Categories
DIY Making

Frameworks Week 13

An ‘audio sketchbook’ – a non-book containing non-sketches, more of a ‘samplesite’

Frameworks for Interactive Sound

Spring, 2004

Jeff Feddersen

Obvert box, shake, return, select orientation, make sketch.

Initial Sketch


(Did not include radiating lines of fresnel lens)

Select aural metaphor for each visual detail.


Represent grid with kick drum

Represent walls with high hat

Represent both screws and half-walls (shown in blue) with hand clap

Represent sugar with snare (granular synthesis would have been too obvious)

Represent Marbles with TS404

Drum Machine snapshot

The hand claps are pitched enough that you can hear the difference.


I chose 90bpm so that it approximates a human heartbeat.

Rather than make 19×11 separate phrases, I chose to make 20 phrases, each representing a column in the grid, with the y axis (looking down) representing pitch.

Waveform

Kick drum and high hat in left channel, hand clap, snare, and TS404 in right channel.

Here I chose to represent my imagined process of how the box was constructed, first just the lens, then the walls, then the other walls and screws, then the sugar, then the marbles – then taking it apart again.

The Piece – “Why, it’s a piece of… art!”

Categories
DIY Language Making

Frameworks Week 12

Genesis put out an album called ABACAB, named for the standard form of many of their songs

Best Song Ever:

“My Six-Year Old Son Hitting Pots and Pans With a Spatula”

Album: Sounds From the Kitchen

Malleus Maleficarum – ©ï@|í5

Find the script to a play. The meter will affect the final music, so keep in mind that Shakespeare may sound somewhat boring.

Find a scene with a number of actors equal to the number of people participating.

Just you means select a monologue, just you and one friend means find a scene with exactly two characters, etc.

If you want to try playing the parts of two characters you can try but it will be more difficult.

If it’s just you, you may want to use a famous speech (e.g. The Gettysburg Address) instead of a play.

Find two or three objects that make a sound when you hit them (with your hand, a pen, a hammer, whatever)

Ideally you will have sounds that differ in pitch so that you end up with the ability to make a low sound and a high sound, and possibly a middling sound.

Now, read the text of the play as though you were acting, but don’t vocalize any of the words.

Instead, ‘play’ the words with the instruments you just collected.

Pay attention to the rhythm and inflections in the voice you hear in your head as you play your instrument.

An example might be:

From The Empire Strikes Back

– “Luke, I am your father.”

– “No. That’s not true!”

Could sound like:

instrument set 1: ‘middle (pause) HIGH middle middle MIDDLE low’

instrument set 2: ‘LOW (pause) middle middle HIGH’

Hit the instrument harder or softer to suggest yelling or whispering, etc. The words in caps above suggest louder sounds.

If playing directly from text is too difficult, first transcribe the text into the notation used above and play from that.

Categories
Animation Kids Stories Videos

The Road to Obion

Here it is, at long last – the synthesis of my interests in music, narrative, and visual arts: matchstick.com/acetio

Matt Slaybaugh – Spring 2005

An Online Animated Musical Adventure

The lessons of the past can be taught via a new kind of narrative.

  1. Mythology
  2. The Story
  3. Trailer
  4. The Animation
  5. The Music
  6. Online Distribution
  7. Production Objectives

Matt Slaybaugh – Spring 2005

Mythology

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Matt Slaybaugh – Spring 2005

The Story

Primary Characters

Cathode Ray – The central hero, the voice of reason, always looking for ‘the middle way’

Paul Pecker – Ray’s closest companion, the skeptic, slacker

Regina – A former pirate, the most spirited of the group

Dr. Kilbert Saturday (Dr. K) – The villain, not quite pure evil

Secondary Characters

Aunt Jenny – Ray’s aunt, a nurturing figure and the cause of the first adventure

Johnny Valve – A robot fascinated and jealous of the human traits denied to him

Dr. Monday – The mentor, affable and loony

The Machine – Dr K’s main tool of destruction, a large walking robot

The Messenger – A flying black metal skull that delivers warnings by spitting out red ribbons with embroidered text

The Guardians – Two ghostly figures, one blind and one mute, who protect the entrance to Dr. K’s fortress

The Helping Hands – Two flying stone hands that do Dr. K’s bidding

The Other Doctors – Drs. Monday and Saturday were once part of a group of 7 engineers. These characters are the wizards of this world.

