 00:07:16,200 --> 00:07:17,840 Speaker 1: project I want to talk about, and it's called The 144 00:07:17,880 --> 00:07:21,600 Speaker 1: Sonic Wonders of the World. It's from this British acoustic 145 00:07:21,640 --> 00:07:24,880 Speaker 1: engineer named Trevor Cox, and it's kind of like these 146 00:07:24,920 --> 00:07:28,360 Speaker 1: beautiful sonic destinations that are worth visiting. It sounds like 147 00:07:28,360 --> 00:07:29,800 Speaker 1: a lot of fun. So so what all is on 148 00:07:29,800 --> 00:07:31,920 Speaker 1: the list? Well, one of the first things I saw 149 00:07:32,080 --> 00:07:35,320 Speaker 1: was the singing sands in California in the Mojave Desert. So, 150 00:07:35,400 --> 00:07:38,040 Speaker 1: according to CNN, when you slide down the sand on 151 00:07:38,080 --> 00:07:42,280 Speaker 1: your backside, the unusual sand makes a quote deep parping 152 00:07:42,400 --> 00:07:48,640 Speaker 1: sound resembling propeller aircraft or a susophone accident. Yeah, Cox 153 00:07:48,640 --> 00:07:50,760 Speaker 1: calls it more of a weird droning. So does this 154 00:07:50,800 --> 00:07:52,600 Speaker 1: have to do with like the shape of the sand 155 00:07:52,760 --> 00:07:55,040 Speaker 1: or the size of the sand? Yeah, that's right, So 156 00:07:55,240 --> 00:07:56,720 Speaker 1: it has to do both with the shape of the 157 00:07:56,800 --> 00:07:59,520 Speaker 1: dune and the size of the sand grains. Apparently that's 158 00:07:59,520 --> 00:08:01,840 Speaker 1: pretty cool, all right. So what else does he talk about? Well, 159 00:08:01,960 --> 00:08:05,440 Speaker 1: some of his men made sounds like there's some acoustic wonders. 160 00:08:05,480 --> 00:08:09,120 Speaker 1: There's this chirping Mayan pyramid where when you clap your 161 00:08:09,120 --> 00:08:11,720 Speaker 1: hands it echoes back with the sound of the sacred 162 00:08:11,800 --> 00:08:14,720 Speaker 1: Mayan bird. It's pretty awesome and it was used for 163 00:08:14,760 --> 00:08:18,200 Speaker 1: religious ceremonies. But there's also a place in Carnatica, India 164 00:08:18,240 --> 00:08:20,680 Speaker 1: where I've actually been. It's called gold Gum Buzz, and 165 00:08:21,200 --> 00:08:24,680 Speaker 1: uh there's this massive whispering gallery. You can speak into 166 00:08:24,720 --> 00:08:26,840 Speaker 1: a column on one side and hear the message on 167 00:08:26,880 --> 00:08:29,960 Speaker 1: the other side, and if you speak in a different part, 168 00:08:30,120 --> 00:08:32,800 Speaker 1: the dome kind of echoes the sounds over and over. 169 00:08:33,240 --> 00:08:35,040 Speaker 1: And the way it was described in the article was 170 00:08:35,320 --> 00:08:37,800 Speaker 1: it's almost like a nineteen sixties horror flick where they're 171 00:08:37,800 --> 00:08:41,160 Speaker 1: all these like layered, sampled sounds just echoing over each other. 172 00:08:41,720 --> 00:08:45,520 Speaker 1: But it's actually way less terrifying and more like, uh, 173 00:08:45,679 --> 00:08:47,559 Speaker 1: I don't know, like the open swim at your YMC. 174 00:08:48,400 --> 00:08:51,480 Speaker 1: That's a little different. Yeah, But my favorite thing he 175 00:08:51,480 --> 00:08:54,040 Speaker 1: talks about is the musical road in California, which has 176 00:08:54,120 --> 00:08:57,480 Speaker 1: the William Tell and Lone Ranger song like grooved into 177 00:08:57,520 --> 00:09:00,960 Speaker 1: the pavement, and as Cox and Cena put it, it 178 00:09:01,080 --> 00:09:03,920 Speaker 1: is a very bad rendition of the William Tell overture, 179 00:09:04,520 --> 00:09:07,400 Speaker 1: like someone gargling with water in an adjacent room. But 180 00:09:07,480 --> 00:09:09,640 Speaker 1: it does make you laugh. Wow, I mean, I do 181 00:09:09,800 --> 00:09:12,800 Speaker 1: love the musical highways and runways. I know we covered 182 00:09:12,800 --> 00:09:14,840 Speaker 1: in a previous episode the one at Disney. You know 183 00:09:14,840 --> 00:09:17,079 Speaker 1: where they they when the when the plane goes over 184 00:09:17,120 --> 00:09:18,839 Speaker 1: to you hear when you wish upon a star. I 185 00:09:18,920 --> 00:09:21,640 Speaker 1: guess it says they land, I think. But now that 186 00:09:21,640 --> 00:09:24,040 Speaker 1: we've covered one sound no one has heard and a 187 00:09:24,120 --> 00:09:26,880 Speaker 1: bunch of sounds you travel to hear, I think we 188 00:09:26,920 --> 00:09:30,680 Speaker 1: should probably cover some terrible sounds that nobody wants to hear. 189 00:09:31,559 --> 00:09:33,800 Speaker 1: So I'm a little hesitant about what that means, but 190 00:09:33,880 --> 00:09:36,800 Speaker 1: I'll go with it. But let's pause for a quick break. First, 191 00:09:50,480 --> 00:09:52,680 Speaker 1: welcome back to Part time Genius. So before the break, 192 00:09:52,760 --> 00:09:55,800 Speaker 1: you were teasing that we get into some awful sounds. Well, 193 00:09:55,880 --> 00:09:58,280 Speaker 1: I found this list from two thousand seven and it's 194 00:09:58,320 --> 00:10:02,280 Speaker 1: of the worst sounds in the world. Okay, so two 195 00:10:02,320 --> 00:10:05,360 Speaker 1: