Posts Tagged software
Version 2.0.1 of my iOS app NastyWriter has 184 different insults (plus two extra special secret non-insults that appear rarely for people who’ve paid to remove ads 🤫) which it can automatically add before nouns in the text you enter. “But Angela,” I hear you not asking, “you’re so incredibly nice! How could you possibly come up with 184 distinct insults?” and I have to admit, while I’ve been known to rap on occasion, I have not in fact been studying the Art of the Diss — I have a secret source. (This is a bonus joke for people with non-rhotic accents.)
My secret source is the Trump Twitter Archive. Since NastyWriter is all about adding gratuitous insults immediately before nouns, which Twitter user @realdonaldtrump is such a dab hand at, I got almost all of the insults from there. But I couldn’t stand to read it all myself, so I wrote a Mac app to go through all of the tweets and find every word that seemed to be an adjective immediately before a noun. I used NSLinguisticTagger, because the new Natural Language framework did not exist when I first wrote it.
Natural language processing is not 100% accurate, because language is complicated — indeed, the app thought ‘RT’, ‘bit.ly’, and a lot of twitter @usernames (most commonly @ApprenticeNBC) and hashtags were adjectives, and the usernames and hashtags were indeed used as adjectives (usually noun adjuncts) e.g. in ‘@USDOT funding’. One surprising supposed adjective was ‘gsfsgh2kpc’, which was in a shortened URL mentioned 16 times, to a site which Amazon CloudFront blocks access to from my country.
For each purported adjective the app found, I had a look at how it was used before adding it to NastyWriter’s insult collection. Was it really an adjective used before a noun? Was it used as an insult? Was it gratuitous? Were there any other words it was commonly paired with, making a more complex insult such as ‘totally conflicted and discredited’, or ‘frumpy and very dumb’? Was it often in allcaps or otherwise capitalised in a specific way?
But let’s say we don’t care too much about that and just want to know roughly which adjectives he used the most. Can you guess which is the most common adjective found before a noun? I’ll give you a hint: he uses it a lot in other parts of sentences too. Here are the top 35 as of 6 November 2020:
- ‘great’ appears 4402 times
- ‘big’ appears 1351 times
- ‘good’ appears 1105 times
- ‘new’ appears 1034 times
- ‘many’ appears 980 times
- ‘last’ appears 809 times
- ‘best’ appears 724 times
- ‘other’ appears 719 times
- ‘fake’ appears 686 times
- ‘American’ appears 592 times
- ‘real’ appears 510 times
- ‘total’ appears 509 times
- ‘bad’ appears 466 times
- ‘first’ appears 438 times
- ‘next’ appears 407 times
- ‘wonderful’ appears 375 times
- ‘amazing’ appears 354 times
- ‘only’ appears 325 times
- ‘political’ appears 310 times
- ‘beautiful’ appears 298 times
- ‘fantastic’ appears 279 times
- ‘tremendous’ appears 270 times
- ‘massive’ appears 268 times
- ‘illegal’ appears 254 times
- ‘incredible’ appears 254 times
- ‘nice’ appears 251 times
- ‘strong’ appears 250 times
- ‘greatest’ appears 248 times
- ‘true’ appears 247 times
- ‘major’ appears 243 times
- ‘same’ appears 236 times
- ‘terrible’ appears 231 times
- ‘presidential’ appears 221 times
- ‘much’ appears 217 times
- ‘long’ appears 215 times
So as you can see, he doesn’t only insult. The first negative word, ‘fake’, is only the ninth most common, though more common than its antonyms ‘real’ and ‘true’, if they’re taken separately (‘false’ is in 72nd position, with 102 uses before nouns, while ‘genuine’ has only four uses.) And ‘illegal’ only slightly outdoes ‘nice’.