Other characters who appear infrequently: Keasto, McDuff, Rumlock, Quoin, Magrus, Ricker, Tyrus

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Matt Slaybaugh – Spring 2005

Trailer

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Matt Slaybaugh – Spring 2005

The Animation

Visual style reflects ideas of recycling and conservation

Characters represented as anthropomorphized animals

Inspirations: Terry Gilliam, Ralph Bakshi

Animation Sketches:


Background for title – 133KB

Gatekeepers – 229KB

Laboratory – 532KB

Retalliation – 539KB

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Matt Slaybaugh – Spring 2005

The Music

Markov Chain analysis

Prevalence of intervals

Inspirations: Rodgers and Hart, Beatles, Nirvana

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Matt Slaybaugh – Spring 2005

Online Distribution

Name and Logo

Ascension from Ruin

Markov Chain, Albion, Zion, Oblivion, Tennessee

The animations will be produced in Flash and made available via the Web.

Marketing

I plan to rely on the power of viral Internet marketing, by submitting new content to well-trafficked blogs.
This is a proven method for online games, short films, and cartoons.

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Matt Slaybaugh – Spring 2005

Production Objectives

Immediate

To create one two-minute teaser trailer that introduces the characters and the visual and musical style

Short-Term

To draft scripts for about one dozen scenes, with one or two songs per scene, including music and lyrics

To complete animation for one five-minute scene, including recorded song and dialogue

Long-Term

To continue project with new one new episode each month

To continue developing characters and storyline

To generate revenue via sales of branded merchandise, sales of compilation DVD, or possibly seling as a package to a network

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Categories
Making

Frameworks Week 11

Ada Babbage: Abba: Aba Cadaba

Heinrich Schenker had some interesting theories of music. One, I believe, was that every euphonious melody begins on the 3rd or 5th and ends on the root.
If you find a melody that does not fit this pattern, by adding or removing notes so that the melody does fit will actually ‘fix’ the melody and make it sound better.

– Made with FruityLoops, Jazz32, and Audition, as well as Blaze Audio Wave Creator and Goldwave

– VanBasco’s Karaoke Player is good for previewing midi files, jetAudio converts just about all formats, including midi. AnvilStudio edits midi files.

1ne – ABA – texture

2wo – ABA – 4/4 : 3/4 : 4/4

3hree – ABA – complexity

4our – ABA (or ABCA?) midi track quantized to 1/12th notes for an odd, staggered rhythm

5ive – AABB’AA severely processed guitar – B’ (b prime) is just a note or two different

6ix – AABA repeated with pitch shifting in the same pattern of AABA

7even – Fractal ABA (11 generations) – imagine a big triangle on its face pointing toward you

8ight – Fractal ABA (better math, but only 3 generations – using voice)

9ine – More processed guitar – AABACDDD

10en – AAAABA – like an irrational number, repeats infinitely

11leven – AAA’ABAA – ‘inverted feedback’ gives it an old-timey sound

Categories
Making Projects

Frameworks Week 10

“Feel the beat of the rhythm of the night!” – El DeBarge

Ursatz or Ersatz?


one – ‘mystery rhythm’ alternating with 3, fft=10

two – beat on 4 with more intricate intermediate rhythm, fft=6

three – loose rhythm, fft=12

four – ‘smells like Philip Glass’, beat on 5, 2+3 a là Brubeck ,fft=8

five – bass line with echo of 300ms (slightly longer than delay between beats) ,fft=8

six – dehydrated electronica: two sines (100 & 101) create pulse of 1 sec. double speed and pitch and remix, do again, and again.

Annotated Listening

Categories
Making

Frameworks Week 7

Bring in the Noise, Bring in the Skunk

Talking about music is like dancing about architecture

Fifty-Five Noises, some from nature, mostly man-made. The natural ones are most interesting to me.


