Cooperative tapping experiments – first impressions

Roland-Sennheiser in sync

This week I’ve been running an experiment I first ran in 2006, collecting more data to see if some of the effects would actually reach statistical significance with more data, or would the inklings of trends be shown to be just flukes.

I’ll write more about the results of this experiment later, I just wanted to share some of my first impressions. These first impressions are mainly based on post-experiment conversations with participants, and in my opinion are important not only when interpreting the results, but also when trying to tie the experiment into its wider contexts. I feel that I learn at least as much about the phenomenon by talking to people after they’ve performed my experiment as I learn by looking through their data. Data is needed to find evidence for or against a hypothesis, but learning about the stuff you’re working with is a more all-encompassing process.

Just to briefly explain the setting. There are two participants, each finger tapping with a MIDI drum. A simple task would be to tap along a metronome (experimenter’s computer), as accurately as possible (synchronisation), and then continue tapping after the metronome stops (continuation). If both participants can hear themselves and each other, we’ve got actual interaction in the auditory domain, a simulation of a genuine music-making situation, but simplified so that it can be controlled and that “everyone” can perform the tasks.

cooptap2

Cooperative tapping setting - experimenter in the middle, drums in the corner are not part of this.🙂

This synchronisation-continuation task is a classic (it’s been used for studying timing at least since Stevens 1886, but normally with individual tappers), and can be modified in many ways, depending on what the research question is. One can tweak the metronome (introduce “errors” and see how people cope), add delays between taps and their “feedback” etc. My cooperative tapping setting of course allows us to investigate a number of variables linked to interaction, rather than just the timing or synchronisation itself.

In this study, I’m looking at how communication effects synchronisation accuracy. I’m basically comparing two situations: tapping with another person, and tapping with a computer. The essential difference here is that the person will respond to what you do, and will cooperate with you to maintain synchrony, whereas the computer will do whatever it was programmed to do regardless of your actions. But, as I said, results and details later, now to the things already learned.🙂

First, disrupting communication channels leads to frustration. I know, it’s a bit evil scientist -like to first ask people to collaborate and then break down their communication so that they can’t. But the strong feeling of frustration that arises from the breakdown of synchrony is still interesting. One of the participants told his tapping partner (jokingly) that he’s never going to play in his band again… (and this is another reason why debriefing is so important.🙂 )

The other side of this coin is of course, that synchronisation leads to affiliation and feeling good. It’s not just about being synchronous, it’s about the feeling of being entrained and keeping it that way together. Lots of socially significant information in that deceptively simple signal. In this experiment, for instance, the timbre, loudness and pitch were all held constant. So it’s really only the timing of those taps that matter, that’s all that is needed to communicate relatively complex intentions.

Two separate mixes were created, so that what each tapper heard could be controlled individually.

Two separate mixes were created, so that what each tapper heard could be controlled individually.

Third thing I’ve learned is that people trust humans more than they trust computers. Most people said they knew they were tapping with a computer “because no human would be that bad, would make “those kinds of mistakes””. Or at least, not the person they were tapping with. This is interesting, and I need to device a proper experiment to look at this issue. In a previous study, it transpired that many of these “too bad to be a human” -tappers were in fact actually humans, but they were made non-responsive by a manipulation of audio channels. Also in this experiment, I heard some pretty bad human tapping, but my participants were very confident that they knew only computers would make certain kinds of mistakes.

This leads to the final thing I’ve learned before I go and look at the data. Non-musicians and those with very little experience tend to speed up. They do pick the beat from the metronome, but once it fades out, it’s tempo mayhem. Pair two of these speedsters together, and you got yourself a race.

This became a longer post than intended, but it’s now time to get to the data. I’ll let you know what, if anything, I find.

One thought on “Cooperative tapping experiments – first impressions

  1. When I played in a band and we would be preparing for a recording, one problem would be to vary the tempi of our songs. Some attempts were made to speed up some songs and slow down others, but it seems we would always revert back to the mean by then end of the song.

    We weren’t speedsters, we just had a tempo that everyone was most comfortable playing, whichever the song.

    This was eventually solved with intense practice with a very loud metronome in the drummer’s head set.

    But at first, this technique was a lot like pulling teeth. And in our shows, I wouldn’t be surprised if 80% of the set was in the same tempo.

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