Archive for the ‘Media’ Category

Lutefisk Lament

Saturday, September 12th, 2009

Today, I ended a decade-long search for a specific recording. If you’ve ever tried to search for something very specific and obscure on the web before, you might know my frustration. The recording in question was a Christmas-themed song, “Lutefisk Lament.” It’s basically a satire of “The Night Before Christmas,” about how horrible Lutefisk is.

The song has great sentimental value in my family, as we are mostly Norwegian. I’ve never had Lutefisk and probably never will, a testament to the impact the song has had on me. Our family came across it by way of a cassette tape, recorded from many novelty Christmas records my grandfather came by. He sold RCA stereos back in the time when my dad was a kid, and would occasionally be sent various promo albums. Someone along the lines compiled lots of the strange or novel Christmas songs from those records onto a tape.

This is the tape I remember, although I don’t remember it well. Every Christmas season my mom would pull it out of storage, and I would listen to it on a tiny portable cassette recorder while laying on the couch and waiting for Christmas Eve. I can only remember bits and pieces about the songs that were on it. I’ve searched rather fruitlessly on the web for years, and unfortunately have come across very little. I remember some songs (“We Need a Little Christmas” from the musical Mame), but since it was a homemade tape there’s no way to positvely identify any of the performers or even some of the song titles.

Every year, I google around for a bit, and usually come up short. Today, I started working on the annual Christmas album I record for my mom (if you haven’t gathered by now, she’s the parent who’s really into the holiday, and she definitely passed that fervor on to me). Going through lists of Christmas songs, I recalled my annual search and decided to tread through the same old Google search results, the same old blogs, and the same old dead links, desperate for the song. It’s not on Amazon and it’s not on iTunes, which is unfortunate because I would have bought it straight away if I’d found it.

This year was different. The first page of results had a link to a new page I hadn’t seen before. It mentioned a webpage which included downloads from WCCO-AM (in Minneapolis, MN). I went to the page and — lo and behold! — the track was there. I had the usual moment of fear as I worried that the link to the track would be a dead link, but it downloaded straight away, and I saved it, and now the track is mine, and it’s just as wonderful as I remember it being all those years ago, when Santa was an actual person who came down our chimney.

The song can be found on this page. Scroll down to 1980 under the first section, WCCO Air Checks. This version is done by Charlie Boone and Roger Erickson (this was one of the frustrating things I’d found out in years prior, frustrating because having the song name and performers wasn’t enough to find it). Please listen and enjoy, and spread the word if you can, because the world really needs to know about the terrors of Lutefisk.

How to Win (Or Maybe Not) on Wheel of Fortune

Wednesday, August 19th, 2009

Wheel! Of! Fortune!One nice thing about being a programmer is that you can automate certain calculations that you’d have to be crazy to attempt any other way. While some would see a non-programmer attempting to figure out some of this stuff as borderline insane, we coders just come across as eccentric with a lot of time on our hands. If people ask a question fairly frequently, and said question involves lots of number-crunching, you can bet some coder somewhere has taken a crack at trying to crunch those numbers.

Case in point: Wheel of Fortune. Now, I’ve never really been a huge fan of the show, but I see it a lot anyway. It’s on after Jeopardy!, which I really do enjoy and try to watch fairly frequently, so I’ve seen my fair share of episodes of Wheel. One thing that always got me was the final puzzle. For those of you who don’t know, this is how it works: the winning contestant from all the previous rounds must solve a shorter, harder puzzle by himself in a small span of time. He is given a (usually unhelpful) hint in the form a category, and some of the most common letters in the English language (R, S, T, L, N, and E) are already shown. Then the contestant must choose three more consonants and one more vowel. If any of these letters occur in the puzzle Vanna White shows them, and the players has ten seconds to guess what the word or phrase is.

There are other factors at play here, but they don’t relate to what I’m interested in most, namely: What are the best letters to pick? Can we do an analysis of the letter frequency of a whole bunch of these puzzles? Can we determine whether or not the producers of the show pay attention to these frequencies? Thanks to the Internet and some spare time in the hands of a programmer, the answer is a (qualified) yes, we can. Please note that while I do enjoy math, I am most certainly not a mathematician, so this is just an armchair analysis, and not a scholar’s take.