Wind itself makes very little noise, just a low pitch as the air is pushed against your eardrum.


The sound of wind over a field of grass makes a ‘shh’ sound as the individual blades vibrate slightly.


The sound of wind through trees has a whistling sound, noise with an exagerated frequency or two. This must be the branches or leaves shaping the air.

I tried doing some spectrography on these noises, but since they contain huge swaths of frequencies, the spectrograms ended up just looking like solid blocks with no discernable concentrations, which makes sense.
The noises that had clear patterns were then not noise at all.

Play with the filtergraph patch in MSP. You’ll see that surf has a Q of under 1 and wind has a Q of over 2. The noise in between doesn’t quite sound like either.

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List of sources

Categories
Making

Frameworks Week 6

Week 6

I discovered that you can save an audio file as txt format, which then has a single line header (e.g. [ASCII 11025Hz, Channels: 1, Samples: 287448, Flags: 0]) and then one line for each sample with a single value (e.g. 0.00781) on each line.
The numbers must represent both pitch and amplitude.


Here’s an original and with all the numbers sorted

Headers are in uppercase, so changing all characters to upper case left the headers intact while making everything lower case ended up messing them up.

Changing character set on the Sopranos file made it unreadable (even though I left the header intact) while it had almost no effect on the honkytonk file.

OriginalUpper CaseLower CaseAlphabetize LinesSpell-CheckCharacter-set Conversion (to DOS)
bionic.aifbionic.aifbionic.aifbionic.aifbionic.aifbionic.aif
ChestnutSidedWarbler.aifChestnutSidedWarbler.aifChestnutSidedWarbler.aifChestnutSidedWarbler.aifChestnutSidedWarbler.aifChestnutSidedWarbler.aif
fembot1.aiffembot1.aiffembot1.aiffembot1.aiffembot1.aiffembot1.aif
honkytonk.aifhonkytonk.aifhonkytonk.aifhonkytonk.aifhonkytonk.aifhonkytonk.aif
jibberish.aifjibberish.aifjibberish.aifjibberish.aifjibberish.aifjibberish.aif
LarkSparrow.aifLarkSparrow.aifLarkSparrow.aifLarkSparrow.aifLarkSparrow.aifLarkSparrow.aif
sopranos1.aifsopranos1.aifsopranos1.aifsopranos1.aifsopranos1.aifsopranos1.aif
under-dog-theme.aifunder-dog-theme.aifunder-dog-theme.aifunder-dog-theme.aifunder-dog-theme.aifunder-dog-theme.aif
wilhelm.aifwilhelm.aifwilhelm.aifwilhelm.aifwilhelm.aifwilhelm.aif
Categories
Making

Frameworks Week 5

Week 5

RM

1 – Bush SotU 1, RM at 500Hz

2 – Bush SotU 2, RM, rising cycle 0 to 1000Hz

(and for comparison, the Gold Cylon leader)

AM

3 – Unprocessed Lark Sparrow

4 – Lark Sparrow with 1kHz AM

5 – Lark Sparrow with 1kHz RM

FM

6 – signal of 1kHz, mod freq of 5, changing modulation depth from 0 to 20000 – note the fluttering helicopter sound

7 – mod freq: 14,061, mod depth: 2,656, carrier from 0 to 20,000 – note the musical scale that appears

8 – R2D2 upchucking the above use phasor, this uses cycle

9 – ‘Wow’ created with modrate of 1 mod depth of 199 on freq of 128

White noise, pink noise, red noise, and brown noise

A history of digital audio compression

A good (well, pretty good) explanation of MP3

And a slightly less technial explanation of MPEG, psychoacoustics, etc. is here

MPEG is lossy, just like JPEG, but bitrates of 48 or 56 produce files with no audible artifacts (at least on my speakers) and going this far below the typical 128kbps means an additional compression of maybe 4:1.
The artifacts produced by too much compression always sound ‘watery’ to me, and, not coincidentally I imagine, seem to be an exact synesthetic representation of JPEG compression artifacts.
JPEG artifacts typically occur at edges between areas of different colors, and MPEG artifacts seem to happen more when there are the audio equivalent of that, having many high- and low-frequencies occuring together.
But, just as texture in a JPEG image can mask the effects of artifacts, rich aural texture can mask MPEG artifacts.

