Posts Tagged software

Unintentional Haiku in New Scientist’s Medical Frontiers: The Movie


How else can you stare at an empty canvas and see a work of art?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.

DRUG: Chlorotoxin
SOURCE: Deathstalker scorpion
CONDITION: Cancer

His superpowers come, of course, from vaccines:

Some vaccines seem to
provide us with a host of
extra benefits

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
antibiotics.

The sequel, which may or may not be a Doctor Who crossover, features a heroine who will live forever:

“Just endless.” Helen
Thomson REGENERATION
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
without HIV?

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
British hospitals.

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
possibilities.

But what is the matrix?

Normally, matrix
is harvested from human
or pig cadavers.

I guess you have to see it for yourself.

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Another Haiku Detector Update, and Some Observations on Mac Speech Synthesis


Screenshot of Haiku Detector

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:

Da-da-de-de-da-
de-da-de-da-de-da-de-
da-da-de-da-da

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
became equated.

We like to think of
ourselves as rational and
logical creatures.

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.

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Haiku Detector Update


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
cycle continues.

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
eventful History.

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.

And conservation
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
poor consolation!

“Beware of rain” when
the sheep are restive, rubbing
themselves on tree stumps.

The brilliant flame, as
well as the smoky flame, is
a fog-producer.

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
interesting problem.

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.

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Five of Hearts: Haiku Detector


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,
1996)

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:

[102]
LHC Higgs Cross Section
Working Group, in: S.

University
of California, Davis,
Davis, USA

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.

Apologies to
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:

Haiku Detector
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
unintentional haiku
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!

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Eight of Spades: The Synaesthetist


I’ve mentioned before that I have grapheme-colour synaesthesia. That means that I intuitively associate each letter or number with a colour. The colours have stayed the same throughout my life, as far as I remember, and they are not all the same colours that other grapheme-colour synaesthetes (such as my father and brother) associate with the same letters. I still see text written in whichever colour it’s written in, but in my mind it has other colours too. If I have to remember the number of a bus line, there’s a chance I’ll remember the number that goes with the colour it was written in rather than the correct letter, or I’ll remember the correct letter and look in vain for a bus with a number written in that colour.

Well, I’ve been wondering whether it could work the other way.

  • Could grapheme-colour synaesthetes learn to look at a sequence of colours that correspond to letters in their synaesthesia, and read a word?
  • Could this be used to send code messages that only a single synaesthete can easily read?
  • Could colours be used to help grapheme-colour synaesthetes learn to read a new alphabet, either one constructed for the purposes of secret communication, or a real script they will be able to use for something?
  • What would be the difference in learning time for a grapheme-colour synaesthete using their own colours for the replacement graphemes, a grapheme-colour synaesthete using random colours, and a non-synaesthete?

I know that for me, there are quite a few letters with similar colours, and a few that are black or white, so reading a novel code wouldn’t be infallible, but I suspect I would be able to learn a new alphabet a little more easily or read it more naturally if it were presented in the ‘right’ colours. I wonder whether the reason the Japanese symbol for ‘ka’ seemed so natural and right to me was that it seemed to be the same colour as the letter k.

It occurred to me that, as a programmer and a grapheme-colour synaesthete, I could test these ideas, or at least come up with some tools that scientists working in this area could use to test them. So I wrote a little Mac program called Synaesthetist. You can download it from here. In it, you choose the colours that you associate with different letters (or just make up some if you don’t have grapheme-colour synaesthesia and you want to know what it’s like) and save them to a file.

Then you can type in some text, and you’ll see the text with the letters in the right colours, like so:

But even though this sample is using the ‘right’ colours for the letters, it still looks all wrong to me. When I think of a word, usually the colour of the word is dominated by the first letter. So I added another view with a slider, where you can choose how much the first letter of a word influences the colours of the rest of the letters in the word.

This shows reasonably well what words are like for me, but sometimes the mix of colours doesn’t really resemble either original colour. It occurred to me that an even better representation would be to have the letters in their own colours, but outlined in the colour of the first letter. So I added that:

Okay, so that gives you some idea of what the words look like in my head. And maybe feeding text through this could help me to memorise it. Here’s an rtf file of the lyrics to Mike Phirman‘s song ‘Chicken Monkey Duck‘ in ‘my’ colours, with initial letter outline. I’ll study these and let you know it it helps me to memorise them. To be scientific about it, I really should recruit another synaesthete (who would have different colours from my own, and so might be hindered by my colours) and a non-synaesthete to try it as well, and define exactly how much it should be studied and how to measure success. But I’m writing a blog, not running a study, so if you want to try it, download the file. (I’d love it if somebody did run a study to answer some of my questions, though. I’d add whatever features were necessary to the app.)

But these functions don’t go too far in answering the questions I asked earlier. How about reading a code? Well, I figured I’d be more likely to intuit letters from coloured things if they looked a little bit like letters: squiggles rather than blobs. So first I added a view that simply distorts the letters randomly by an amount that you can control with the slider. I did this fairly quickly, so there are no spaces or word-wrapping yet.

I can’t read it when it gets too distorted, but perhaps it’s easier to read at low-distortion than it would be if the letters were all black. Maybe I’d be able to learn to ‘read’ the distorted squiggles based on colour alone, but I doubt it. This randomly distorts the letters every time you change the distortion amount of change the text, and it doesn’t keep the same form for each occurrence of the same letter. Maybe if it did, I’d be able to learn and read the new graphemes more easily than a non-synaesthete would. Okay, how about just switching to a font that uses a fictional alphabet? Here’s some text in a Klingon font I found:

I know that Klingon is its own language, and you can’t just write English words in Klingon symbols and call it Klingon. But the Futurama alien language fonts I found didn’t work, and Interlac is too hollow to show much colour.

Anyhow, maybe with practice I’ll be able to read that ‘Klingon’ easily. I certainly can’t read it fluently, but even having never looked at a table showing the correspondence between letters and symbols, I can figure out some words if I think about it, even when I copy some random text without looking. I intend to add a button to fetch random text from the web, and hide the plain text version, to allow testing of reading things that the synaesthete has never seen before, but I didn’t have time for that.

Another thing I’ll probably do is add a display of the Japanese kana syllabaries using the consonant colour as the outline and the vowel colour as the fill.

Here’s a screenshot of the whole app:

As I mentioned, you can download it and try it for yourself. It works on Mac OS X 10.7, and maybe earlier versions too. To use it, either open my own colour file (which is included with the download) or create a new document and add some characters and colours in the top left. Then enter some text on the bottom left, and it will appear in all the boxes on the right side. If you change the font in the bottom left, say to a Klingon font, it will change in all the other displays except the distorted one.

This is something I’ve coded fairly hastily on the occasional train trip or weekend, usually forgetting what I was doing between stints, so there are many improvements that could be made, and several features already halfway developed. It could do with an icon and some in-app help, too. I’m still working on this, so if you have any ideas for it, I’m all ears.

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