First, I needed a set of data. As interested as I was in determining the letter frequencies, I wasn’t about to spend six months collecting data by actually watching the end of each show. I have the Internet to do that sort of stuff for me! In this case, I found this forum, whose residents had already done the hard work. I was able to grab the final puzzles from a couple of threads on this site, and store them in some text files, one puzzle to a line. Then, I wrote a short Python script to parse through the results and generate links to a Google Charts representation of the data. If you’re going to screw around on the Internet, why waste time inputting data into Excel?

The Code

Below is the code. Please note that while I have commented it, it’s task-oriented code. I did not sit down and think things through for hours on end; I was more interested in the results produced by the code than the process of making it. To that end it may be a bit rough around the edges. If you’re a Python programmer you might even think it un-Pythonic.

Show/Hide Source Code

from operator import itemgetter # for sorting
import sys # for command-line arguments
 
# makes sorting dictionaries prettier
def sortDictionary (s):
    return sorted(s.items(), key = itemgetter(1), reverse = True)
 
hexColors = ["F05DCF", "F4B213", "7BB5FE", "19B915",
       "C913E4", "E38080", "4891EB", "DCF725", "E02EB0",
       "EE7D18", "16D949", "73E0C9", "22F1DB", "1460A1",
       "CF8040", "FFFFFF", "CF8054", "204E00", "2B1160",
       "87513C", "DECEE9", "C913E4", "83B892", "597D4C",
       "DACA5D", "2F486B", "D79E17", "826889", "359DA1",
       "DE7A43", "568C51", "FBF786"]
 
 
if __name__ == "__main__":
    # set up command line arguments
    # thumb:   creates a smaller file, with shorter (or no, depending on letter count) labels
    # verbose: prints out each list of letters and frequencies, too
 
    if (len(sys.argv) < 2 or len(sys.argv) > 4):
        print "Usage: wof.py [filename] [t|f] [v]"
        exit()
 
    thumb = False
    verbose = False
    fileName = sys.argv[1]
    if len(sys.argv) > 2 and sys.argv[2].lower() == "t":
        thumb = True
    if len(sys.argv) > 3 and sys.argv[3].lower() == "v":
        verbose = True
 
 
    # set up lists of letters
    letters = ["a", "b", "c", "d", "e", "f", "g", "h",
               "i", "j", "k", "l", "m", "n", "o", "p",
               "q", "r", "s", "t", "u", "v", "w", "x",
               "y", "z"]
    consonants = ["b", "c", "d", "f", "g", "h",
                "j", "k", "l", "m", "n", "p",
               "q", "r", "s", "t", "v", "w", "x",
               "y", "z"]
    vowels = ["a", "e", "i", "o", "u"]
 
    # letters to exclude (already given to you on game show)
    already = ["r", "s", "t", "l", "n", "e"]
 
 
    # set up frequency dictionaries {leter : number of occurences}
    allFrequencies = dict((letter, 0) for letter in letters)
    vowelFrequencies = dict((letter, 0) for letter in vowels)
    consonantFrequencies = dict((letter, 0) for letter in consonants);
 
    # Read the data file. Should consist of one final puzzle
    # solution per line, optionally lines can start with "#" for a comment
    file = open(fileName)
    while True:
        line = file.readline()
        if not line: break #end of loop
        if line[0] == "#": continue # skip comments
        for letter in line:
            lower = letter.lower()
            if lower in allFrequencies:
                allFrequencies[lower] = allFrequencies[lower] + 1
            if lower in already: # exclude RSTLNE from vowels and consonants
                break
            if lower in vowelFrequencies:
                vowelFrequencies[lower] = vowelFrequencies[lower] + 1
            if lower in consonantFrequencies:
                consonantFrequencies[lower] = consonantFrequencies[lower] + 1
 
    #sort dictionaries
    allFrequencies = sortDictionary(allFrequencies);
    vowelFrequencies = sortDictionary(vowelFrequencies);
    consonantFrequencies = sortDictionary(consonantFrequencies);
 
    if verbose:
        #display the lists
        print "ALL:\n", allFrequencies
        print "\nVOWELS:\n", vowelFrequencies
        print "\nCONSONANTS:\n", consonantFrequencies
 
 
    charts = {"All+Letters" : allFrequencies, "Vowels" : vowelFrequencies,
             "Consonants" : consonantFrequencies}
 
    for chart in charts:
        # make the image URLs, using Google Charts
        if thumb:
            url = "http://chart.apis.google.com/chart?chs=100x100&cht=p"
        else:
            url = "http://chart.apis.google.com/chart?chs=400x300&cht=p"
 
