Helium
materials: Helium tank quiet room Zoom recorders questions: how do we measure the amount of Helium? displace water? lifting power? how do you measure how much went into the lungs? is that important? can you measure the amount of Helium in the lungs by the change in timbre? voices: low and high pitch registers singing pitches whistling steady tone staccato tone singing and speaking words vs sounds instruments woodwind breathing into the instrument sax? flute clarinet speaker in a Helium environment low and high pitch registers singing pitches whistling steady tone staccato tone singing and speaking words vs sounds activity stations recording station sound file preparation record to notebook compare waveforms[[experiments---Helium]]
Experiments / Helium
How Helium changes the sound of your voice
Helium is 7x less dense than air. This accounts for Helium's buoyancy and efficacy in lifting blimps and party balloons. More relevantly, Helium changes the sound of your voice by altering the familiar density of the medium through which the sound travels.
n.b. Helium is non-toxic. However, when you concentrate Helium to produce changes in the quality of your voice you have effectively displaced life-giving air with an Oxygen-free gas. Breathing Helium may lead to unwitting asphyxiation within minutes. Use your judgment!
How is the voice changed in Helium? Let's start by listing the possible changes.
- Loudness, intensity or amplitude
- Fundamental pitch frequency
- Harmonics: overtones, timbre
- duration (faster or slower)
(can you think of any others?)
Timbre seems to be the quality most changed. What is timbre again?
how many overtones are present relative to the fundamental and in what series?
timbre |ˈtambər, ˈtäNbrə| noun the character or quality of a musical sound or voice as distinct from its pitch and intensity: trumpet mutes with different timbres | a voice high in pitch but rich in timbre.
experiment
Speculation: Helium does not change the fundamental frequency of your voice, though it does alter the way that the harmonics are produced and so radically alters the timbre.
falsifiable statement: Helium does not change the fundamental frequency of a voice. The changed timbre will be visible on a spectrogram image.
record different kinds of sounds. List:
- record a voice in air (one note, scale, glissando up, glissando down)
- record a voice in Helium (one note)
- record a pure tone in air (one note)
- record complex tones in air
- record a pure tone produced in Helium (with a loudspeaker)
- record a complex tone produced in Helium (tritone carn horn)
- record a vocal recording
(what else?)
In all cases the fundamental (or lowest) tone will be the same and the harmonics will be changed and we should see those changes on the spectrogram.
materials needed
- Helium source (ballon? Bring two)
- audio source
- small speaker
- audio sources
- audio recorder
- FFT analyzer (Fast Fourier Transform) analysis
teams
- sound production
- singer(s)
- tone wrangler/producers
- sound recordists
- sound preparers
- how will the files be treated?
- Helium wranglers
- file wranglers
- notebook keepers
let's all describe the quality of the results
file storage
put a file listing for a Dropbox folder here write a little file chooser program for the notebook
questions
- do you trust what you see in the spectrogram?
- is the distortion the same for all kinds of sounds?
references
- http://www.animations.physics.unsw.edu.au/jw/speech.html
- http://www.phys.unsw.edu.au/~jw/reprints/A_novel_instrument.pdf
- http://cournape.github.io/audiolab/index.html
- http://vibrationdata.com/python-wiki/index.php?title=Main_Page
- http://jaganadhg.freeflux.net/blog/archive/2009/07/23/how-to-plot-spectrogram-with-python.html
- http://www.kempa.com/2004/05/03/more-musical-steganography/
So what is a spectrogram anyway?
A sound spectrogram (or sonogram) is a visual representation of an acoustic signal. To oversimplify things a fair amount, a Fast Fourier transform is applied to an electronically recorded sound. This analysis essentially separates the frequencies and amplitudes of its component simplex waves. The result can then be displayed visually, with degrees of amplitude (represented light-to-dark, as in white=no energy, black=lots of energy), at various frequencies (usually on the vertical axis) by time (horizontal).
Depending on the size of the Fourier analysis window, different levels of frequency/time resolution are achieved. A long window resolves frequency at the expense of time—the result is a narrow band spectrogram, which reveals individual harmonics (component frequencies), but smears together adjacent 'moments'. If a short analysis window is used, adjacent harmonics are smeared together, but with better time resolution. The result is a wide band spectrogram in which individual pitch periods appear as vertical lines (or striations), with formant structure. Generally, wide band spectrograms are used in spectrogram reading because they give us more information about what's going on in the vocal tract, for reasons which should become clear as we go.
http://home.cc.umanitoba.ca/~robh/howto.html
try a piano try a flute after breathing Helium
amplitude vs frequency plot¶
from scikits.audiolab import wavread
import scikits.audiolab as audiolab
filename = '/Users/douglasgoodwin/Downloads/aphex_mono.wav'
au = audiolab.sndfile(filename, 'read')
tmp = au.read_frames(1e4)
# float_tmp = au.read_frames(1e4, dtype = N.float32)
title( 'Frequency plot for \n%s\n'%(filename),loc='left' )
# import pylab as P
plot(tmp[:])
spectrogram¶
filename = '/Users/douglasgoodwin/Downloads/aphex_mono.wav'
sound = audiolab.sndfile(filename, 'read')
# Reads wav file with audiolab
sound_info = sound.read_frames(sound.get_nframes())
# Extracts feature info from sound file with scipy module
spectrogram = specgram(sound_info)
#Generates soectrogram with matplotlib specgram
title( 'Spectrogram of \n%s\n'%(filename),loc='left' )
show()
# sound.close()
Any sound can be visually represented by its spectrogram, an image of its spectrum. The horizontal dimension corresponds to time and the vertical dimension corresponds to frequency. The intensity of a given frequency at a given time is given by a color plot at that {time;frequency} coordinate in the image space. Spectrogram views can be found in audio editing softwares such as Adobe Audition, Audacity and many others.
filename = '/Users/douglasgoodwin/Downloads/aphex_mono.wav'
import scipy
x, fs, nbits = audiolab.wavread(filename)
X = scipy.fft(x)
# If you want the magnitude response:
import pylab
Xdb = 20*scipy.log10(scipy.absolute(X))
f = scipy.linspace(0, fs, len(Xdb))
title( 'magnitude response for \n%s\n'%(filename),loc='left' )
plot(f, Xdb)
show()
title?