A neurobiology and behavior student has made hamster-controlled midi music
(mirror)


As usual, Markov chains were involved

Categories
Making

Frameworks Week 4

Week 4

Electronic Music that tries, and fails

15-year old invents ultrasound mosquito larvacide device

The grey album link posted this week on the list is better than the one I had a week or two ago.


It’s much better after a few listenings. The first time I thought, “I wish that guy would shut up and let the Beatles play.”


But now I can hear beyond the original songs and appreciate the new arrangements, and like them all (though least of all ‘justify my thug’, there’s some actual singing on the vocal track that doesn’t match the dubbed-in music)


The with this kind of mix is that the melody supplies the rhythm and the bass line provides the narrative, just the reverse of most older pop music, certainly the White Album.


On the other hand, I can’t listen to this for than about an hour without starting to feel irritated.

Scalies

#1: Inverse Primes

  1. Take the set of prime numbers, including 1 (1,2,3,5,7,9,11…)
  2. Divide them into 1 to get a set of values between 0 and 1 (0.5, 0.333, 0.2, 0.142857, 0.09…)
  3. Multiply these values by some frequency (A-440) to get a scale
  4. Add these numbers to the same frequency (A-440) to get the octave scale above it.

The values are: 880, 660, 587, 528, 503, 480… 440


As the primes increase, the inversions approach 0, so the scale frequencies get closer and closer together.


It’s quite euphonious, in a minor kind of way

Listen

#2: Inverse Primes II

  1. Take the set of prime numbers, including 1 (1,2,3,5,7,9,11…)
  2. Divide them into 1 to get a set of values between 0 and 1 (1, 0.5, 0.333, 0.2, 0.142857, 0.09…)
  3. Multiply these values by some frequency (A-440) to get a scale
  4. Subtract these numbers from double the same frequency (A-880) to get the octave scale above it.

The values are: 440, 660, 733, 792, 817, 840… 880


As the primes increase, the inversions approach 0, so the scale frequencies get closer and closer together.


In both examples, I pause at the point where the notes get so close that they sound dissonant, in both cases at 1/11


It’s a little euphonious, in a minor kind of way

Listen

#3: Inverse Primes III

Taking just the primes 2, 3, and 5 and combining the two scales above:

n1/nA-440 + A-440/n2*A-440 – A-440/n
1/11880440
1/20.5660660
1/30.333587733
1/50.2528792

Listen

Not too bad. The equal-tempered equivalents are:

A (440,440)

C (528,523)

D (587,587)

E (660,659)

F# (733,740)

G (792,784)

A (880,880)

This scale has a sharper minor third, slightly flat fifth, flatter 6th, and sharper 7th.

#4: birdSong

The frequencies taken from a sample of a lark sparrow’s song.

Listen

‘snot wong – ‘swite

Snot Wong has some interesting patches for Max/MSP.


There are at least 50 sites that I saw with patches to download, you can google them yourself, but this one is worth listing as well.
He has practically a dissertation written as MSP help files, so you can play along.

Sounds of Nature: Breaking the Wind

This page has more spectral analysis software as well as analyses of whales, human voice, etc.

When I was in college, my job was digital sound engineer, recording and editing language instruction tapes using this brand new tool called ProTools.
I used to hang out with the linguistics post-docs and they showed me their work. If I remember correctly, the human voice has three dominant frequencies, with many more less-pronounced ones.
So to imitate the human voice, I guess we’d need chords with three pithces. Maybe that why three-note chords sound good to us.

Here’s a spectrograph of my voice. Even while trying to speak clearly and evenly, there are lots of harmonics.

Here are the frequencies I found in one bit where I said ‘ah’ for a few seconds, trying to match C2 on my keyboard: (just looking at frequencies with over 30dB of representation)

144D
268C/C#
402G/G#
526C
670E/F
794G/G#
918A/A#
1052C
1186D
1309E
3010F#/G
3546A

Not at all what I was expecting. The ‘C’s seem on target, but all the other notes are a surprise. It looks like some kind of 9th chord.