He also talks about American things a lot, which is not surprising given his location. ‘Russian’ comes in 111st place, with 62 uses, so about a tenth as many as ‘American’. As far as country adjectives go, ‘Iranian’ is next with 40 uses before nouns, then ‘Mexican’ with 39, and ‘Chinese’ with 37. ‘Islamic’ has 33. ‘Jewish’ and ‘White’ each have 27 uses as adjectives before nouns, though the latter is almost always describing a house rather than people. The next unequivocally racial (i.e. referring to a group of people rather than a specific region) adjective is ‘Hispanic’, with 25. I’m not an expert on what’s unequivocally racial, but I can tell you that ‘racial’ itself has nine adjectival uses before nouns, and ‘racist’ has three.
“But Angela,” I hear you not asking, “why are you showing us a list of words and numbers? Didn’t you just make an audiovisual word cloud generator a few months ago?” and the answer is, yes, indeed, I did make a word cloud generator that makes visual and audio word clouds, So here is an audiovisual word cloud of all the adjectives found at least twice before nouns in tweets by @realdonaldtrump in The Trump Twitter Archive, with Twitter usernames filtered out even if they are used as adjectives. More common words are larger and louder. Words are panned left or right so they can be more easily distinguished, so this is best heard in stereo.
There are some nouns in there, but they are only counted when used as attributive nouns to modify other nouns, e.g. ‘NATO countries’, or ‘ObamaCare website’.
I came upon a secret stash of free time, so I finally put finishing touches on the Siri Shortcuts I’d added to NastyWriter, made the app work properly in Dark Mode, added the latest gratuitous insults harvested from Twitter (I’ll write another post about how I did that), and released it. Then somebody pointed out something that still didn’t work in Dark Mode, so I fixed that and a few related things, and released it again. Thus NastyWriter’s version number (2.0.1) is the reverse of what it was before (1.0.2.)
I added Siri Shortcuts to NastyWriter soon after iOS 12 came out, just to learn a bit about them. You can add a shortcut with whatever text you’ve entered, and then run the shortcut whenever you like to get a freshly-nastified version of the same text.
There’s also a ‘Give me an insult’ shortcut (which you can find in the Shortcuts app) which just gives a random insult, surrounded by unpleasant emoji.
As I added these soon after iOS 12 came out, they don’t support parameters, which are new in iOS 13. I may work on that next, so you’ll be able to nastify text on the fly, or nastify the output from another shortcut as part of a longer workflow.
Since Tom Lehrer recently released all his music and lyrics into the public domain, I took this opportunity to update the screenshots of NastyWriter in the App Store to show Tom Lehrer’s song ‘She’s My Girl’ where they had previously shown Shakespeare’s Sonnet 18. You can read a full nastification of this on the NastyWriter tumblr.
I released a new version of NastyWriter today! It fixes the various bugs I found while posting nastified text every day on the NastyWriter Tumblr and Twitter, and some that other people kindly told me about. I also added new, all-natural insults sustainably gathered from the wild, and state restoration so you won’t risk losing what you were working on every time you switch to another app. Given how simple that was to implement, I am now even more annoyed at the many better-funded apps that don’t do it.
There are still a few issues that I’m aware of, but I decided the issues I’d already fixed were worse, so it was more important to get the fixes to them out. Anyway, check out the new app on the App Store, or if you like, read more about the bug fixes in this version on my company blog.
There are many important milestones in the life cycle of an iOS app. First beta, first release, hurried second release within hours of the first because something wasn’t set up right in the App Store, first download, first request for a version that runs on some other OS, first review, first angry bug report, first in-app purchase, first cent made from advertising revenue… but all of these pale in comparison to the first song. Because everything’s a song, and if NastyWriter is also a song, then it must be really quite something.
Here is Joey Marianer singing NastyWriter’s version of ‘There Was an Old Lady Who Swallowed a Fly‘:
(Hopefully the video will be embedded above; the WordPress iPad app does not show it in the preview the way its web-based editor does.)