        # build lists for data series and its labels
        labels = []
        data = []
        for entry in charts[chart]:
            if int(entry[1]) > 0: # exclude any letters not used
                # make sure a thumbnail doesn't have too many labels to clutter it
                if thumb and len(charts[chart]) <= 6:
                    labels.append(entry[0].upper())
                else:
                    labels.append(entry[0].upper() + "+(" + str(entry[1]) + ")")
                data.append(str(entry[1]))
 
        # set them to the query string parts for data and labels
        dataRange = "&chd=t:" + ",".join(data);
        if (thumb and len(charts[chart]) >= 6):
            labelRange = ""
        else:
            labelRange = "&chl=" + "|".join(labels);
 
 
        # build the array of chart colors
        chartColors = "&chco=" + ",".join(hexColors[0:len(charts[chart])-2])
 
        # build final URL
        url = url + dataRange + labelRange + "&" + chartColors + "&chtt=" + chart;
        print "\n", chart, "\n", url

The Results

Might as well show off the pretty, pretty pictures, huh? Click any graph below to enlarge it.

At first look, the data is not too promising. I can give you two letters that will increase your chances of getting a ‘hit’, and one of them might come in handy. In our six months’ worth of data, O is the favorite… but not by much. Looking at both periods, it seems pretty clear that somebody at Merv Griffin Productions is responsible for distributing the vowels O, I, and A across the spectrum so none of them shows up too frequently. Notice how I and O are tied on the most recent set of data, but A is the second-most frequent vowel on the older figures. Combining all the numbers, we see that these three vowels are essentially tied in frequency, with U in a slightly lower class. But at least it’s something to work with, right? From the last six months of Wheel, it looks like ‘O’ is the best vowel to go with.

Now what about consonants? I was most excited when I pulled up the 2009 consonants graph (the first one I did), because you can clearly see that the top two letters are definitely a bit more common than the rest, and even the top three look pretty solid. H, G, and D… could those be the winning ones? My excitement faded, however, as I ran the earlier set of data through the script. Looking at the combined chart, H still has a statistically significant lead. But you’ll have no luck trying to discover the three letters to choose. But we can limit our options a little. F, G, and B are all clearly separated from the next letter (D) in the combined graph, with a decent-sized gap between them. It’s harder to say for certain, but it looks like the producers may be balancing these top four letters throughout their puzzles.

So, what to go with? You should definitely choose O for your vowel. H is the consonants which statistically is most likely to occur. Then any of F, G, and B would probably do you some good.

And how about those shifty producers? Are they gaming the final answers, so they don’t have to give out as much prize money? Are they maybe picking and choosing their phrases to deflect somebody who did a little research before heading down to the studio to play? Well, let’s try to find a pattern in the frequency of letters in the English language (please note that I’ve removed RSTLNE from these graphs):

Right away you should notice some major discrepancies between the Wheel of Fortune data set and written English. While H shows up at the top where we’d expect, D is clearly in a much higher class than B, F, and G that we picked above. In fact, F and G aren’t even in the top five, and other letters that show up often in English aren’t placed very high in the combined final puzzle data. This is probably the result of producers fine-tuning their answers over the years, either to avoid the letters contestants chose most often or to more evenly distribute the winning ones.

This is such a small data set, however, that we shouldn’t rely on it too heavily. After all, Wheel of Fortune has been on the air for twenty-six years, and we only have half a year’s worth of data, or around 2% of all that is available. But a small attempt at analyzing this data is probably better than going in blind and picking letters that you ‘think’ show up frequently.

There are other ways that this quick-and-dirty analysis can be improved. Mine is a pretty naive approach. Going over some basic rules of English might help to improve the method. For example, breaking the final puzzles down into phonemes could yield more information, as might looking at letter pairs instead of single letters. For instance, Q never occurs without U, and some letters are more common after others. This is especially useful in our task, as we need to choose three consonants but only one vowel. Consonants are most often followed by vowels, so consonant pairs increase the uniqueness of a phrase. P is often followed by R, L, or H, for example. Looking for patterns in the words themselves might also yield better predictions about what letters would be better to guess.

Another thing to realize is that these numbers are averages from a discrete set. Some puzzles might include the high-frequency letters and be solvable with only those (and RSTLNE), while some might not include a single one of the high-frequency picks. Picking from one of the high scorers might improve your odds of getting more letters, but it doesn’t guarantee that you’ll get some, or even any. You might wind up with something like ‘Blind Luck’, which doesn’t contain an O or an H. These estimates can help you, but only so much.

