Title: Volcano seismograms sonification application
1Volcano seismograms sonification application
- Domenico Vicinanza, CERN
- EELA Conference, Santiago, September 04-05, 2006
2Volcano eruption forecasting
- Currently no definitive method to predict the
eruption of a volcano has been discovered or
implemented (yet). - Scientists monitor
- seismic waves
- number of earthquakes and the intensity of a
specific type of quake (harmonic tremors) in the
run up to eruptions. - changes in the shape of the volcano or
concentrations of gases emitted from the cone.
3The hope music for forecasting
- By correlating spectra and melodies with precise
stages of volcanic activity we hope to discover a
sort of signature tune of an imminent eruption
or earthquake. - By identifying musical patterns that warn of an
eruption it would be possible to implement civil
protection measures, days or even hours before
the event
4Data Audification
- Data audification can be considered as the
acoustic counterpart of data graphic
visualization, a mathematical mapping of
information from data sets to sounds. - Data audification is currently used in several
fields, for different purposes - science and engineering,
- education and training,
- mainly as data analysis and interpretation tool.
-
- Although most data analysis techniques are
exclusively visual in nature, data presentation
and exploration systems could benefit greatly
from the addition of sonification capabilities.
5Motivations
- Sonic representations are particularly useful
when dealing with complex, high-dimensional
data, or in data monitoring tasks where it is
practically impossible to use the visual
inspection, or for pattern detection. - Research has shown that people are quite more
confident in recognizing patterns audibly rather
then visually - Music theorists and researchers have carried out
in centuries of history lots of techniques and
methods to detect, study and classify musical
phrases - Main idea Music as a language and music
analysis as a tool to inspect scientific data
6Advantages of hearing
- Hearing is non-directional
- It is surely easier to recognize a change in a
sound with respect to a modification in something
which has to be looked at. - It is quite impossible to distinguish a blinking
light flashing 100 times a second from another
one flashing at 200, 1000, or 10000 times a
second, while anyone can recognize periodic
signals from 20 Hz to (almost) 20000 Hz
7Sonification on the GRID network
- First experiments involving sound production with
INFN-GRID facilities started during the last
months of 2003. - In September 2003, it was installed CSound, a
free and cross-platform acoustic compiler, on a
GRID test site, the Catania INFN-GRID computer
farm - The compiler was tested within the new
environment and since its beginning, the test
phase produced interesting results efficient use
of the calculus resources, customizable quality
of the audio files.
8First Phase CSound
- After a four-five months test phase, CSound has
been distributed to other GRID farms in Europe, - Data sonification, sound synthesis and
algorithmic composition have been investigated
using couple of Csound files and Python (or
sometimes Perl) scripts. - Python scripts have been used to prepare the
right data files during the tests.
9Second Phase Java
- Second test phase development of a sound
production suite based on Java (equipped with the
standard audio and math libraries), more flexible
and easy to manage. - All the results presented in this website have
been carried on using this last approach sample
computation, audio rendering, DFT computing were
obtained with the Java sonification program on
the GRID - Executable "/bin/sh" StdOutput
"sonification.out" StdError
"sonification.err" InputSandbox
"sonification.sh", "Sonification.java",
"etna.dat" OutputSandbox "Sonification.aiff"
, "Sound.dat","Spectrum.dat", "sonification.out","
sonification.err", "logfile" RetryCount 7
Arguments "sonification.sh"
10Sound form volcanoes
- Sonified data were geophysical data collected by
digital seismographs placed on the Etna volcano
in Catania (Italy) and on Tungurahua volcano in
Ecuador. - We carried out two sonifications
- seismogram straight sonification (tranformation
into an audible waveform) - seismogram melodisation (tranformation into a
melody)
Etna Volcano
Tungurahua (Picture M. Monzier IRD/IG-EPN)
11About seismograms audification
- In both the cases, structural properties of the
seismographic information would be straightly
mapped into sound or melody properties - In the first case, regularities in the
seismograms will be reflected by the existence of
spectral lines in the sonified signal - In the second case, regularities in the
seismograms will be transferred into regularities
in the melody (such as a repeated set of data
will become a repeated musical phrase)
12Seismograms sonification
- Seismographic data have been recorded onto the
surface of volcanoes, by digital seismographs at
a sampling frequency of about 100 Hz (100.1603
Hz).