I’ve been publishing nastified versions of reasonably well-known texts daily on the NastyWriter Tumblr and Twitter (I abandoned the Instagram once I found out their app doesn’t work on iPad, but I have since discovered that even though their website doesn’t allow uploading on Mac, it does on iPad, so perhaps I’ll start posting there again.) So far there’s text from Shakespeare, Dickens, The Arrogant Worms, the App Store license agreement, CERN, the US Declaration of Independence, an Apple ad, The Beatles, NastyWriter’s description on the App Store, and of course the nursery rhyme sung above. I intend to keep publishing these daily, so follow the tumblr or Twitter if you don’t want to miss out on any. The Tumblr is open to submissions, so if you’ve made something fun with NastyWriter, please submit it.
I came across a few bugs in NastyWriter while creating these, but my Mac is still at the Apple Store being fixed, so I can’t fix the bugs yet. I hope to fix them in a way that doesn’t involve introducing additional bugs, birds, and assorted mammals. Here’s hoping the 71 unit tests and four or five UI tests help with that.
Also, while waiting for my Mac to come back, I’ve been posting a random rhyme or two every day on the Rhyme Science Twitter feed, so follow that if you want some poetic inspiration. Rhyme Science also has some nearly-finished features and bug fixes I’m looking forward to getting back to once I get my Mac back, although what I should be doing is finding more freelance work and/or a day job so I can afford to pay rent while doing these things. Want me to make something for you? My CV is over on my not-so-businesslike business site.
I’ve been writing Mac software for fun and occasional profit for decades, and freelancing writing an iOS app for use in-house, but don’t you think it’s about time I wrote an iOS app for the App Store?
Surprise! I just released one. It’s called NastyWriter, and it inserts insults before nouns as you type. I see people online who can barely mention people or things they don’t like without insulting them, and I figured I may as well automate that and have some fun with it. It’s always fun to play with natural language processing!
This was mostly an experiment, a learning exercise, and a way to feel better about applying for jobs which have ‘must have app in the App Store’ in the requirements. The experiment is to see how a silly free app with ads and an in-app purchase to turn off ads does, although James Thomson already ran that experiment so I don’t expect it to pay for very many kilos of rice.
The learning exercise was a huge success. I learnt many things, about natural language processing in macOS/iOS, about how many other things there are to think of that take much more effort than the actual adding-insults-before-nouns part, about how awesome automated testing is in a small project by a single person, about how testing accessibility can make flaws in the regular interface more apparent (I didn’t even realise dictation was broken until I tested with VoiceOver!), about the most common adjectives used directly before nouns in the Trump Twitter Archive (‘great’ outnumbers the next most common by about a factor of three), about fastlane, and about the App Store, AdMob and in-app purchases. I might write blog posts about those things later. Do any of these topics seem particular interesting to you?
However, hours after I submitted it, the ‘e’ key on my MacBook’s keyboard stopped working, and while it’s not one of those new butterfly switch keyboards that can apparently need replacing after seeing a speck of dust (or maybe it is? It’s a 2014 model), somehow it turns out that in addition to that my Mac’s battery is swollen and it’ll have to go to the Apple Store and have the battery and the whole keyboard part of the case replaced. This will make it rather difficult to tend to any serious issues in NastyWriter or write as much about it as I wanted to just yet. I can use my iPad (which I am currently typing this on) or, until the Mac goes into the shop, an external keyboard, but neither is quite as comfortable.
And since many people have asked: no, there is no Android version yet, but I’m freelancing and I like learning new things so I would be happy to write one iff somebody pays me to. It would be cheaper for you to buy an iOS device.
I might make a Mac version for fun, though!
I watched a speech by by Haben Girma yesterday, and as she was talking about making things accessible to people with disabilities and how that can lead to usefulness and innovations beyond accessibility, I decided to write a quick parody of James Blunt’s ‘Beautiful’ about accessibility. Here are the lyrics. They don’t always match the original tune exactly, but rather an approximation of it I have in my head from listening to parodies such as The Amateur Transplants’ Beautiful Song, Weird Al’s You’re Pitiful, and James Blunt’s own My Triangle. Feel free to come up with your own additions to include other aspects of accessibility or other things which could be more accessible.