Here’s the actual sound

And here it is created by Max (warning: sounds like crap)

So if I ever meet my robot-clone-doppleganger, I’ll be able to recognize him by his voice, which clearly, sounds terrible.

Obviously there’s a lot more subtlety to the human voice than just raw frequencies.


Pythagorean Coma Toast

“When you ascend by a cycle of justly tuned perfect fifths (ratio 3:2), leapfrogging 12 times, you eventually reach a note around seven octaves above the note you started on, which, when lowered to the same octave as your starting point, is 23.46 cents higher than the initial note. This interval, 531441:524288 or approximately 1.0136:1, is called a Pythagorean comma.

This interval has serious implications for the various tuning schemes of the chromatic scale, because in western music, 12 perfect fifths and seven octaves are treated as the same interval. Equal temperament, today the most common tuning system used in the west, gets around this problem by flattening each fifth by a twelfth of a pythagorean comma (2 cents), thus giving perfect octaves.”

51st root of 2 = 1.0136839
Pythagorean comma = 1.0136432647705078125
52nd root of 2 = 1.01341899

What does this mean?


It means you smell.

The amazing thing about Pythyagorus and the other ancients is that they did their long division using fucking Roman Numerals!

There are a few fundamental irrational numbers:
pi = 3.14159265


e = 2.71828183


the golden ratio = 1.61803399

Early confusion over the exact value of pi was because people assumed it had to result from a basic ratio, such as 22/7.

I have a theory, that there is a basic irrational number that determines fifths in music that is not based on a fraction such as 3/2 and results in a euphonious scale that includes no comma.


It can’t be pi, e, or the golden mean, because they all sound terrible (I tried them all and pi sounds best, but still bad)


In order to eliminate the comma, the ratio has to be around 1.49.


Now, I tried 3/2 (1.359140915) which sounds okay, actually, and pi/2 (1.5707963267948966192313216916398) isn’t as bad as it could be.

Cent


“The cent is a logarithmic measure of relative pitch or intervals. 1200 cents are equal to one octave, and an equally tempered semitone is equal to 100 cents. The formula to determine the value in cents between two notes with frequencies a and b.

The measure was developed by A. J. Ellis around the 1870s, and was published in his edition of Hermann von Helmholtz’s On the Sensations of Tone. It has since become the standard way of measuring intervals in equal temperament systems or for comparison with equal temperament systems.”

So the comma (logarithmic) is equal to about a quarter of a half-note (linear)

This JavaScript (I think) shows the comma for A-440

Going up by fifths, you wind up at 57088.388671875, but going up by octaves you get 56320.


If you go down by octaves from the first value, you get 446.0030364990234375.


Since A# = 466.1637596Hz, and the difference between A and A# = 26.1637596Hz, a comma here of 6 cycles per second is significant.

So, my proposed new irrational number is:

1.498307

This page shows how the intervals stay the same all the way up the chain.
It’s so close to 1.5 that you don’t hear the difference between say, 100Hz and 149.8Hz

And now. Oh shit. I look at the chart with the 12-tone equal temperament and see my number already there, as the ‘fixed’ ratio for a perfect 5th.


Oh well. I guess that’s what they were talking about.


Mth Nrd2

Let’s a try a kind of fibonacci sequence, using the ratios between numbers for our scale:

11/0
11/11
22/12
33/21.5
55/31.67
88/51.6
1313/81.625
2121/131.615
3434/211.619
5555/341.617
8989/551.618
144144/891.618
233233/1441.618

It looks good. It even includes the basic pleasing intervals of 3/2 (fifth), 5/3 (sixth), and 8/5 (minor 6th)


The assymptotes to the golden ratio, so I guess this scale is just a single octave with infinitely many notes in teh area where sixths normally are.