thousand seven. I'm gonna put myself back in the mindset 196 00:10:05,360 --> 00:10:08,240 Speaker 1: of when Ratatoui was in theaters and that show Chuck 197 00:10:08,360 --> 00:10:11,800 Speaker 1: was on the air. Chuck, I'm not sure you have 198 00:10:11,840 --> 00:10:14,280 Speaker 1: to think that deeply about it. But so this is 199 00:10:14,320 --> 00:10:16,880 Speaker 1: a British list, So most of the sounds are pretty 200 00:10:16,960 --> 00:10:19,280 Speaker 1: similar as the ones that we might think of here 201 00:10:19,320 --> 00:10:22,080 Speaker 1: and there are things like feedback from a microphone or 202 00:10:22,120 --> 00:10:25,120 Speaker 1: crying babies. And I guess maybe they knew about your 203 00:10:25,200 --> 00:10:28,280 Speaker 1: violin playing you were talking about, because poorly played violin 204 00:10:28,400 --> 00:10:31,240 Speaker 1: is actually number six on the list here. But what 205 00:10:31,280 --> 00:10:34,880 Speaker 1: about something like nails on a chalkboard. Honestly, just saying 206 00:10:34,880 --> 00:10:37,200 Speaker 1: that phrase gives me the shivers. It makes me uncomfortable. 207 00:10:37,320 --> 00:10:39,679 Speaker 1: You know. Surprisingly that wasn't on there. I mean, I 208 00:10:39,720 --> 00:10:42,320 Speaker 1: guess the closest thing to that they have here. Let's 209 00:10:42,360 --> 00:10:45,480 Speaker 1: see the train scraping on the track. So that's on there. 210 00:10:45,480 --> 00:10:47,520 Speaker 1: But there are a few on here that I actually 211 00:10:47,520 --> 00:10:50,280 Speaker 1: didn't see, now, okay, or this feels a little bit 212 00:10:50,280 --> 00:10:52,280 Speaker 1: like British family few. But I'm still gonna make you 213 00:10:52,360 --> 00:10:54,800 Speaker 1: take a guess. So what are some of the other 214 00:10:54,920 --> 00:10:59,239 Speaker 1: top ten worst sounds in the world in England specifically? 215 00:10:59,320 --> 00:11:03,320 Speaker 1: I think anyway, Um, I don't know. I have to 216 00:11:03,320 --> 00:11:05,640 Speaker 1: say throwing up is probably top of the list. Nicely 217 00:11:05,800 --> 00:11:09,520 Speaker 1: done survey says that's actually number one. Didn't expecting to 218 00:11:09,600 --> 00:11:12,240 Speaker 1: nail that, so, I mean, vomiting is definitely a sound 219 00:11:12,280 --> 00:11:14,920 Speaker 1: people would love to block out. But there are others 220 00:11:14,920 --> 00:11:18,640 Speaker 1: on here that are pretty hilarious. So Squeaky Seesaw comes 221 00:11:18,640 --> 00:11:21,520 Speaker 1: in at number five, and I think that's that annoying 222 00:11:21,520 --> 00:11:25,320 Speaker 1: of the noise right above violin. It's on there. Whoopee 223 00:11:25,320 --> 00:11:27,679 Speaker 1: cushion comes in at number seven. I don't know what 224 00:11:27,720 --> 00:11:30,520 Speaker 1: makes people think about these things. Number eight is an 225 00:11:30,600 --> 00:11:35,199 Speaker 1: argument from a soap opera, is so specific it is. Well. 226 00:11:35,240 --> 00:11:37,240 Speaker 1: The funniest thing on the list, though, is number ten, 227 00:11:37,800 --> 00:11:42,480 Speaker 1: Tasmanian devil. I mean that makes no sense. How did 228 00:11:42,480 --> 00:11:44,360 Speaker 1: that many people in England even know what a Tasmanian 229 00:11:44,360 --> 00:11:47,600 Speaker 1: devil sounds like? All right, well, here's the strange thing though, 230 00:11:47,600 --> 00:11:49,280 Speaker 1: I mean, I had no idea you were going to 231 00:11:49,360 --> 00:11:51,679 Speaker 1: bring up Trevor Cox earlier. He's the guy that's been 232 00:11:51,679 --> 00:11:55,160 Speaker 1: collecting sounds from around the world, but oddly enough he's 233 00:11:55,240 --> 00:11:59,280 Speaker 1: also responsible for this survey. Basically, he and some colleagues 234 00:11:59,320 --> 00:12:02,600 Speaker 1: took thirty or repellent sounds and they played them for 235 00:12:02,640 --> 00:12:04,840 Speaker 1: a group of men and women. And part of the 236 00:12:04,840 --> 00:12:06,760 Speaker 1: reason he did this is that Cox has been trying 237 00:12:06,800 --> 00:12:10,680 Speaker 1: to figure out what drives such strong emotions and reactions, 238 00:12:10,720 --> 00:12:13,560 Speaker 1: you know, the various sounds, and also the engineers are 239 00:12:13,559 --> 00:12:15,160 Speaker 1: trying to find out if there are ways to re 240 00:12:15,320 --> 00:12:18,440 Speaker 1: engineer these sounds to be less offensive, I guess, So 241 00:12:18,720 --> 00:12:20,760 Speaker 1: do they find out anything interesting? Well, there were some 242 00:12:20,840 --> 00:12:23,560 Speaker 1: differences in gender. You know, women, for instance, tended to 243 00:12:23,559 --> 00:12:26,120 Speaker 1: find a baby's crying a little less jarring than men. 244 00:12:26,280 --> 00:12:28,440 Speaker 1: But I think what's interesting is how some of the 245 00:12:28,480 --> 00:12:31,160 Speaker 1: things you think would annoy people were far lower on 246 00:12:31,200 --> 00:12:34,280 Speaker 1: the list. Alan kats and things like snoring were far 247 00:12:34,360 --> 00:12:38,160 Speaker 1: less annoying to most people than Tasmanian Devil's snoring ranked 248 00:12:38,240 --> 00:12:41,160 Speaker 1: number twenty six on the list. That's such an annoying sound. 