My widget’s brilliant
My venue’s brilliant
Of that I’m sure
For all the people
I don’t ignore
I met someone who was different
And I knew I’d undershot
‘Cause I thought my plans were brilliant
and they were not
Accessible to all
To learn or say, in a different way
When one sense is essential
It makes sense to overhaul
So I fixed my stuff
It was not enough
I met more folk who tried and they still
found it tough
And I don’t think I can accommodate
But I have a goal now and I will innovate
Accessible to all
To simply manoeuvre, no matter how we move
Paralysed or pained or small
Still our movement shall not fall
la la la la…
Accessible to all
And the gains are shared with the unimpaired
Till there’s nothing that seems impossible
If you see, hear, feel the call
Make some tools; tear down a wall.
Of course, I can’t publish lyrics to a song about accessibility without mentioning The Accessibility Song by James Dempsey. If you didn’t like mine, try his, now also available along with his other songs about Cocoa development on iTunes:
I’ve actually seen the original song ‘Beautiful’ performed live, since I randomly went to a James Blunt concert with some co-workers the very first time I was in Vienna. However, even then, I did not really listen to the words. I did while writing this, and realised just how weird and creepy it is. The protagonist is not telling his partner she’s beautiful, as a casual listener might assume, but rather singing to a woman he caught a glimpse of once on a train as if she were some great lost love, despite the fact that they never spoke to each other and she was already involved with someone. It’s essentially Jackson Park Express, presented as a romantic short film rather than a feature-length comedy. With songs like this out there, no wonder random guys on the street sometimes think they can follow me home!
Unrelated to all this, Joey Marianer has once again sung some words I wrote! This time it’s A Few Things You’ll Need for the Cruise, slightly changed to be about the fact that there was, at the time of publishing, exactly one month until JoCo Cruise 2018. There is now less than a month, but still room for you to join us!
I’ve made a new version of Haiku Detector. The main changes are:
- Performance improvements
- Tweaks to which haiku are identified when punctuation is pronounced differently depending on line breaks and other factors (this includes a workaround for the ‘all numbers pronounced as zero’ bug I found in the speech synthesiser.) In my test data the list of haiku identified is better now.
- Bug fixes.
To celebrate the new release, I fed in the text from the latest New Scientist ‘Collection’ issue, on medical frontiers. The funniest haiku arose when the last sentence of one article joined up with the headline and byline of the next. For example, this looks like the tagline of a movie about an underappreciated superhero, fighting to save anti-vaxxers from diseases of yore:
They will not thank you.
Dan Jones FIGHTING INFECTION
Small shot, big impact
After the opening credits, we see our hero Dan Jones in his lab, and the subtitle announcing his first challenge.
SOURCE: Deathstalker scorpion
His superpowers come, of course, from vaccines:
Some vaccines seem to
provide us with a host of
But not everybody is happy with that:
Several groups have been
trying to develop drugs
that block these signals.
These groups spread propaganda:
Half an hour or
so later, you’ll feel a lot
better. Or will you?
They work around rules:
“Because we use cells,
not field-grown plants, we don’t come
under the same rules.”
And they target humanity by zapping the very microorganisms they’re made up of. Here’s a quote from the evil mastermind:
There are more cells in
your body than there are stars
in the galaxy.
These cells can then be
killed using a laser that
penetrates the skin.
And just when Dan thought he had the solution, the problems compounded to the point of suspension of disbelief, precipitating a crisis. The mastermind had cooked up her own microbial minions:
Those microbes can be
in the environment or
a vaccine syringe.
To make matters worse,
there is a shortage of new
The sequel, which may or may not be a Doctor Who crossover, features a heroine who will live forever:
“Just endless.” Helen
Let’s get physical
Yep, it’s definitely a Doctor Who crossover. Here’s a quote from that movie:
“I’m the doctor. I’m
going to tell you what your
feelings really mean.”
She discovered that time, and specifically time travel, is the best cure for a broken heart:
If we can’t fix hearts
with stem cells there might be an
even better way
As the animal
was slowly warmed, it began
to return to life.