Unfortunately, there is no equivalents of 2nds, 3rds, 4ths, or 7ths. Unless…

Lets’ add a column to allow division by 2 numbers behind. Of course, then we end up with intervals such as 3/1, which is outside the range of an octave, so let’s also divide everything by 2, to keep it in scope:

11/01/01/0
11/111/01/0
22/122/122/21
33/21.53/133/21.5
55/31.675/22.55/41.25
88/51.68/32.678/61.33
1313/81.62513/52.613/101.3
2121/131.61521/82.62521/161.3125
3434/211.61934/132.61534/261.307
5555/341.61755/212.61955/421.309
8989/551.61889/342.61789/681.308
144144/891.618144/552.618144/1101.309
233233/1441.618233/892.618233/1781.309

The first new column levels off at the golden mean + 1. I didn’t know that would happen. And of course the second levels off to half that.


We could keep messing around with this forever, I suppose, but let’s now order our scale:

1/11
5/41.25
13/101.3
(gold+1)/2
8/6 (4/3) 1.33
3/21.5
8/51.6
gold
13/81.625
5/31.67
2/12

So the lowest note above the root is a major third, then some meanderings around half of one plus the golden ratio (which would be like a diminished 4th, I guess), then a 4th,
then a 5th, then a collection around the golden mean, which is around a major 6th. So, no equivalents of 2nds or 7ths.

Let’s add another column:

numberratiodecimalratio2decimal‘repaired’ ratio2decimalratio3decimal
11/01/01/01/0
11/111/01/01/0
22/122/122/212/0
33/21.53/133/21.53/13
55/31.675/22.55/41.255/15
88/51.68/32.678/61.338/24
1313/81.62513/52.613/101.313/34.33
2121/131.61521/82.62521/161.312521/54.2
3434/211.61934/132.61534/261.30734/84.25
5555/341.61755/212.61955/421.30955/134.23
8989/551.61889/342.61789/681.30889/214.23
144144/891.618144/552.618144/1101.309144/344.23
233233/1441.618233/892.618233/1781.309233/554.23

It looks like we can’t go on infintely after all. Even if we fix the column by finding the ratios an octave down, we get mostly the same values

I’ll drop the values that hover around the assymptotes, and we get: (bold indicates the ‘pure’ tones that we got on the first pass, the other ones can be optional)

1/11
5/41.25
(gold+1)/21.309
3/21.5
gold1.618
5/31.67
2/12

There are no numbers in the ratios larger than 5. That seems clean and pure.

And again with sample frequencies and equal-termpered equivalents:

1/11440A
5/41.25550C#
(gold+1)/21.309576C#/D
3/21.5660E
gold1.618712F/F#
5/31.67735F#
2/12880A

The ugliest notes are the gold and (gold+1)/2.
With the others we can make a decent A major chord.

The next trick will be to do it again using the E-660 as the root:

1/11660E
5/41.25825G#
(gold+1)/21.309864G#/A
3/21.5990B
gold1.6181,068C
5/31.671,102C#
2/121,320E

Combining these tables and halving some of the values, we get the full monty:

440A
495B
534C
550C#
576C#/D
660E
712F/F#
735F#
825G#
880A

And just for overkill:

1/11990B
5/41.251237.5D#
(gold+1)/21.3091295.91D#/E
3/21.51485F#
gold1.6181601.82G/G#
5/31.671653.3G#
2/121980B

To produce: (cleaning out redundancies and adjacents) The standard frequencies are in the right column

440A440
495B493.88
534C523.25
550C#554.37
576D587.33
619D#622.25
660E659.26
712F698.46
735F#739.99
801G783.99
825G#830.61
880A880

I’m still missing an A#.

Maybe this shouldn’t count. All I’ve done really is replicate a version of a just tuning that surely existed hundreds of years ago.
But play it in mixolydian or phrygian, and then you’ve got something!


Bird Droppings

Cornell’s Ornithology Lab (birds.cornell.edu) is probably the best of its kind in the world (and a beautiful facility nestled in Sapsucker Woods in Ithaca, NY if you’re ever upstate).
They have a free gallery/museum/exloratorium with lots of exhibits in which you can, for example, manipulate the wave forms of different bird songs.
They’ve made the software available on their site, under the Bioacoustics Research Program

I downloaded Raven which has a 10-minute timeout on the license, and doesn’t allow saving.
They also have an app called Canary on the same page which is mac only, so I didn’t try it.