249 00:12:41,960 --> 00:12:44,199 Speaker 1: I mean, you'd obviously take snoring over the sound of 250 00:12:44,240 --> 00:12:48,480 Speaker 1: someone vomiting. But this idea of re engineering sounds is 251 00:12:48,480 --> 00:12:51,760 Speaker 1: pretty interesting. So what does that mean exactly? Well, I 252 00:12:51,760 --> 00:12:54,520 Speaker 1: don't know what Cox is thinking about exactly, but actually 253 00:12:54,559 --> 00:12:58,240 Speaker 1: there is this ignoble study about nails and chalkboards. So 254 00:12:58,240 --> 00:13:01,480 Speaker 1: these scientists isolated the high pitch frequencies as well as 255 00:13:01,520 --> 00:13:04,280 Speaker 1: the middle and low frequencies, and then they tried to 256 00:13:04,320 --> 00:13:07,520 Speaker 1: figure out what made people cringe, and they realized it's 257 00:13:07,559 --> 00:13:11,120 Speaker 1: actually not the high frequencies, but actually the middle ones 258 00:13:11,160 --> 00:13:12,960 Speaker 1: that cause the hair to go up on your neck. 259 00:13:13,080 --> 00:13:15,599 Speaker 1: So you know, in a movie, taking out or reducing 260 00:13:15,600 --> 00:13:19,040 Speaker 1: that middle frequency would be much easier to watch. All right, 261 00:13:19,080 --> 00:13:21,640 Speaker 1: But two last quick discoveries about this before we move on. 262 00:13:21,679 --> 00:13:24,760 Speaker 1: So number one, if you're given warning about someone scraping 263 00:13:24,760 --> 00:13:28,160 Speaker 1: a chalkboard before you do it, you actually react way, 264 00:13:28,160 --> 00:13:30,679 Speaker 1: way worse than if you just hear the sound. That's 265 00:13:30,679 --> 00:13:33,560 Speaker 1: actually pretty funny because I heard that behavioral economist Dan 266 00:13:33,679 --> 00:13:36,600 Speaker 1: Ry Ellie talk about removing bandages and how if someone 267 00:13:36,720 --> 00:13:38,880 Speaker 1: tells you or warns you that they're going to do 268 00:13:38,920 --> 00:13:42,040 Speaker 1: it and then gently pulls the bandages off your body, 269 00:13:42,360 --> 00:13:45,000 Speaker 1: you've got this higher tolerance for pain versus the idea 270 00:13:45,000 --> 00:13:46,920 Speaker 1: of just ripping them off and getting it over with. 271 00:13:47,480 --> 00:13:49,959 Speaker 1: And it's fine to think about what your mind can 272 00:13:50,000 --> 00:13:53,360 Speaker 1: and can't handle knowing in advance. That's pretty interesting. Well, 273 00:13:53,480 --> 00:13:55,160 Speaker 1: here here's the other thing I was gonna say. So 274 00:13:55,440 --> 00:13:58,320 Speaker 1: scientists have wondered whether our aversion to that nails on 275 00:13:58,360 --> 00:14:01,359 Speaker 1: a chalkboard sound is actually it's just the same frequency 276 00:14:01,440 --> 00:14:05,439 Speaker 1: as some primate warning calls. That's crazy. So primate warnings 277 00:14:05,440 --> 00:14:08,000 Speaker 1: and nails on the chalkboard are actually emitted at the 278 00:14:08,000 --> 00:14:11,280 Speaker 1: same frequency. Yeah, that's right, So it might accidentally be 279 00:14:11,400 --> 00:14:15,280 Speaker 1: triggering this danger instinct that's in all of us. Well, 280 00:14:15,400 --> 00:14:17,440 Speaker 1: I'm certainly glad that part of the show is over, 281 00:14:17,559 --> 00:14:19,640 Speaker 1: and I know we want to talk about earworms too, 282 00:14:19,680 --> 00:14:21,480 Speaker 1: which are the songs that get stuck in your head. 283 00:14:21,520 --> 00:14:23,560 Speaker 1: But before we do that, how about we have a 284 00:14:23,560 --> 00:14:27,080 Speaker 1: little palate cleanser of cute facts. Al right, sure, So 285 00:14:27,160 --> 00:14:29,560 Speaker 1: what do you have for us? So? Did you know 286 00:14:29,640 --> 00:14:32,160 Speaker 1: that baby turtles all hatch at the same time because 287 00:14:32,160 --> 00:14:36,800 Speaker 1: they're actually communicating through their eggshells. Oh that's like synchronized hatching. 288 00:14:36,840 --> 00:14:39,480 Speaker 1: That that is pretty cute. Good job, ango, Yeah, it 289 00:14:39,520 --> 00:14:41,640 Speaker 1: gives them a better chance to survival. And actually, I've 290 00:14:41,640 --> 00:14:44,040 Speaker 1: got another one for you. So did you know that 291 00:14:44,080 --> 00:14:47,000 Speaker 1: scientists at Georgia Tech have created software for barns and 292 00:14:47,080 --> 00:14:50,800 Speaker 1: henhouses that tries to create happier chickens. It does this 293 00:14:50,920 --> 00:14:53,920 Speaker 1: all by listening to their clucks and squawks. Apparently you 294 00:14:53,960 --> 00:14:56,720 Speaker 1: can tell whether a chicken is stressed, or too cold, 295 00:14:56,880 --> 00:14:59,240 Speaker 1: or a whole host of other things by listening to 296 00:14:59,280 --> 00:15:03,000 Speaker 1: a group's cluck king. And this smart barn software actually 297 00:15:03,040 --> 00:15:05,880 Speaker 1: listens to the sound feed of chickens and adjust things 298 00:15:05,960 --> 00:15:08,960 Speaker 1: like