My "Native American" name

Last year, I did a project extracting semantic data from the BBC's archive catalogue. I presented the results to a senior colleague, who now wants me to present it to some academics who are involved in a collaborative project. The thing that seems to have stuck in his mind about my presentation is that I demonstrated my results with an old wildlife programme about a bird called a Red Tailed Hawk. He therefore described me in an email as

The bloke who can find a nesting Redtail Hawk in 1,000,000 hours of tape and film

. As a result, I was put on the agenda as "Hawkfinder".

I therefore seem to have acquired a Native American name. I'd be interested to hear how it would come out in various conlangs - particularly Native American inspired ones like Jeff Burke's Central Mountain Languages - so leave me a comment with your translation. In Khangaþyagon it would be

ketargslatontrik

ketarg- slat- ont- rik
hawk find PrP man

Also, what would your "Native American name" be, and why?

Oh, It Makes Me Wonder

Gradus ad Parnassum, meaning Steps to Mount Parnassus (in Greek mythology, the home of the Muses), is a famous musical composition textbook from the 18th Century. It taught, in a series of step-by-step lessons, the rules of the musical technique known as counterpoint, where several different melodies are composed to be performed in harmony with each other. Of course, once the student had mastered the rules (it was very technical), they would hopefully be able to work out for themselves where they could get away with breaking them for artistic effect.

Led Zeppelin's most famous song is called Stairway to Heaven. You know the one - starts of gently with 12-string guitars, recorders, and references to Tolkien, and gradually becomes more Hard Rock as it progresses (You can listen to it in Pete's Progcast if you wait long enough for it to come round). The resemblence between the title and that of the Baroque music textbook may seem like a complete coincidence. However, there's a bit near the end that goes

And as we wind on down the road,
Our shadows taller than our souls,
There stands the lady we all know
Who shines white light and wants to show
How everything still turns to gold.
And if you listen very hard
The dream will come to you at last
Where all are one, and one is all,
To be a rock, and not to roll!

If you're singing Stairway to Heaven on a karaoke night, about halfway though this bit you realise that you're really going to need a drink after this. Each line of the passage goes to just about the same tune, but is pitched a little bit higher than the one before. In musical terms, that's called a canon. It's a technique that was frequently in the type of music that Gradus ad Parnassum teaches,

What are the odds of a planet having a large moon?

As Dr. Maggie Alderin-Pocock pointed out in Do We Really Need The Moon?, our Moon is unusually large in comparison to its parent planet, and the large tidal forces it generates are thought to have been very important to the origin of life on Earth. She therefore suggested that when looking for life on other planets, we should concentrate out efforts on other planets that have large moons.

Our Moon, according to the best theories we have, was formed when another planet, the size of Mars, crashed into the early Earth. This, at first, sounds like a spectacularly unlikely event. It may sound quite discouraging if you were hoping to get in touch with aliens. However, models of the early solar system show that it was quite a violent, chaotic place, and space rocks crashing into each other is pretty much how the inner planets were formed. So, is there any way we can calculate the probability of a planet having a large moon like ours?

The best way is to make an empirical estimate, and it turns out to be a lot easier to do than you might have expected, and to have quite encouraging results. There are four rocky planets in the inner solar system. One has a large moon. So the odds of a rocky planet having a large moon, based on the available evidence, is 1/4. (± √3/8)

Do We Really Need The Moon?

I used to be an astronomer (Ph.D from Leicester, studying Active Galactic Nuclei) so I quite enjoyed Do We Really Need The Moon? on BBC 2 last night. The programme explored the effects the Moon has on the Earth, and how those effects have been helpful to the development of life.

I also found the presenter really interesting. If you look at my profile photo, you'll see that I belong to the same demographic group as most people with physical sciences Ph.Ds. Dr Maggie Aderin-Pocock is in the intersection of two groups who are severly underrepresented in the physical sciences. On top of which, she mentioned that she is dyslexic, which is a condition that can limit a person's educational opportunities. Hopefully, people who had thought that they weren't the sort of people who could be a scientist will have seen the programme and realised that maybe they could.

AI is No Longer a Dirty Word

I recently did a search for Artificial Intelligence London, and then looked at the results on a map. By doing so, I discovered a company called Cognitive Match. They're a start-up whose product aims to customise a client's website to match a user's needs on the fly. What particularly caught my attention was the following quote

Our software combines mathematics with psychology and artificial intelligence to give your customers what they want.

It's very unusual to see anyone outside the games industry use the term Artificial Intelligence for something they're actually selling. The reasons for this are largely historical. A few years ago, a lot of people made rather overhyped claims for what AI would be able to do, which didn't match up with what it could actually do at the time. This created the impression that anything that was described as Artificial Intelligence belonged in the lab, and wasn't likely to turn into a usable product in the forseeable future.

There's a gradual change in the perception of AI going on. This is partly because researchers have been taking a more pragmatic approach to AI, and partly because the internet is making large datasets more readily available. Good data is the limiting factor in most AI applications, so, the more data is available, the better AI works.

Coming Soon on Doctor Who

This was shown after the Doctor Who Christmas special. It promises a lot of things to look forward to, including -

• Georgians
• Nazis (bet they'd get on with the Daleks)
• The Doctor says he's "been running, faster than I've ever run. Now it's time for me to stop." ...
• then makes outrageous demands of a lot of armed men.
• Whenever the Doctor says his hat is cool, River Song shoots it.
• "We've been recruited." "Recruited by who?"
• The interior of a ship like the one from The Lodger. Bet that's something to do with The Silence.
• Sinister figure in a spacesuit. Are the Vashta Nerada back?
• River Song (apparently) nude. That'll bump up my search ratings... (as the actress said to the bishop).
• The Ood
• Sinister dolls
• That writing on Amy's face reminds me of something.
• "My life in your hands, Amelia Pond."
• "One thing I can tell you... Monsters are real" Is that a Grey that's got Rory cornered?

Looking forward to it!

Creating a langauge with clustering algorithms

I recently posted this at the Conlang Mailing List, but I thought it was worth putting up here.

Define a phonology for a language. Make sure you know what all its
distinctive features are.

Generate a very large set of wordforms for the language using an
automatic vocabulary generator.

Calculate the difference between each pair of wordforms in the
vocabulary, using a modified version of the Levenshtein Distance, where
the cost of an insertion or deletion is the total number of distinctive
features in the language's phonology, and the cost of a substitution is
the number of features that differ between the substituted phonemes.

Cluster the wordforms so that each wordform belongs to the same cluster
as its nearest neighbour.

Explore the clusters, assigning related meanings to related wordforms.
Make notes of how changes of form relate to changes of meaning, so that
they can be reapplied later - if the software is clever enough, once
you've annotated a process that applies to two wordforms, it can search
the dataset for other pairs of wordforms where the same process may be
occurring.

This could be a good way of generating non-concatenative morphologies,
and simulating the effects of analogy on language development.

What do people think? Anyone like to have a go at implementing it?