April Fooling with computing – IP over avian carriers, PigeonRank ^JB

Happy April Fool’s Day everyone, here are a couple of examples of programmers having a little fun.

Winged messengers

In 1990 a joke memo was published for April Fool’s Day which suggested the use of homing pigeons as a form of internet, in which the birds might carry small packets of data. The memo, called ‘IP over Avian Carriers’ (that is, a bird-based internet), was written in a mock-serious tone (you can read it here) but although it was written for fun the idea has actually been used in real life too. Photographers in remote areas with minimal internet signal have used homing pigeons to send their pictures back.

The beautiful (and quite possibly wi-fi ready, with those antennas) Victoria Crowned Pigeon. Not a carrier pigeon admittedly, but much more photogenic. Image by Foto-Rabe from Pixabay

A company in the US which offers adventure holidays including rafting used homing pigeons to return rolls of films (before digital film took over) back to the company’s base. The guides and their guests would take loads of photos while having fun rafting on the river and the birds would speed the photos back to the base, where they could be developed, so that when the adventurous guests arrived later their photos were ready for them.

Further reading

Pigeons keep quirky Poudre River rafting tradition afloat (17 July 2017) Coloradoan.

You might also enjoy this attempt to make broadband work over wet string instead of the more usual wires. They actually managed it! Broadband over ‘wet string’ tested for fun (13 December 2017)

 

Serious fun with pigeons

On April Fool’s Day in 2002 Google ‘admitted’ to its users that the reason their web search results appeared so quickly and were so accurate was because, rather than using automated processes to grab the best result, Google was actually using a bank of pigeons to select the best results. Millions of pigeons viewing web pages and pecking picking the best one for you when you type in your search question. Pretty unlikely, right?

In a rather surprising non-April Fool twist some researchers decided to test out how well pigeons can distinguish different types of information in hospital photographs. They trained pigeons by getting them to view medical pictures of tissue samples taken from healthy people as well as pictures taken from people who were ill. The pigeons had to peck one of two coloured buttons and in doing so learned which pictures were of healthy tissue and which were diseased. If they pecked the correct button they got an extra food reward.

Pigeon, possibly pondering people’s photographs. Image by Davgood Kirshot from Pixabay

The researchers then tested the pigeons with a fresh set of pictures, to see if they could apply their learning to pictures they’d not seen before. Incredibly the pigeons were pretty good at separating the pictures into healthy and unhealthy, with an 80 per cent hit rate.

Further reading

Principle behind Google’s April Fools’ pigeon prank proves more than a joke (27 March 2019) The Conversation.

 

A version of this article was originally published on this blog as part of the CS4FN Christmas Advent Calendar, on 7 December 2021.

Standup Robots

‘How do robots eat pizza?’… ‘One byte at a time’. Computational Humour is real, but it’s not jokes about computers, it’s computers telling their own jokes.

Robot performing
Image from istockphoto

Computers can create art, stories, slogans and even magic tricks. But can computers perform themselves? Can robots invent their own jokes? Can they tell jokes?

Combining Artificial Intelligence, computational linguistics and humour studies (yes you can study how to be funny!) a team of Scottish researchers made an early attempt at computerised standup comedy! They came up with Standup (System to Augment Non Speakers Dialogue Using Puns): a program that generates riddles for kids with language difficulties. Standup has a dictionary and joke-building mechanism, but does not perform, it just creates the jokes. You will have to judge for yourself as to whether the puns are funny. You can download the software from here. What makes a pun funny? It is a about the word having two meanings at exactly the same time in a sentence. It is also about generating an expectation that you then break: a key idea about what is at the core of creativity too.

A research team at Virginia Tech in the US created a system that started to learn about funny pictures. Having defined a ‘funniness score’ they created a computational model for humorous scenes, and trained it to predict funniness, perhaps with an eye to spotting pics for social media posting, or not.