the lighting or temperature or whatever makes chickens a 299 00:15:09,000 --> 00:15:11,920 Speaker 1: little happier in their coupes. Apparently it makes for more 300 00:15:12,000 --> 00:15:16,120 Speaker 1: eggs and plumper chickens. That's pretty crazy, all right, Well, 301 00:15:16,120 --> 00:15:19,200 Speaker 1: why don't we move from eggs to earworms? And as 302 00:15:19,240 --> 00:15:22,000 Speaker 1: you know, earworms are those catchy songs and refrains that 303 00:15:22,080 --> 00:15:24,480 Speaker 1: gets stuck in your head. And sometimes they're there for 304 00:15:24,480 --> 00:15:26,800 Speaker 1: a few hours. Sometimes honestly for me, it feels like 305 00:15:26,840 --> 00:15:30,000 Speaker 1: they'll stay there for days and days. But the founding 306 00:15:30,000 --> 00:15:33,080 Speaker 1: director of the Music, Mind and Brain program at Goldsmiths 307 00:15:33,080 --> 00:15:35,440 Speaker 1: in London, her name is Lauren Smith. Well she's been 308 00:15:35,480 --> 00:15:39,480 Speaker 1: studying this phenomenon since two thousand nine, but earworms feel 309 00:15:39,480 --> 00:15:41,440 Speaker 1: like to been around for longer than that, right, Well, 310 00:15:41,480 --> 00:15:43,520 Speaker 1: the phenomenon is a whole lot older. And there's a 311 00:15:43,560 --> 00:15:46,240 Speaker 1: great New Yorker piece by Maria Knakova. You know, we 312 00:15:46,240 --> 00:15:48,080 Speaker 1: actually had her on the program before. Oh yeah, she 313 00:15:48,120 --> 00:15:50,960 Speaker 1: was so great. She did that wonderful podcast The Griffin. Yeah, 314 00:15:50,960 --> 00:15:53,000 Speaker 1: it was a really interesting what do But in this 315 00:15:53,080 --> 00:15:57,800 Speaker 1: piece specifically, she references this Russian musical prodigy named Nicholas Lanimski, 316 00:15:58,240 --> 00:16:00,320 Speaker 1: and he wrote a book in the nineteen is all 317 00:16:00,320 --> 00:16:04,120 Speaker 1: about creating musical patterns that quote hooked the mind and 318 00:16:04,200 --> 00:16:07,440 Speaker 1: force mimicry and repetition, And I don't know if he's 319 00:16:07,480 --> 00:16:10,360 Speaker 1: exactly talking about earworms here, but he is talking about 320 00:16:10,400 --> 00:16:14,240 Speaker 1: catchy music, and Frank Zappa and John Coltrane, among others, 321 00:16:14,240 --> 00:16:18,160 Speaker 1: were influenced by Slenemski's work. So the term earworm then 322 00:16:18,160 --> 00:16:20,960 Speaker 1: gets coined back in the nineteen seventies and this happens 323 00:16:21,000 --> 00:16:24,840 Speaker 1: in Germany. But even that has some old roots kind 324 00:16:24,880 --> 00:16:27,160 Speaker 1: of Covid writes about the old folk music that was 325 00:16:27,240 --> 00:16:30,440 Speaker 1: known to stick in your crawl, like quote a piper's maggot. 326 00:16:31,320 --> 00:16:34,120 Speaker 1: Exactly what that means, but it sounds gross. Which is 327 00:16:34,160 --> 00:16:36,800 Speaker 1: all to say that earworms have a long history, but 328 00:16:37,040 --> 00:16:39,280 Speaker 1: it was only with Lawrence Smith in two thousand nine 329 00:16:39,280 --> 00:16:42,760 Speaker 1: that they really studied what makes an earworm. So what 330 00:16:42,880 --> 00:16:44,920 Speaker 1: does make a earworm? Well, part of it has to 331 00:16:44,960 --> 00:16:47,960 Speaker 1: do with hearing a song a few times, but another 332 00:16:48,000 --> 00:16:50,920 Speaker 1: part is that the song itself normally has notes that 333 00:16:50,960 --> 00:16:54,280 Speaker 1: are very close together. So you're talking about like musical 334 00:16:54,280 --> 00:16:56,920 Speaker 1: intervals here. Yeah, that's right, a lot of half steps 335 00:16:57,000 --> 00:16:59,120 Speaker 1: or whole steps between a lot of the notes. But 336 00:16:59,640 --> 00:17:02,400 Speaker 1: also you know the notes getting held for a long 337 00:17:02,480 --> 00:17:04,920 Speaker 1: time and then it repeats. So if you're thinking about 338 00:17:05,000 --> 00:17:08,040 Speaker 1: something like you know the White Stripes seven Nation Army 339 00:17:08,080 --> 00:17:12,000 Speaker 1: where the song is repeating that like bum bump bump bump, 340 00:17:12,000 --> 00:17:15,040 Speaker 1: bum bomp, and that those notes are all right there 341 00:17:15,080 --> 00:17:18,520 Speaker 1: next to each other on the keyboard. I mean, that's 342 00:17:18,520 --> 00:17:22,040 Speaker 1: both fascinating and terrifying to me, that like Justin Bieber 343 00:17:22,200 --> 00:17:25,879 Speaker 1: or Fifth Harmonies, songwriters or whoever know exactly what makes 344 00:17:25,880 --> 00:17:27,879 Speaker 1: a song stick in our heads? Why is that terrifying? 