Tag: Sonification

Listening to the machines

Clear sound image by Sunrise from Pixabay

In older films computers are sometimes shown doing a calculation while making lots of bleeps and bloops – sounds that indicate ‘something technical is happening’. In reality computers are generally very quiet (you might hear the sound of the fan, that’s just keeping everything cool) and they don’t normally make a peep. But computer scientists have been wondering if some sound added in might help people make sense of what’s going on.

People who use artificial intelligence tools often have no idea what is happening inside (it’s a bit hidden, like a ‘black box’), or even how much they can trust the results they produce. Explainable AI (“XAI”) is the idea that people should have a better understanding of how an AI tool has reached its answer.

Cars that are powered by batteries don’t have a physical engine so don’t make as much noise (other than the sound of the tyres on the road) but car manufacturers have added in artificial ‘engine sounds’ to make it easier for pedestrians and cyclists to know that a car is heading towards them. This is ‘sonification’, adding sounds that aren’t naturally there to make things more audible. Computer scientists have begun to consider whether it might be possible to sonify the way some language generating AI tools process and produce information, to make their inner workings easier for people to interpret. Whether that might be a microwave-style ‘ping’ to let you know when it’s done something, or a tuneful melody to accompany the AI’s processes remains to be seen…

Jo Brodie, Queen Mary University of London

Other added sounds

Can you think of other examples where a sound has been added (sonification) to help people make sense of something?

Examples include these, which are also helpful for visually impaired people

  • ‘This vehicle is turning left / reversing’ warnings from lorries
  • A lift / elevator making a ‘ping’ sound to alert you that it’s arrived
  • At pedestrian crossings the traffic lights might make an audible sound when the little red man goes green.

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Tony Stockman: Sonification

Two different coloured wave patterns superimposed on one anohter on a black background with random dots like a starscape.
Image by Gerd Altmann from Pixabay

Tony Stockman, who was blind from birth, was a Senior Lecturer at QMUL until his retirement. A leading academic in the field of sonification of data, turning data into sound, he eventually became the President of the “International Community for Auditory Display”: the community of researchers working in this area.

Traditionally, we put a lot of effort into finding the best ways to visualise data so that people can easily see the patterns in it. This is an idea that Florence Nightingale, of lady of the lamp fame, pioneered with Crimean War data about why soldiers were dying. Data visualisation is considered so important it is taught in primary schools where we all learn about pie charts and histograms and the like. You can make a career out of data visualisation, working in the media creating visualisations for news programmes and newspapers, for example, and finding a good visualisation is massively important working as a researcher to help people understand your results. In Big Data a good visualisation can help you gain new insights into what is really happening in your data. Those who can come up with good visualisations can become stars, because they can make such a difference (like Florence Nightingale, in fact)

Many people of course, Tony included cannot see, or are partially sighted, so visualisation is not much help! Tony therefore worked on sonifying data instead, exploring how you can map data onto sounds rather than imagery in a way that does the same thing.: makes the patterns obvious and understandable.

His work in this area started with his PhD where he was exploring how breathing affects changes in heart rate. He first needed a way to both check for noise in the recording and then also a way to present the results so that he could analyse and so understand them. So he invented a simple way to turn data into sound using for example frequencies in the data to be sound frequencies. By listening he could find places in his data where interesting things were happening and then investigate the actual numbers. He did this out of necessity just to make it possible to do research but decades later discovered there was by then a whole research community by then working on uses of and good ways to do sonification,

He went on to explore how sonification could be used to give overviews of data for both sighted and non-sighted people. We are very good at spotting patterns in sound – that is all music is after all – and abnormalities from a pattern in sound can stand out even more than when visualised.

Another area of his sonification research involved developing auditory interfaces, for example to allow people to hear diagrams. One of the most famous, successful data visualisations was the London Tube Map designed by Harry Beck who is now famous as a result because of the way that it made the tube map so easy to understand using abstract nodes and lines that ignored distances. Tony’s team explored ways to present similar node and line diagrams, what computer scientist’s call graphs. After all it is all well and good having screen readers to read text but its not a lot of good if all it tells you reading the ALT text that you have the Tube Map in front of you. And this kind of graph is used in all sorts of every day situations but are especially important if you want to get around on public transport.

There is still a lot more to be done before media that involves imagery as well as text is fully accessible, but Tony showed that it is definitely possible to do better, He also showed throughout his career that being blind did not have to hold him back from being an outstanding computer scientists as well as a leading researcher, even if he did have to innovate himself from the start to make it possible.

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This blog is funded by EPSRC on research agreement EP/W033615/1.

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