But however clever the TARDIS is, there’s one thing Helen Thomson isn’t sure she can do:
But can we ever
turn the clock back to a world
It turned out, weirdly enough, that the answer was in making sure there was enough shelf space for one’s awards. So she went home to Britain to save the Officers of the British Empire:
On her return home,
she applied those lessons in
So far, two patients
have had OBEs, but neither in
a room with a shelf…
While we’re making sequels, let’s revive an old favourite, which never had any sequels:
The matrix holds a
dazzling array of future
But what is the matrix?
is harvested from human
or pig cadavers.
I guess you have to see it for yourself.
I subjected Haiku Detector to some serious stress-testing with a 29MB text file (that’s 671481 sentences, containing 16810 haiku, of which some are intentional) a few days ago, and kept finding more things that needed fixing or could do with improvement. A few days in a nerdsniped daze later, I have a new version, and some interesting tidbits about the way Mac speech synthesis pronounces things. Here’s some of what I did:
- Tweaked the user interface a bit, partly to improve responsiveness after 10000 or so haiku have been found.
- Made the list of haiku stay scrolled to the bottom so you can see the new ones as they’re found.
- Added a progress bar instead of the spinner that was there before.
- Fixed a memory issue.
- Changed a setting so it should work in Mac OS X 10.6, as I said here it would, but I didn’t have a 10.6 system to test it on, and it turns out it does not run on one. I think 10.7 (Lion) is the lowest version it will run on.
- Added some example text on startup so that it’s easier to know what to do.
- Made it a Developer ID signed application, because now that I have a bit more time to do Mac development (since I don’t have a day job; would you like to hire me?), it was worth signing up to the paid Mac Developer Program again. Once I get an icon for Haiku Detector, I’ll put it on the app store.
- Fixed a few bugs and made a few other changes relating to how syllables are counted, which lines certain punctuation goes on, and which things are counted as haiku.
That last item is more difficult than you’d think, because the Mac speech synthesis engine (which I use to count syllables for Haiku Detector) is very clever, and pronounces words differently depending on context and punctuation. Going through words until the right number of syllables for a given line of the haiku are reached can produce different results depending on which punctuation you keep, and a sentence or group of sentences which is pronounced with 17 syllables as a whole might not have words in it which add up to 17 syllables, or it might, but only if you keep a given punctuation mark at the start of one line or the end of the previous. There are therefore many cases where the speech synthesis says the syllable count of each line is wrong but the sum of the words is correct, or vice versa, and I had to make some decisions on which of those to keep. I’ve made better decisions in this version than the last one, but I may well change things in the next version if it gives better results.
Here are some interesting examples of words which are pronounced differently depending on punctuation or context:
|ooohh||Pronounced with one syllable, as you would expect|
|ooohh.||Pronounced with one syllable, as you would expect|
|ooohh..||Spelled out (Oh oh oh aitch aitch)|
|ooohh…||Pronounced with one syllable, as you would expect|
|H H||Pronounced aitch aitch|
|H H H||Pronounced aitch aitch aitch|
|H H H H H H H H||Pronounced aitch aitch aitch|
|Da-da-de-de-da||Pronounced with five syllables, roughly as you would expect|
|Da-da-de-de-da-||Pronounced dee-ay-dash-di-dash-di-dash-di-dash-di-dash. The dashes are pronounced for anything with hyphens in it that also ends in a hyphen, despite the fact that when splitting Da-da-de-de-da-de-da-de-da-de-da-de-da-da-de-da-da into a haiku, it’s correct punctuation to leave the hyphen at the end of the line:
Though in a different context, where – is a minus sign, and meant to be pronounced, it might need to go at the start of the next line. Greater-than and less-than signs have the same ambiguity, as they are not pronounced when they surround a single word as in an html tag, but are if they are unmatched or surround multiple words separated by spaces. Incidentally, surrounding da-da in angle brackets causes the dash to be pronounced where it otherwise wouldn’t be.