Raven come with some good audio files.


For example, here is a Lark Sparrow


And here is a Canyon Wren

And here is a Bowhead Whale

Sped up 2x, 4x, 8x, 16x

The 4x and 8x sounds like bird calls, and the 16x sounds more like an insect.

For comparison, there is also a Spotted Hyena, and perhaps the most interesting, a Bearded Seal

Many animals seem to use a lot of rising and falling pitches, rather than single ones.


Also, there is no sound envelope with these sounds, playing them backwards sounds pretty much the same as forwards – there is no attack, just quick fade in and quick fade out.

You should also be aware of Silbo Gomero, a human language based entirely on whistling, used in the Canary Islands.
Here’s an example with three people communicating.
The langugage supposedly has eight ‘elements’ which would correspond to phonemes, I suppose. I’m guessing it uses duration and rising vs. falling pitch as some of them, as opposed to absolute pitch.


Here’s a translation of the above conversation

 
"Hey, Servando!"
"What?"
"Look, go tell Julio to bring the castanets."
"OK. Hey, Julio!"
"What?"
"Lili says you should go get the kids and have them bring the castanets for the party."
"OK, OK, OK."


Using Raven to run a spectrum analysis on the Lark Sparrow recording, I find these dominant frequencies (paired with conventional equal-tempered note equivalents)

2,412D/D#
2,584D#/E
2,670E/F
4,134B/C
4,221C/C#
4,306C/C# closer to C#
4,996D#
5,082D#/E
5,426E/F
6,460G/G#
9,388D
And some weaker overtones at
10,900E/F
16,350B/C

At first glance I look for doublings to indicate octaves, 2,412 * 2 = 4,824, which is close to the derived value of 4,996, but still almost an entire half-step below.


Similarly, 2,584 doubles to 5,168, which is near 5,082, but about a third-step above.


A little closer is 5,426 which doubles to 10,852, very close to 10,900.


The measurements on these can’t be precise, so I may be allowed to assume some fudge factor.

Remarkably, although the pitches above fall in between the standard note frequencies, they do so regularly and consistently.
Also, the majority of notes fall between C and F, regardless of which octave it’s in.

The 12th root of 2 is 1.05946309. If we look at the two lower frequencies above, the difference is 1.0713101160862354892205638474295 – close but different.


If I divide adjacent frequencies, I get numbers such as 1.191, 1.160, 1.041, 1.033, 1.021, 1.020, 1.017. None are the same, but they’re all in the same order of magnitude and there seems to be hovering around 1.020.


Now, Google tells me that the 32nd root of 2 is 1.02189715.


Let’s build a scale, using the base Lark Sparrow note of 2,412 as our fundamental (with a little recorrecting). It holds up pretty well,
for example, 4134 * 1.02189715 is 4224.5228181, quite close to the 4221 that I got from the spectral analysis

2,412
2464.815
2518.788
2573.942
2640.582
2728.465
2788.211
2849.264
4045.416
4134
4224.522
4313.427
4400.289
4496.642
4888.946
4996
5105.398
5193.281
5306.999
5423.207
5544.813
6321.575
6460
6601.455
9186.834
9388
9593.570
10666.43
10900
11138.67
15999.65
16350
16708.01

On this page I made a JavaScript that spits out all values based on the above scale, starting at each different value from the spectrograph (using the first few).


Some are close, but I’m doubting whether it’s right.

This page has a good Java applet to let you combine notes and see their waveforms.

I’ve been Googling, looking for the piece that used an 11th interval to suggest the braying of a donkey.
“Donkey+11th” didn’t yield much, nor did “donkey+11th+interval”.
“11th” by itself produced, of course, thousands of references to ‘September 11th’
I tried synonyms for ‘donkey’ and let’s just say that while “11th+ass” got lots of results, the fruit it yielded was less sweet than I had hoped.


Prime Ribbing

Let’s do the Fibonacci (one ‘n’, two ‘c’s) thing again, shall we? But this time using Prime numbers.