So, after all these calculations, I now know what I would do if I ever found myself in Wheel’s final round. I’d go for H, G, and B (G and B having been arbitrarily picked over F), and then O as my vowel. And maybe I’d win big. Of course, the biggest factor in all this is your ability to manipulate letters and words in your mind. That’s one subject in which I lack skill, as evinced by the Boggle-solving program I wrote (a story for another time). So I might tank, even if my statistically-chosen letters filled out quite a bit of the puzzle. A lot of it does come down to luck, which was probably the producers’ intention all along.

Twitter: UR DOING IT RONG

Thursday, August 13th, 2009

I’ve been using Twitter for a while now, and in that short amount of time, I’ve heard a lot about how other people are using it, too. Twitter started out as something special, but if we’re not careful, it’s going to become another part of the dregs of the Internet — a haven for spammers and friendwhores.

The allure of the site for me was the microblogging aspect. Random things pop into my head throughout the day, and some of them are serviceable enough to share. This wasn’t a problem in my old job, because I worked in the same room with a bunch of like-minded peers who often agreed with me and had more input in the same oeuvre. Now, however, I have an office, and can’t shout random observations about whatever pops into my head to my coworkers. They’re for the most part older than me, and not as interested in video games, comic books, programming, and old 80’s pop culture as I am. By microblogging on Twitter, I was potentially able to share these thoughts with like-minded individuals.

But, as with most other things on the web, people are seeing this new platform for sharing as a chance for self-promotion. This comes in two flavors, both bitter: those who want to make money off of it, and those who want to increase their status on it. Both of these reasons are wrong and worsen the site.

Those who try to make money off of it usually do it wrong. My follower count hovers around 50, going up and down by two or three accounts every day, as spammers find me, follow me and 1,000 other people, then get reported and banned. The spammers are easy to spot: every single tweet is a link, and they usually mention a) making money or b) sex, apparently the only two revenue-generating topics on the whole wide web. There are a few commercial accounts who get it right. One I’m particularly fond of is Amazon’s MP3 store (@amazonmp3), which posts a daily discounted album every single day. The key difference between this use of Twitter and the spammers is that they are offering something of value to me: cheap downloads of music. The spammers, on the other hand, are only trying to make money for themselves. They want to take, take, take without giving back, and they’re tearing Twitter apart.

The other kind are the friend whores, the people who do anything to get others to follow them. I’m sure one or two of the daily fluctuations in my Twitter followers come from people who follow me only because they expect to be followed back. This isn’t the way the site is supposed to work, fellas. You follow me because you think I have something interesting to say. I follow you back if I believe the same thing. This isn’t some sort of commodities market, where we trade shares in each others’ tweets. The point of twitter isn’t to gather as many followers as possible. I have to admit that in my early days, I was guilty of exacerbating things. I would reciprocate follows. This led to trouble when I logged on and realized that I really didn’t care about so-and-so’s self-promotion or auto-generated messages about tools they were using. I would ignore their posts, and at the same time miss the point — your Twitter feed is for hearing things from people you find interesting. Your signal-to-noise ratio should be infinite, because you should follow only those people who interest you to begin with, and you shouldn’t find any noise cluttering your feed.

I’m sure Twitter is doing something to combat the spammers, but I’m not so sure about the others. Twitter has lots of neat applications, but the company can’t really help it if their site is overrun by the self-promoters. The best technology in the wrong hands (and I don’t mean evil or even malicious hands) can become worthless. I’ll continue to use Twitter the way I think it should be used, but it’s becoming harder and harder to find like-minded individuals. The thing with the web is that if one site doesn’t do what you want, there’s usually another out there gunning for it. The question is this: will Twitter realize this before it’s washed out by its own users?

Streaming Video: A Rant From Twitter

Friday, August 7th, 2009

Why can’t streaming video player programmers EVER get their buffer size prediction algorithms correct? Or, failing that, just make them more fault-tolerant so they buffer more than is necessary to start playing? I’m watching Amazon video on demand, and golly gee, it would be nice if I had control to buffer as much as I wanted, instead of what the moronic algorithm programmed into it thinks is enough.

Other irksome things: When it has to re-buffer, it takes away the progress indicator. This is because during 33% of rebuffers, the connection cuts. This way, I have to guess where I was on the movie when I re-load the page. Amazon, I know you’re trying to idiot-proof your software, but can you please put up something so we have some semblance of control? All I want is a truthful indicator of the connection status, and control over the buffer… is that too much to ask?