But are there funny robots out there? Yes! RoboThespian programmed by researchers at Queen Mary University of London, and Data, created by researchers at Carnegie Mellon University are both robots programmed to do stand-up comedy. Data has a bank of jokes and responds to audience reaction. His developers don’t actually know what he will do when he performs, as he is learning all the time. At his first public gig, he got the crowd laughing, but his timing was poor. You can see his performance online, in a TED Talk.

RoboThespian did a gig at the London Barbican alongside human comedians. The performance was a live experiment to understand whether the robot could ‘work the audience’ as well as a human comedian. They found that even relatively small changes in the timing of delivery make a big difference to audience response.

What have these all got in common? Artificial Intelligence, machine learning and studies to understand what humour actually is, are being combined to make something that is funny. Comedy is perhaps the pinnacle of creativity. It’s certainly not easy for a human to write even one joke, so think how hard it is distill that skill into algorithms and train a computer to create loads of them.

You have to laugh!

Watch RoboThespian [EXTERNAL]

– Jane Waite, Queen Mary University of London, Summer 2017

Download Issue 22 of the cs4fn magazine “Creative Computing” here

Lots more computing jokes on our Teaching London Computing site

Studying Comedy with Computers

by Vanessa Pope, Queen Mary University of London

Smart speakers like Alexa might know a joke or two, but machines aren’t very good at sounding funny yet. Comedians, on the other hand, are experts at sounding both funny and exciting,  even when they’ve told the same joke hundreds of times. Maybe speech technology could learn a thing or two from comedians… that is what my research is about.

Image by Rob Slaven from Pixabay 

To test a joke, stand-up comedians tell it to lots of different audiences and see how they react. If no-one laughs, they might change the words of the joke or the way they tell it. If we can learn how they make their adjustments, maybe technology can borrow their tricks. How much do comedians change as they write a new show? Does a comedian say the same joke the same way at every performance? The first step is to find out.

The first step is to record lots of the same live show of a comedian and find the parts that match from one show to the next. It was much faster to write a program to find the same jokes in different shows than finding them all myself. My code goes through all the words and sounds a comedian said in one live show and looks for matching chunks in their other shows. Words need to be in the same exact order to be a match: “Why did the chicken cross the road” is very different to “Why did the road cross the chicken”! The process of looking through a sequence to find a match is called “subsequence matching,” because you’re looking through one sequence (the whole set of words and sounds in a show) for a smaller sequence (the “sub” in “subsequence”). If a subsequence (little sequence) is found in lots of shows, it means the comedian says that joke the same way at every show. Subsequence matching is a brand new way to study comedy and other types of speech that are repeated, like school lessons or a favourite campfire story.

By comparing how comedians told the same jokes in lots of different shows, I found patterns in the way they told them. Although comedy can sound very improvised, a big chunk of comedians’ speech (around 40%) was exactly the same in different shows. Sounds like “ummm” and “errr” might seem like mistakes but these hesitation sounds were part of some matches, so we know that they weren’t actually mistakes. Maybe “umm”s help comedians sound like they’re making up their jokes on the spot.

Varying how long pauses are could be an important part of making speech sound lively, too. A comedian told a joke more slowly and evenly when they were recorded on their own than when they had an audience. Comedians work very hard to prepare their jokes so they are funny to lots of different people. Computers might, therefore, be able to borrow the way comedians test their jokes and change them. For example, one comedian kept only five of their original jokes in their final show! New jokes were added little by little around the old jokes, rather than being added in big chunks.

If you want to run an experiment at home, try recording yourself telling the same joke to a few different people. How much practice did you need before you could say the joke all at once? What did you change, including little sounds like “umm”? What didn’t you change? How did the person you were telling the joke to, change how you told it?

There’s lots more to learn from comedians and actors, like whether they change their voice and movement to keep different people’s attention. This research is the first to use computers to study how performers repeat and adjust what they say, but hopefully just the beginning. 

Now, have you heard the one about the …

For more information about Vanessa’s work visit https://vanessapope.co.uk/ [EXTERNAL]