torsdag den 16. september 2010

Lesson 3


Data Logger

Data was logged from the microphone and plotted in a chart using Excel:

Chart showing noise


Sound Controlled Car

The car moves based on sound meaning that when a noise is made the car switches between the following driving modes:
  • Forward
  • Right
  • Left
  • Stop
This results in a car moving a bit odd. The way the program makes sure that random background noise doesn't result in change of direction is by having a minimum thresshold. Only if the dB level of the sound is above 90 a change will occur. 


Clap Controlled Car

In the last part of the Lesson, we experimented with implementing the SIvan Toledo algorithm for detecting a "clap". He described a clap as a sequence of key characteristics that must be met within a certain timeframe of each other. Specifically a clap is instantiated with a "low-amplitude" sample of below 50, followed by a very-high amplitude sample of at least 85 within 25 ms of the instantiation and followed by a low-sample below 50 within another 250 ms of the high amplitude. In order to filter out noise from potential instantiations of a clap, we used the data collected from the second part to determine a noise level threshold, which we determined to be 30 or below. Using this knowledge, we ignore all samples below this value when listening for a clap instantiation, i.e. to instantiate a clap we listen for a sample between ]30,50]. Because this algorithm is very time sensitive, we maxed out the sampling rate at 3ms interval sampling. One thing we experienced with this alternate way of detecting a clap, is that it is a bit more sensitive to the actual sound of the clap, we needed to clap in a certain way for it to detect it as a clap. It actually seemed more sensitive to snapping your fingers than the common clap, we experienced that our claps needed to be very high pitched, short and loud. We expect that we would have been able to work out the quirks and inaccuracies given more time to tweak the individual thresholds, timeouts etc. But all in all, it seems to be more picky about the exact sound of the clap, but also more resistant against other loud noises.

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