Oh, one more thing: If I pause, that’s your opportunity to LOAD AS MUCH BUFFER AS POSSIBLE. I’m hoping some progress has been made since this rant started, but I highly doubt that.

Code Monkey (Jonathan Coulton cover)

Wednesday, May 21st, 2008

This is a bare-bones acoustic cover of Jonathan Coulton’s song, “Code Monkey.” The cover’s nothing special, just something I did in between packing stuff. I recorded it live with my Mac’s mic, with very little processing: a little noise reduction here, a little bass reduction there. The hardest part was keeping quiet, since it is technically quiet hours in my dorm. Enjoy!

Download MP3 here.

Smash Bros Brawl Has a Broken AI

Tuesday, May 6th, 2008

Try this experiment:

  1. Start a game of Smash Bros Brawl on Free For All. Use stock mode.
  2. Just play with one player, set the rest to CPUs on level 9.
  3. Start the game, and time how long it takes for the game to end.
  4. Now, replace yourself with another computer on level 9, and time that match.

Which game took longer? Nine times out of ten, it will probably be the all-computer match. Does the first game end quickly because the AI on Smash Bros Brawl is just that good, that three of them can usually beat a human player? Does the second game take longer because the computers are excelent players?

No, it’s because the AI is biased against humans. In FFA matches, the computers actually target the human players, leaving each other alone relatively. If you need proof of this, play FFA with two humans and two CPUs. If you and your friend are halfway decent and unbiased, you will probably be the last two standing. You can also try a 1v1 in FFA, you against a computer. It’s a lot easier. Even 1v1v1 is better. But when you get three computer players all ganging up on the one human, the game becomes a lot harder.

Need some examples of this bias? Read on. From what I’ve seen, Free-for-All with 3 CPUs is really a team match, human vs. 3 computers. The game has been kind enough to activate team damage, so every once in a while they’ll hurt each other. Here are some examples:

Final Smashes

This is where it gets ridiculous. They computer will, without fail, target the human players. If you happen to die right before a CPU gets the Smash Ball, that player will wait until you have come back to use it. If you wait up on your platform while you’re invincible, so will the CPU. He will not even consider using his Final Smash on his teammates. The other CPUs will not even consider trying to take it from him. The most ridiculous cases are Lucas or Ness. It looks like the programmers gave each character a final smash AI, so they know how to use it. A lot of characters (Captain Falcon, Meta Knight) need to be close to use their smash. Ness and Lucas don’t, however. Their final smash is screen-wide. But they usually try to get near the human player before they deploy it.

Even worse are the Final Smashes that involve controlling direction. For example, the Star Fox characters use their big, stupid tanks. Sonic flies around the stage, as does Pikachu. It’s especially fun to get into a corner where Fox’s tank can’t reach, or to lead him somewhere he’ll get stuck. If you stand still, he’ll try to get at you but not go anywhere, even if the other CPUs are easily accessible. Similarly, Super Sonic or Pikachu will try and hammer you. They might hit another CPU in passing, but they’re not fooling anybody.

Dragoon

This is the most infuriating. True, you can dodge it, but you need split-second timing. If one CPU gets this, he will target you mercilessly. Even if the other two CPUs are standing in a tempting cluster, the CPU will prefer hitting the human player for one kill over getting the other two computers for two. Like with the Final Smash, if you die just before they get it and wait to come out, the CPU will wait until your invincibility wears off before attacking you.

The Chase

Try playing a large stage, like the Zelda Castle or the custom ‘Maze’ stage. Right at the start of the match, run from the CPUs (all three will immediately begin chasing you when the match begins). You can lead the other three CPUs on a chase, round and round the stage. They will occasionally take swipes at each other, but they’re only love taps.

No unbiased person can argue that the CPU itself is unbiased. They hate human players. They even taunt the humans after they’ve killed them — but not other computers. Way to rub it in, guys.

So what can you do? Well, you can always play with at least one other human. People may develop grudges from time to time, but they usually mix it up after they’re told to piss off and stop targeting one person. You can’t do that for the AI. Unfortunately, if you just want a quick game by yourself, you’re SOL.

I’ve tried playing 1v1v1 in team mode, with me on one team and the other two players on different team. It seems to end up the same way.

For now, I guess we’ll just have to treat FFA like a team match, humans vs. robots. The Smash Bros Brawl AI is not the hardest alone, but with three ganging up on you, the sheer force of the numbers is enough to trip you up. The only upside to this situation is that if you keep practicing, you’ll probably get really good against other humans.