345 00:17:28,000 --> 00:17:30,600 Speaker 1: Things wonderful because I don't need any more than my head, 346 00:17:31,080 --> 00:17:33,600 Speaker 1: They're already there. But do you have any insight on 347 00:17:33,880 --> 00:17:36,880 Speaker 1: why songs catch or like why they pop up when 348 00:17:36,920 --> 00:17:39,680 Speaker 1: we don't expect them to. Well, we don't know for sure, 349 00:17:39,720 --> 00:17:42,720 Speaker 1: but there is one hypothesis that's pretty interesting, and it's 350 00:17:42,760 --> 00:17:45,480 Speaker 1: the idea that people either get an earworm because it 351 00:17:45,600 --> 00:17:49,320 Speaker 1: matches their mental state or because it's helping you change 352 00:17:49,359 --> 00:17:51,959 Speaker 1: your mental state. So, as this article points out, if 353 00:17:51,960 --> 00:17:55,000 Speaker 1: you're feeling super sluggish, you might hear a song that 354 00:17:55,040 --> 00:17:57,880 Speaker 1: revs you up, or alternately, you know one that can 355 00:17:57,920 --> 00:18:00,480 Speaker 1: calm you down if the situation demands it. And that's 356 00:18:00,480 --> 00:18:03,400 Speaker 1: amazing that, like your body is your mind's regulating your body. 357 00:18:03,440 --> 00:18:06,439 Speaker 1: That right, So one last question on this before we 358 00:18:06,480 --> 00:18:08,600 Speaker 1: move on? How do you get rid of them? Like 359 00:18:08,720 --> 00:18:10,560 Speaker 1: I I heard the best way was to just sing 360 00:18:10,600 --> 00:18:13,639 Speaker 1: yourself another catchy song. But that seems like a terrible 361 00:18:13,760 --> 00:18:17,359 Speaker 1: cure to me. Well, distracting yourself is one way, but 362 00:18:17,440 --> 00:18:20,800 Speaker 1: the better way, according to researchers, is just to belt 363 00:18:20,840 --> 00:18:23,359 Speaker 1: the song out. Like, if you sing it, your mind 364 00:18:23,480 --> 00:18:26,440 Speaker 1: gets over it, or at least gets closer to being 365 00:18:26,440 --> 00:18:29,600 Speaker 1: over it, and then you can actually move on. Crazy. Well, 366 00:18:29,800 --> 00:18:31,359 Speaker 1: I want to talk about some of the more weird 367 00:18:31,440 --> 00:18:33,960 Speaker 1: funny sounds, but before we do, let's go to a break. 368 00:18:47,400 --> 00:18:49,680 Speaker 1: Welcome back to Part time Genius. Now we're talking about 369 00:18:49,720 --> 00:18:53,000 Speaker 1: some of the biggest, strangest and most irritating sounds in 370 00:18:53,160 --> 00:18:55,920 Speaker 1: the universe and basically a whole lot of noise you'd 371 00:18:55,960 --> 00:18:59,120 Speaker 1: love to block out and listeners what Well, we did 372 00:18:59,160 --> 00:19:02,119 Speaker 1: mention this in the episode description. Both this episode and 373 00:19:02,160 --> 00:19:03,720 Speaker 1: the one we did a few episodes back on the 374 00:19:03,800 --> 00:19:06,399 Speaker 1: art of trash talking were made possible by beats by 375 00:19:06,480 --> 00:19:10,000 Speaker 1: Dre and their noise canceling headphones. And just for the record, 376 00:19:10,080 --> 00:19:13,600 Speaker 1: Dr Dre did not personally collaborate or participate in this episode, 377 00:19:13,600 --> 00:19:15,760 Speaker 1: but we do look forward to working with him in 378 00:19:15,800 --> 00:19:18,679 Speaker 1: the future. Right of course. Well some ango before we 379 00:19:18,680 --> 00:19:20,720 Speaker 1: get back to it. You wanted to talk a little 380 00:19:20,720 --> 00:19:24,320 Speaker 1: bit about sound in history, right, Yeah. I was reading 381 00:19:24,320 --> 00:19:26,520 Speaker 1: this story at the huffing In post by David Hendy 382 00:19:26,720 --> 00:19:29,800 Speaker 1: about the history of sound and Nolan pointed it to me. 383 00:19:29,920 --> 00:19:33,600 Speaker 1: But it's filled with all sorts of great stories, and 384 00:19:33,640 --> 00:19:36,480 Speaker 1: one of them is like how medicine changed when stethoscopes 385 00:19:36,480 --> 00:19:39,000 Speaker 1: were invented. So doctors have been listening to the body 386 00:19:39,040 --> 00:19:41,639 Speaker 1: for clues forever, you know, heartbeats and paulse and whatever, 387 00:19:41,800 --> 00:19:45,159 Speaker 1: but suddenly there were all these gurgles and rattles and 388 00:19:45,280 --> 00:19:47,479 Speaker 1: hisses that they could now hear, and there was this 389 00:19:47,600 --> 00:19:50,560 Speaker 1: new level of sophistication, and it made the body so 390 00:19:50,680 --> 00:19:53,639 Speaker 1: much more wondrous and opened up all these new mysteries 391 00:19:53,680 --> 00:19:56,800 Speaker 1: and ideas through advances and sound. That's pretty cool. So 392 00:19:56,840 --> 00:19:58,760 Speaker 1: what else, Well, there was a bit on how the 393 00:19:58,800 --> 00:20:01,840 Speaker 1: early phonographs and g the phones weren't really exciting to 394 00:20:01,880 --> 00:20:04,480 Speaker 1: people because of their ability to play music. It was 395 00:20:04,520 --> 00:20:07,480 Speaker 1: really more because they were thought of as these recording devices, 396 00:20:07,520 --> 00:20:09,720 Speaker 1: like there were a way that you could preserve your 397 00:20:09,920 --> 00:20:14,040 Speaker 1: dying uncle's voice and his words of wisdom for posterity. 