Here are the first 8 (did I miss any?)
2, 3, 5, 7, 11, 13, 17, 19

n1/nA-440 + A-440/nEqual-Tempered Equivalent
1/11880A
1/20.5660E
1/30.333587D
1/50.2528C
1/70.142857503B/C
1/110.09480A#/B
1/130.076923474A#/B
1/170.0588235294117647466A#
1/190.052631578947368421463A#

Not bad. Levels off to A#, and eventually to A.

nn/n-1decimaln/n-2decimal
1
22/12
33/21.53/13
55/31.6675/22.5
77/51.47/32.333
1111/71.5711/52.2
1313/111.1813/71.857
1717/131.30817/111.54
1919/171.11819/131.462
2323/191.21123/171.353
2929/231.26129/191.526
3131/291.06931/231.348
3737/311.19437/291.276
4141/371.10841/311.323
4343/411.04943/371.162

Clearly we have a leveling again as the ratios approach 1.
But we want to have a ratio as low as the 12th root of 2.
Looking at the Mersiennes, it looks like we may need all numbers up to 40 or so.


But now I have too many. This one’s too complicated.

Categories
Making

Frameworks Week 3

Week 3

Mth Nrd

Explanations of the sounds below

1.mp3 a chord based on tuning based on the Golden Mean.


2.mp3 a chord based on tuning based on the Fibonacci Sequence.

Secrets of Beating Off Explained!

Explanations of the sounds below

3.mp3 100Hz + 101Hz = beat of 1 sec.

4.mp3 100Hz + 102Hz = beat of 0.5 sec.

5.mp3 100Hz + 101Hz + 103Hz = 3 beats per second, with an emphasis every third beat (3/4 or waltz time).

6.mp3 100Hz + 101Hz + 104Hz = 4 beats per second, with a deemphasis every fourth beat (quasi 4/4 time).

7.mp3 100Hz + 102Hz + 105Hz = finally getting interesting. I’m not sure I can describe it.

8.mp3 100Hz + 102Hz + 103Hz + 105Hz + 107Hz + 111Hz + 113Hz + 117Hz + 119 = Still a one-second beat, with much more texture.

9.mp3 100Hz + 103Hz + 107Hz = An interesting kind of 5/4 beat. I can’t explain it.

The bigger the difference between the frequencies, the faster the interference and thus the beat.
I got some good, subtler effects by adding small fractionally-larger frequencies to the above (e.g. 100.25Hz) which then modulates the overall wave over a period of a few seconds (four, I think).


“Radio killed the Telharmonium star… Radio killed the Telharmonium star…”

You’ve probably heard some of the hype around “The Grey Album” a remix of The Beatles’ white album and Jay-Z’s “The Black Album”.
I’ve been looking for downloads, but only found 45-second samples here.
I think it’s kind of over-rated, although “99 Problems” is okay. So much of that kind of music is little more than playing a good song while talking over it.
Maybe it’s just me, but I like music that represents someone talking to me, rather than actually having someone talking.
The classical or jazz instrumentals that I like have the quality of being an aural abstraction of someone telling me a story.

If you look at the Sandbox site some more, you can find quite a lot of interesting (though unordered) clips.
I found one that didn’t have the word ‘nigga’ in every other track.

The problem I have with a lot of ‘new music’ is that it’s designed and marketed for the ‘club scene’ and in some ways is the ultimate sellout in that it exists to be sold rather than existing to be beautiful.


I’m waiting for an album called ‘Sand Nigga’ made by some Palestinian rapping about oppression under the Israeli government.


Bob Gluck made an interactive sound installation using Max/MSP called Sounds of a Community with sculptural electronic instruments in the form of Jewish ritual objects: eShawl, eFloor, eHarvest, and eChant.
There are Max screenshots and Quicktimes, but they don’t reveal much.


I did a Google on interactive sound, most links were uninteresting, but this one had some sub-links worth listening to.


I ‘work’ with acknowledgement of the thesis that music is the aural equivalent of the clitoris – an evolutionary accident that gives pleasure to some.