|U.S or u.s||Pronounced you dot es (this way, domain names such as angelastic.com are pronounced correctly.)|
|U.S. or u.s.||Pronounced you es|
|US||Pronounced you es, unless in a capitalised sentence such as ‘TAKE US AWAY’, where it’s pronounced ‘us’|
I also discovered what I’m pretty sure is a bug, and I’ve reported it to Apple. If two carriage returns (not newlines) are followed by any integer, then a dot, then a space, the number is pronounced ‘zero’ no matter what it is. You can try it with this file; download the file, open it in TextEdit, select the entire text of the file, then go to the Edit menu, Speech submenu, and choose ‘Start Speaking’. Quite a few haiku were missed or spuriously found due to that bug, but I happened to find it when trimming out harmless whitespace.
Apart from that bug, it’s all very clever. Note how even without the correct punctuation, it pronounces the ‘dr’s and ‘st’s in this sentence correctly:
the dr who lives on rodeo dr who is better than the dr I met on the st john’s st turnpike
However, it pronounces the second ‘st’ as ‘saint’ in the following:
the dr who lives on rodeo dr who is better than the dr I met in the st john’s st john
This is not just because it knows there is a saint called John; strangely enough, it also gets this one wrong:
the dr who lives on rodeo dr who is better than the dr I met in the st john’s st park
I could play with this all day, or all night, and indeed I have for the last couple of days, but now it’s your turn. Download the new Haiku Detector and paste your favourite novels, theses, holy texts or discussion threads into it.
If you don’t have a Mac, you’ll have to make do with a few more haiku from the New Scientist special issue on the brain which I mentioned in the last post:
Being a baby
is like paying attention
with most of our brain.
But that doesn’t mean
there isn’t a sex difference
in the brain,” he says.
They may even be
a different kind of cell that
just looks similar.
It is easy to
see how the mind and the brain
We like to think of
ourselves as rational and
It didn’t seem to
matter that the content of
these dreams was obtuse.
I’d like to thank the people of the xkcd Time discussion thread for writing so much in so many strange ways, and especially Sciscitor for exporting the entire thread as text. It was the test data set that kept on giving.
On Monday I posted a quick-and-dirty Haiku Detector Mac application I’d written which finds haiku (in terms of syllable counts and line breaks, not aesthetics) in any given text. Since then I’ve made it less dirty and maybe more quick. It now shows progress when it’s busy looking for haiku in a long text, and gives you a count of the sentences it looked at and the haiku it found. You can also copy all the haiku (Copy All Haiku in the Edit menu) or save them to a file (Save in the File menu.) Here’s where you can download the new version, which should still work on Mac OS X 10.6 and later. And here are a few more haiku I’ve found with it.
There’s only one (not counting a by-line) in the feature articles of the April 27 edition of New Scientist:
Inside a cosy
new gut the eggs hatch and the
From Flatland: a romance of many dimensions, by Edwin Abbott Abbott:
On the reply to
this question I am ready
to stake everything.
“I come,” said he, “to
proclaim that there is a land
of Three Dimensions.”
Man, woman, child, thing—
each as a Point to the eye
of a Linelander.
This was the Climax,
the Paradise, of my strange
Here are a few more from Flatland which I’m editing this post to add, since I liked them more on the second reading:
Let us begin by
casting back a glance at the
region whence you came.
Therefore, pray have done
with this trifling, and let us
return to business.
Even if I were
a baby, I could not be
so absurd as that.
From Last Chance to See, by Douglas Adams and Mark Carwardine, which I somehow ended up with a text file of many years ago and eventually got a book of:
I’ve been here for five
days and I’m still waiting for
something to go right.
We each went off to
our respective rooms and sat
in our separate heaps.
They’re nocturnal birds
and therefore very hard to
find during the day.
It looked like a great
horn-plated tin opener
welded to its face.
We keep searching for
more females, but we doubt if
there are any more.
The very laws of
physics are telling you how
far you are from home.
Foreigners are not
allowed to drive in China,
and you can see why.
`Just the one left,’ she
said, putting it down on the
ground in front of her.