398 00:20:14,080 --> 00:20:16,359 Speaker 1: Instead of I don't know, just like a way of 399 00:20:16,440 --> 00:20:18,760 Speaker 1: playing your Power of Love, best of the eighties power 400 00:20:18,800 --> 00:20:22,080 Speaker 1: ballads album. So the article had these interesting things I 401 00:20:22,080 --> 00:20:25,320 Speaker 1: hadn't realized about sound in history, But the most fascinating 402 00:20:25,320 --> 00:20:27,320 Speaker 1: thing to me was just how music has been used 403 00:20:27,359 --> 00:20:30,040 Speaker 1: to control people. All right, well, you'll have to explain 404 00:20:30,080 --> 00:20:31,520 Speaker 1: this to me, what do you mean? So in one 405 00:20:31,560 --> 00:20:33,879 Speaker 1: section the article talked about town bells in history and 406 00:20:33,920 --> 00:20:36,040 Speaker 1: how they were used for the whole town to know, 407 00:20:36,359 --> 00:20:37,879 Speaker 1: I don't know when to get up in the morning 408 00:20:37,960 --> 00:20:40,159 Speaker 1: or when to sleep, but they also let you know 409 00:20:40,200 --> 00:20:42,760 Speaker 1: when to pray, or when to take up arms, or 410 00:20:42,840 --> 00:20:46,000 Speaker 1: when to do dinner. And this all sounds so harmless, 411 00:20:46,200 --> 00:20:49,720 Speaker 1: but as the article put it, it actually tightens both 412 00:20:49,840 --> 00:20:53,000 Speaker 1: the secular and religious authorities hold over the daily life 413 00:20:53,040 --> 00:20:56,400 Speaker 1: of all within hearing distance. Yeah, so that's one part 414 00:20:56,400 --> 00:20:58,560 Speaker 1: of it. But in terms of things like music, it 415 00:20:58,680 --> 00:21:01,840 Speaker 1: also works, right, Like how background music is often organized 416 00:21:01,840 --> 00:21:04,000 Speaker 1: to this rhythm that and that tries to calm you 417 00:21:04,040 --> 00:21:06,760 Speaker 1: down or get us to work harder, or eat faster 418 00:21:07,000 --> 00:21:09,400 Speaker 1: or buy more. Yeah, I mean you always hear about 419 00:21:09,400 --> 00:21:11,800 Speaker 1: that at restaurants where they don't want you lingering or 420 00:21:12,119 --> 00:21:14,080 Speaker 1: that old story of the mall parking lot and when 421 00:21:14,119 --> 00:21:16,159 Speaker 1: I think it was in Australia where they were playing 422 00:21:16,720 --> 00:21:19,280 Speaker 1: Barry Manilow and music like that, just to keep the 423 00:21:19,359 --> 00:21:22,000 Speaker 1: kids from lloitering there at night. All right, well, I 424 00:21:22,040 --> 00:21:23,600 Speaker 1: know we've got a fact off to get to, but 425 00:21:23,720 --> 00:21:26,439 Speaker 1: before we do, why don't we each tell one story 426 00:21:26,720 --> 00:21:29,159 Speaker 1: of an annoying sound in history? Do you want to 427 00:21:29,160 --> 00:21:31,320 Speaker 1: do this? Yeah, all right, why don't you go first? 428 00:21:31,680 --> 00:21:33,960 Speaker 1: How one of the best and worst venues to be 429 00:21:34,000 --> 00:21:37,920 Speaker 1: a performer, which was Shakespeare's Globe Theater. Shakespeare's Globe Theater 430 00:21:38,000 --> 00:21:40,480 Speaker 1: and you get to work with Shakespeare performed for royalty. 431 00:21:40,520 --> 00:21:43,320 Speaker 1: Why would this be a terrible place? Honestly, it was 432 00:21:43,359 --> 00:21:46,480 Speaker 1: because the crowds were so awful. I mean, the sound 433 00:21:46,520 --> 00:21:48,880 Speaker 1: is only part of the experience, and for the actors, 434 00:21:48,960 --> 00:21:51,560 Speaker 1: they were constantly under the threat of, like having rotten 435 00:21:51,640 --> 00:21:54,399 Speaker 1: vegetables thrown in their direction, you know, if the rowdy 436 00:21:54,480 --> 00:21:57,320 Speaker 1: crowd didn't like their work. But the smell was a 437 00:21:57,400 --> 00:22:00,840 Speaker 1: huge assault on the census. So, according to literary traveler 438 00:22:00,880 --> 00:22:03,520 Speaker 1: dot com, the penny seats in the yard which went 439 00:22:03,520 --> 00:22:06,280 Speaker 1: to the folk known as I don't know the groundlings, 440 00:22:06,400 --> 00:22:09,399 Speaker 1: or sometimes the stinkers. It was full of drunks and 441 00:22:09,440 --> 00:22:12,399 Speaker 1: they were just waiting and standing ankle deep in mud. 442 00:22:13,119 --> 00:22:16,560 Speaker 1: And according to the site, because the crowds were so thick, 443 00:22:17,080 --> 00:22:19,560 Speaker 1: like the bathroom breaks for men, just ment aiming between 444 00:22:19,600 --> 00:22:22,120 Speaker 1: your shoes. Oh my god, that's so gross. I know 445 00:22:22,800 --> 00:22:25,399 Speaker 1: it wasn't exactly hygienic, but you get what you pay for. 446 00:22:25,560 --> 00:22:28,919 Speaker 1: And for the actors it was even worse because in 447 00:22:28,960 --> 00:22:32,800 Speaker 1: addition to all the stink the acoustics were miserable. Like 448 00:22:32,960 --> 00:22:35,879 Speaker 1: the crowds would be yelling and chatting and fighting, and 449 00:22:35,880 --> 00:22:38,800 Speaker 1: so just to get the stories communicated, the actors would 450 00:22:38,840 --> 00:22:42,520 Speaker 1: have to over exaggerate their gestures and like boom their lines, 451 00:22:42,560 --> 00:22:45,359 Speaker 1: which totally changes how you'd imagine like a Shakespeare play. 452 00:22:45,400 --> 00:22:47,639 Speaker 1: If you're thinking about Hamlet, just yelling to be or 453 00:22:47,680 --> 00:22:50,960 Speaker 1: not to be over this noisy crowd. It's pretty funny though, 454 00:22:51,080 --> 00:22:54,520 Speaker 1: just always angry. I could see why an actor would 455 00:22:54,520 --> 00:22:56,680 Speaker 1: want to tune that out. All right, Well, my story 456 00:22:56,720 --> 00:23:00,480 Speaker 1: is about music being used by interrogators. I'm or remember 457 00:23:00,520 --> 00:23:03,480 Speaker 1: how the FBI played Tibetan monk Chance outside the Branch 458 00:23:03,560 --> 00:23:07,320 Speaker 1: Davidian Compound and Waco, you know, just to drive them crazy. 