Why Cloverfield Will Suck

Sunday, January 13th, 2008

Don’t get me wrong. I’m going to see it, I’m excited as hell, and I’m pretty sure they’re gonna show the monster in all its glory — but I know the movie’s going to suck. Here’s why:

  1. There will be no buildup. My guess is that it starts out at the party, and goes from there. How about five minutes of strange incidents from around the globe, à la the viral videos already released? I don’t want to come into the movie and miss half of it because I’m too lazy to waste time clicking through tie-in websites that pretend to give you vital clues to the plot.
  2. There won’t be a plausible reason for the monster to attack NYC. Perhaps some suspension of disbelief is in order, but the fact that the film is a ‘realistic’ documentary will not play into the plot. Obviously, a gigantic creature that lives underwater will head to NYC, with a million buildings in the way and irritating explosions, to spawn/have fun/feed. I’m pretty sure there’s more food available in the ocean — including that tantalizing Slusho ingredient!
  3. We won’t get more info than what’s on the ‘recovered’ tapes. I love back story, and the shit we’re spoon-fed on the viral marketing websites won’t explain anything about the monster. So we’ll never know if it’s an alien, or a mutation caused by man, or something else. Some will say that this enhances the ‘mystery’, but I’ve had enough uninformed fan speculation from the lead-up to the movie. I want some goddamn answers, not more fanboy theory. I want to know A) what it is, B) why’s it’s pissed, and C) how they stopped it.
  4. There will be an epilogue, but it will leave more questions than answers. This is, after all, the product of J.J. “Lost” Abrams.
  5. They’re gonna waste time on the ‘parasites.’ You know, the little creatures the main monster exudes? The ones that are probably taking a bite out of that chick’s neck outside the medical tent from the 2:00 trailer? I don’t want an Aliens-style crawlspace suspense terror-fest — I want a Godzilla-style smash-the-buildings monster movie.
  6. Is anything more cliché than “I’m going into the city, I don’t care about the 100 story-tall freakazoid, but she’s there and I have to save her?” Stupid romantic subplot detracts from awesome Statue of Liberty-munchin’.

I guess I’m just being pre-irritated by all the hype. I could be wrong; I hope I’m wrong, but I doubt it.

R.I.P., Pushing Daisies (Prehumously)

Saturday, October 13th, 2007

Hmmm… a show that is funny, yet dramatic, creatively visual, and has a quirky premise. How many episodes is Pushing Daisies going to last? Four? Seven? Probably, the network execs (ooooh… those vilifiable executives!) will decide that the show’s budget is too high for the ratings it gets, and will push it to… I dunno… Thursdays at 3 a.m.? Or they could kill it outright by moving it to the Friday night death slot.

And then, of course, the inevitable articles lamenting its death, and possibly pointing to the fan outcry as a possibly means of resurrection. Fifty bonus points to each journalist who ‘creatively’ suggests that maybe the should could make a comeback if only it could use the main character’s power on itself!

Or, they could let a show thrive. I’m not brilliant network executive, with private jets and 3-martini lunches, so I can’t interpret the show’s ratings. Maybe it’s doing spectacularly? It would be a sin to kill a show that started so strong, and has so much room to grow.

It really makes you question the nature of death. Can there be a God when a vile, wretched show like Desperate Hosewives will live, probably forever, sucking the blood of the innocent and sinless shows in its wake, while something as cute as Pushing Daisies is almost certain to kick the bucket.

“She Looks Like” by Ten Foot Pole

Monday, July 2nd, 2007

… is currently what I believe to be the Best Song EverTM. Excerpt:

And I bet she likes dogs and would never hurt a creature
She’d snowboard so high that I almost couldn’t reach her
She’d never tell a lie and she’d leave her friends to be with me

Mark Knopfler Mondegreen

Friday, June 29th, 2007

A mondegreen is a misheard phrase; the canonical example is probably “‘Scuse me while I kiss this guy”, a mishearing of “‘Scuse me while I kiss the sky” from Jimi Hendrix’s “Purple Haze.”

Anyway, my boss Jess thought that in the Mark Knopfler song “Hill Farmer’s Blues” (from The Ragpicker’s Dream), the narrator proclaims “I’m goin’ into town, LOL.” The actual lyric, apparently, is “I’m goin’ into Tow law.” But I think the mondegreen is better.