Yet it was hunted
to extinction in little
more than fifty years.
is very much in tune with
our own survival.
And here’s my own haiku about a particularly amusing passage in that book:
Here Douglas Adams
trudges through his anagram:
Sago mud salad.
Charles Darwin’s most popular work, The Formation of Vegetable Mould Through the Action of Worms with Observations on their Habits, only contained 12 mostly-lacklustre haiku, but I like to think this one is a metaphor:
Worms do not always
eject their castings on the
surface of the ground.
Something about lack of worm castings being only skin-deep.
But most of these don’t mention nature or seasons, as haiku should. So here are some from Sylva, or A Discourse of Forest Trees:
Dieu, and thence rode to
Blois and on to Tours, where he
stayed till the autumn.
How graphic, and how
refreshing, is the pithy
point thus neatly scored—
Meteorology, or Weather Explained, by J.G. M’Pherson contains some very poetic-sounding unintentional haiku:
“It’ll pe aither
ferry wat, or mohr rain”—a
“Beware of rain” when
the sheep are restive, rubbing
themselves on tree stumps.
The brilliant flame, as
well as the smoky flame, is
Till ten o’clock the
sun was not seen, and there was
no blue in the sky.
But, strange to say, there
is a healing virtue in
breathing different air.
There is much pleasure
in verifying such an
Unfortunately, there are no haiku in Dijkstra’s ‘Go To Statement Considered Harmful‘.
The app still uses a lot of memory if you process a novel or two, and may have trouble saving files in that case; It looks like it’s a bug in the speech synthesis library (or my use of it) or simply a caching strategy that doesn’t work well when the library is used in this rather unusual and intensive way. Anyway, if you ever try to save a file and the Save dialog doesn’t appear, try copying instead, and relaunch the program.
Next I think I’ll experiment with finding the best haiku based on the parts of speech at the ends of lines. But first, I’d better start working on the thing I’ve plan to do for the six of hearts.
If you’ve found any nice unintentional haiku, or if you can’t run Haiku Detector yourself but have ideas for freely-available texts it could be run on, let me know in the comments.
A few weeks ago, a friend linked to Times Haiku, a website listing unintentional haiku found in The New York Times, saying ‘I’d actually pay for a script that could check for Haiku in my writings. That would make prose-production a lot more exciting! Who’s up to the script-writing-challenge?’
I knew I could do it, having written syllable-counting code for my robot choir (which I really need to create an explanation page about.) I told her I’d make it that weekend. That was last weekend, when I decided at the last moment to write an article about neutron stars and ISOLTRAP, and then chickened out of that and wrote a poem about it. So I put off the haiku program until yesterday. It was fairly quick to write, so here it is: Haiku Detector. It should work on Mac OS X 10.6 and above. Just paste or type text into the top part of the window, and any detected haiku will appear in the bottom part.
Haiku Detector looks for sentences with seventeen syllables, and then goes through the individual words and checks whether the sentence can be split after the fifth and twelfth syllables without breaking a word in half. Then it double-checks the last line still has five syllables, because sometimes the punctuation between words is pronounced. The Times Haiku-finding program has a database of syllable counts per word, but I didn’t need that since I can use the Mac OS X speech synthesis API to count the syllables. Haiku Detector makes no attempt to check for kigo (season words.)
The first place I looked for haiku was the Wikipedia page for Haiku in English. Due to the punctuation, it didn’t actually find any of the example haiku on the page, but it did find this:
Robert Spiess (Red Moon
Anthology, Red Moon Press,
How profound. Next, having declared myself contributing troubadour for New Scientist magazine, I fed this week’s feature articles through it, and found:
A pill that lowers
arousal doesn’t teach shy
people what to do
Meanwhile, there are signs
that the tide is turning in
favour of shyness.
So by 4000
years ago, the stage was set
for the next big step.
This heat makes the air
spin faster, so pulling the
storm towards the city.
Some will be cooler
and less humid — suitable
for outdoor sports, say.
The last ones seem almost seasonal.