459 00:23:07,359 --> 00:23:10,200 Speaker 1: But it isn't the only case of them doing this. Apparently. 460 00:23:10,200 --> 00:23:13,000 Speaker 1: In two thousand three, the BBC reported that the US 461 00:23:13,119 --> 00:23:17,400 Speaker 1: was blasting songs from Metallica, Skinny Puppy and of course 462 00:23:17,440 --> 00:23:19,800 Speaker 1: the theme song to Barney to get people to talk. 463 00:23:20,320 --> 00:23:22,840 Speaker 1: How about it that like Barney gets thrown in that 464 00:23:22,920 --> 00:23:26,159 Speaker 1: next somehow that feels like even crueler. Yeah, I just 465 00:23:26,200 --> 00:23:28,520 Speaker 1: don't think that should be allowed. Well, but according to 466 00:23:28,600 --> 00:23:31,960 Speaker 1: news Week, twenty four hours of it will drive someone insane. 467 00:23:32,280 --> 00:23:34,840 Speaker 1: Twenty four hours. I'm thinking like thirty minutes of this 468 00:23:34,960 --> 00:23:38,119 Speaker 1: and I'll be ready to talk. That's definitely a sound 469 00:23:38,200 --> 00:23:40,440 Speaker 1: you want to block out. But you know, the story 470 00:23:40,480 --> 00:23:43,159 Speaker 1: got weirder because when the band Skinny Puppy heard about this, 471 00:23:43,240 --> 00:23:46,760 Speaker 1: they realized the government owed them royalties for playing their music. 472 00:23:47,240 --> 00:23:49,840 Speaker 1: So they sent the Department of Defense a six hundred 473 00:23:49,880 --> 00:23:53,439 Speaker 1: thousand dollar bill for royalties. Actually was six hundred and 474 00:23:53,480 --> 00:23:56,359 Speaker 1: sixties six thousand, because you know, I guess they were 475 00:23:56,359 --> 00:23:58,840 Speaker 1: trying to make a point here. That's funny and pretty cavalier. 476 00:23:59,040 --> 00:24:01,080 Speaker 1: But now that gotten a little warmed up with a 477 00:24:01,119 --> 00:24:03,120 Speaker 1: back and forth, why don't we start the fact off, 478 00:24:03,840 --> 00:24:05,639 Speaker 1: all right, I'm for it. Well, we knew we'd be 479 00:24:05,640 --> 00:24:08,960 Speaker 1: talking about some terrible sounds, so we agreed in advance 480 00:24:09,040 --> 00:24:11,040 Speaker 1: that we would keep this one focused on you know, 481 00:24:11,040 --> 00:24:13,000 Speaker 1: it makes something a little happier. So we're going to 482 00:24:13,119 --> 00:24:15,399 Speaker 1: do a cute animal edition. Are you still up for this? 483 00:24:15,760 --> 00:24:27,679 Speaker 1: That's right, all right, well let's do it. So, I know, 484 00:24:27,800 --> 00:24:30,880 Speaker 1: we both watched that David Edinburgh clip on YouTube about 485 00:24:30,920 --> 00:24:33,960 Speaker 1: the liar bird. It's amazing because in it, like this 486 00:24:34,040 --> 00:24:36,879 Speaker 1: bird imitates all these sounds like a car alarm and 487 00:24:36,920 --> 00:24:39,919 Speaker 1: a cell phone or even a chainsaw in the wild, 488 00:24:40,440 --> 00:24:42,359 Speaker 1: and the doc makes it seem like the liar birds 489 00:24:42,400 --> 00:24:45,520 Speaker 1: picked up those sounds from I don't know, developers invading 490 00:24:45,560 --> 00:24:48,119 Speaker 1: the forest. But the real reason the bird on camera 491 00:24:48,160 --> 00:24:50,680 Speaker 1: could actually make those sounds was that it had been 492 00:24:50,760 --> 00:24:55,159 Speaker 1: living in captivity at the zoo. So apparently the bird 493 00:24:55,320 --> 00:24:59,080 Speaker 1: name Chook, had overheard construction on the new panda enclosure. 494 00:24:59,320 --> 00:25:01,280 Speaker 1: And that's how you did all this like hammering and 495 00:25:01,359 --> 00:25:05,360 Speaker 1: drilling and sauce sounds to his repertoire. That's still incredible though, 496 00:25:05,359 --> 00:25:07,840 Speaker 1: that they can do that, It's it's it's pretty wild. Well, 497 00:25:07,880 --> 00:25:11,160 Speaker 1: did you know that dolphins actually don't have vocal cords? 498 00:25:11,200 --> 00:25:13,800 Speaker 1: So when they're squeaking and chirping, they're actually doing it 499 00:25:13,840 --> 00:25:16,159 Speaker 1: through a lip shaped tissue in their nose and and 500 00:25:16,200 --> 00:25:19,960 Speaker 1: these are called phonic lips. That's super weird. Speaking of 501 00:25:19,960 --> 00:25:22,520 Speaker 1: water critters, did you know that walruses come with bells 502 00:25:22,520 --> 00:25:25,800 Speaker 1: and whistles. They make a bell sound underwater, not from 503 00:25:25,840 --> 00:25:28,840 Speaker 1: their vocal cords, but instead from these inflatable sacks called 504 00:25:28,880 --> 00:25:32,679 Speaker 1: pharyngeal pouches. It's actually kind of beautiful. Well, you know 505 00:25:32,720 --> 00:25:35,960 Speaker 1: what isn't beautiful, mango? When that's the sound of a kowal. 