13Original data
- Example of ASCII files processed
- (sample from Etna data)
- Starting time 15/06/2001 000339.920
Frequency 100.1603 Hz Samples 168960 44
43 42 44 44 46 43 45
14First SonificationFrom data to waveform
- Scaling procedure to properly arrange the samples
in the -1,1 interval, according to their
sampling frequency. - Users can specify in the sonification program a
certain resample frequency (pitch shift). - Setting resample factors in the Java code greater
than 1 won't preserve the original pitch,
allowing a frequency shift... - ....making audible regular phenomena happening at
very low frequencies. - In this way it is possible to observe and study
periodical patterns, regular behaviors,
long-range correlations, which can happen at
different time scales.
15Sample and hold and linear interpolation
- It have been implemented two interpolation
methods to generate the waveform - linear interpolation and sample-and-hold (SH)
interpolation. - Linear interpolation returns particularly
"smoother" sounds. - Nevertheless, for some analysis application, it
could be useful to prefer the SH audio file,
where no external values are added to the
original (scaled) data set.
16Creating the waveform Linear interp.
17Creating the waveform Sample Hold
18Quasi-regular phenomena
- The waveform coded in the audio file will have
exactly the same regularities, also recognizable
thanks to the presence of some higher lines in
the spectrum. - The order of magnitude of the frequency of
quasi-regular phenomena is in the range 0-50 Hz,
with a spectral envelope centered around 25-30
Hz.
20x resampled Etna seismogram
19Etna waveform and sonogram
20Tungurahua Waveform
21Tungurahua Spectrum
Spectral lines Regular patterns
22Tungurahua Sonogram
Time evolution of the spectrum. Each vertical
slice is the spectrum at a certain time
Oscillation pattern variations are clearly
visible in the pattern
23Etna sonification within GILDA
https//gilda.ct.infn.it/
https//glite-demo.ct.infn.it/
24http//glite-demo.ct.infn.it
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29Listening to sonification.aiff file
Etna sonogram
30Data melodization
- The whole data set interval is mapped on the
(equally tempered) piano keyboard - The min value of the seismographic data will
correspond to the lowest playable note on the
piano keyboard - The max value to the highest playable note
31Main advantages
- Already available tools to manage MIDI files and
analyze them - Tracking the evolution of the musical intervals,
the dynamics of their patterns, it is possible to
detect, with an high level and in a customizable
way, any kind of modifications in the shape of
seismogram. - Two example of MIDI analysis (free) software
- Rubato (www.rubato.org)
- MIDI Toolbox (http//www.jyu.fi/musica/miditoolbox
/)
32MIDI Toolbox
33Dynamic evolution of the tonalities (related to
couples of adjacent values)
34Example Sinusoidal behavior
- 0.00.5877852522920.9510565162950.9510565162950
.5877852522920.0-0.587785252292-0.951056516295
-0.951056516295-0.5877852522920.00.587785252292
0.9510565162950.9510565162950.5877852522920.0
Graphical representation
Original data
35Sinus melodization
Data are periodic, so the melody is periodic,
with the same period
Music representation (of the same set of data)
36Melodization a pictorial view
- Pictorially we can say that the melodization
works by overlaying seismograms with music notes - To create the volcanic score, we take a
seismogram and trace the shape on to blank music
bars. - Then we overlay the contours with musical notes.
37Seismograms Melodisation
38Seismograms Melodisation
39Seismograms Melodisation
40Seismograms Melodisation
have you ever heard a volcano playing a piano ?
41Melody follows the shape of the oscillation
42First Etna-Tungurahua duet
- Players
- Mt Etna Piano
- Mt Tungurahua Guitar
43Reference sites
- Etna Sonification website http//grid.ct.infn.it/
etnasound - Tungurahua Sonification web repository
http//grid.ct.infn.it/tungurahuasound - MIDI Toolbox manual http//www.jyu.fi/musica/midi
toolbox/MIDI_Toolbox_Manual.pdf
44Thanks! Questions