I needed to stress-test the app with a large body of text, so I grabbed the first novel of which I had the full text handy: John Scalzi‘s Old Man’s War, which I had on my iPad on my lap to read while my code was compiling. This book has at least one intentional haiku in it, which Haiku Detector detected. Apart from that, some of my favourites are:
I hate that her last
words were “Where the hell did I
put the vanilla.”
As I said, this is
the place where she’s never been
anything but dead.
“I barely know him,
but I know enough to know
he’s an idiot.”
She’d find me again
and drag me to the altar
like she had before.
A gaper was not
long in coming; one swallow
and Susan was in.
They were nowhere to
be found, an absence subtle
and yet substantial.
And it stares at me
like it knows something truly
strange has just happened.
I haven’t got up to that fifth one in the novel yet, but it mentions a swallow, which I understand is (when accompanied by more swallows) a harbinger of Spring or Summer depending on which language you get your idioms from, so there’s the kigo.
Next I figured I should try some scientific papers — the kinds of things with words that the Times haiku finder would not have in its syllable database. You probably can’t check this unless your workplace also provides access to Physics Letters B, but I can assure you that the full text of the ISOLTRAP paper about neutron stars does not contain any detectable haiku. However, the CMS paper announcing the discovery of the boson consistent with the Higgs does:
In the endcaps, each
muon station consists of
six detection planes.
As is usual for CMS papers, the author and institute lists are about as long as the paper itself, and that’s where most of the haiku were too. Here are a few:
LHC Higgs Cross Section
Working Group, in: S.
of California, Davis,
That’s ‘one hundred and two’ in case anyone who doesn’t say it that way was wondering.
And here are some from my own blog. I used the text from a pdf I made of it before the last JoCo Cruise Crazy, so the last few months aren’t represented:
Beds of ground cover
spread so far in front of him
they made him tired.
those who only understand
half of this poem.
I don’t remember
what colour he said it was,
but it was not green.
His eyes do not see
the gruesome manuscript scrawled
over the white wall.
• Lines 1 to 3 have
four syllables each, with stress
on the first and last.
(That’s not how you write a haiku!)
I don’t wear armour
and spikes to threaten you, but
to protect myself.
A single female
to perpetuate the genes
of a thousand men.
Kerblayvit is a
made-up placeholder name, and
a kerblatent cheat.
He wasn’t the first,
but he stepped on the moon soon
after Neil Armstrong.
He just imagined
that in front of him there was
a giant dunnock.
(there are plenty more where that one came from, at the bottom of the page)
She was frustrated
just trying to remember
what the thing was called.
Please don’t consider
this a failing; it is part
of your programming.
While writing this program, I discovered that that the speech API now has an easier way to count syllables, which wasn’t available when I wrote the robot choir. The methods I used to separate the text into sentences and the view I used to display the haiku are also new. Even packaging the app for distribution was different. I don’t get to write Mac software often enough these days.
Yet again, I didn’t even bother to deal out the cards because I already had something to inspire me. In my halfhearted attempt to find a matching card, I came across one about electronics in the service of ALICE, so I ran the latest instalment of Probably Never, by Alice, into it, and got this:
Or well, I have to
put up with getting called a
fake girl all the time.
The jackhole who called
me a “he/she” recognized
that he crossed the line.
If that sounds interesting, subscribe to Probably Never, and I could probably forward you the rest of that episode if you want.
And finally, two unintentional haiku from this very post:
makes no attempt to check for
kigo (season words.)
(there are plenty more
where that one came from, at the
bottom of the page)
Wait; make that three!
And finally, two
from this very post:
Have fun playing with Haiku Detector, and post any interesting haiku you find in the comments. Also, let me know of any bugs or other foibles it has; I wrote it pretty quickly, so it’s bound to have some.
I know what I’m doing for the six of hearts; I’ve planned it for a long time but still haven’t actually started it. It’s musical, so it will probably be terrible; brace yourselves. By the way, I keep forgetting to mention, but They Might Not Be Giants will be published in Offshoots 12. Yay!