506 00:25:36,680 --> 00:25:39,200 Speaker 1: They might look like bears, but they actually grunt more 507 00:25:39,240 --> 00:25:43,360 Speaker 1: like pigs. So this isn't exactly an animal. But I 508 00:25:43,400 --> 00:25:45,840 Speaker 1: did want to talk about Wolverine and the sound his 509 00:25:45,960 --> 00:25:48,000 Speaker 1: claws make and the X Men movies. You're right, he 510 00:25:48,080 --> 00:25:50,840 Speaker 1: is not an animal. But to make the sound of 511 00:25:50,880 --> 00:25:55,040 Speaker 1: him flashing and retracting those atmantium claws, the sound designer 512 00:25:55,240 --> 00:25:57,920 Speaker 1: used the sound of a knife being drawn from a sheath. Right, 513 00:25:58,040 --> 00:26:00,640 Speaker 1: that makes sense, But because the sound make it seem 514 00:26:00,680 --> 00:26:03,520 Speaker 1: like the clause we're emerging and then slipping back into 515 00:26:03,520 --> 00:26:07,040 Speaker 1: Wolverine's flesh, enough, sound designer mixed it with the juicy 516 00:26:07,119 --> 00:26:09,879 Speaker 1: sound of a chicken carcass being pulled apart, so you 517 00:26:09,920 --> 00:26:12,320 Speaker 1: get like a little squishing noise in there too, if 518 00:26:12,359 --> 00:26:16,320 Speaker 1: you listen closely. It's weird, just saying squishing noise kind 519 00:26:16,320 --> 00:26:19,280 Speaker 1: of makes react. All right, we'll Speaking of movies, I've 520 00:26:19,320 --> 00:26:22,080 Speaker 1: got a great one from Jurassic Park. And obviously it's 521 00:26:22,119 --> 00:26:24,800 Speaker 1: hard to figure out exactly what a t rex roar 522 00:26:24,840 --> 00:26:28,040 Speaker 1: would have sounded like, so the sound designer sampled and 523 00:26:28,119 --> 00:26:31,840 Speaker 1: blended a number of different sounds, everything from a baby 524 00:26:31,880 --> 00:26:36,560 Speaker 1: elephant crying to a hissing tiger to an alligator's gurgle. 525 00:26:36,600 --> 00:26:39,080 Speaker 1: Apparently I don't know exactly what that is, but that's 526 00:26:39,119 --> 00:26:41,720 Speaker 1: what it says. But they all got slowed down and 527 00:26:41,840 --> 00:26:44,760 Speaker 1: mixed together to make for this what they considered a 528 00:26:44,760 --> 00:26:48,040 Speaker 1: realistic t rex roar. That's pretty amazing, and it is 529 00:26:48,080 --> 00:26:50,520 Speaker 1: better than a motorcycle fart. I guess I think you're 530 00:26:50,560 --> 00:26:54,520 Speaker 1: probably right about that. Also, to make the dinosaur's breathing sound, 531 00:26:54,560 --> 00:26:57,119 Speaker 1: the engineers modified the sound of air coming out of 532 00:26:57,119 --> 00:27:00,000 Speaker 1: a whale's blowhole. That's pretty cool. Huh. Yeah, that's all. 533 00:27:00,640 --> 00:27:02,760 Speaker 1: And while none of those are sounds I seek out, 534 00:27:02,960 --> 00:27:05,199 Speaker 1: I am sufficiently impressed that I'm going to crown you 535 00:27:05,240 --> 00:27:07,560 Speaker 1: this week's winter Well. Thank you very much, and and 536 00:27:07,640 --> 00:27:10,320 Speaker 1: thanks to Beats by Drey for sponsoring this episode. If 537 00:27:10,359 --> 00:27:13,199 Speaker 1: there's some great noises from the natural world or history 538 00:27:13,240 --> 00:27:15,399 Speaker 1: that you'd love to share with us, remember you can 539 00:27:15,440 --> 00:27:17,920 Speaker 1: always email us part Time Genius at how Stuff Works 540 00:27:17,960 --> 00:27:21,320 Speaker 1: dot com. You can always reach us one fact hotline 541 00:27:21,320 --> 00:27:24,000 Speaker 1: that's one eight four four pt Genius, and of course 542 00:27:24,040 --> 00:27:26,200 Speaker 1: you can hit us up on Facebook or Twitter. Two. 543 00:27:26,600 --> 00:27:42,200 Speaker 1: Thanks so much for listening. Thanks again for listening. Part 544 00:27:42,200 --> 00:27:44,240 Speaker 1: Time Genius is a production of How Stuff Works and 545 00:27:44,240 --> 00:27:46,879 Speaker 1: wouldn't be possible without several brilliant people who do the 546 00:27:46,920 --> 00:27:50,240 Speaker 1: important things we couldn't even begin to understand. Tristan McNeil 547 00:27:50,320 --> 00:27:52,720 Speaker 1: does the editing thing. Noel Brown made the theme song 548 00:27:52,760 --> 00:27:55,560 Speaker 1: and does the mixy mixy sound thing. Jerry Rowland does 549 00:27:55,600 --> 00:27:58,760 Speaker 1: the exact producer thing. Gay Bluesier is our lead researcher, 550 00:27:58,800 --> 00:28:01,760 Speaker 1: with support from the Research Army including Austin Thompson, Nolan 551 00:28:01,800 --> 00:28:04,000 Speaker 1: Brown and Lucas Adams and Eve Jeff Cook gets the 552 00:28:04,000 --> 00:28:06,280 Speaker 1: show to your ears. Good job, Eves. If you like 553 00:28:06,359 --> 00:28:08,199 Speaker 1: what you heard, we hope you'll subscribe. And if you 554 00:28:08,240 --> 00:28:10,200 Speaker 1: really really like what you've heard, maybe you could leave 555 00:28:10,200 --> 00:28:13,240 Speaker 1: a good review for us. Did you forget James Jason 556 00:28:13,280 --> 00:28:13,440 Speaker 1: who