String of Yeasts

After reading and studying the data (so far) from The Sourdough Project, a bit of it jumped out as a possible sound pallete. The growth profiles of the five most prevalent yeasts and aabs (acetic acid bacteria) measured as increasing Optical Density over a 48 hour period. Measurements were taken in 12 hour increments and recorded from 0.1 to 1.2 levels of density.

I was drawn to this data because the graphs reminded me of waveforms.

I am not at liberty to reveal the details of the data, so suffice to say that these are 5 strains of yeast. We will call them pink, blue, orange, green and neon. The pinpoints mark the 12 hour samplings of the prevalence of the strain. So at 12 hours pink grew to around .25 OD, while neon grew to .6 OD. How to represent this in sound is the next question!

My old friend, the piano keyboard, provides a familiar sonic framework. A two octave chromatic scale will represent the sound of OD growth by stretching the OD measurement scale over the two octaves. Like this:

Each OD amount covers 2 notes. D and D# represent the .1 amount, E and F are .2 and so on. This allows some wriggle room when the 12 hour sample seems to be between two numbers as is seen with pink. The growth range for pink will run from D to F and encompass 4 notes. In the case of neon, the growth range runs from D to C and encompasses 11 notes. The differences in the growth rates will be heard in the number of and duration of the steps taken within each twelve hour time frame. So far, so good!

The time frame will run in beats and measures. Since it is 48 hours of growth, one hour can equal one measure. The step patterns will run up to the highest note indicated by the OD data at that particular 12 hour marker. That makes each sampling unit 12 measures in length – seems perfect. Even better, at 4/4 time, each 12 measure sampling unit is 48 beats long! Synchronous!

Lets lay out the first 12 hours of pink and neon. Since all the yeast densities begin from .1, all the patterns will begin with D in the 3rd octave (D3). pink grows from D through D#, E, and lands on F. For this growth pattern there are 4 notes and 48 beats, so each note will be 12 beats long. The long notes and fewer steps up communicate that pink did not grow much in the first 12 hours. Neon grows from D, D#, E, F – C. For this growth pattern there are eleven notes and 48 beats. Each note is 4.36 beats in length. So the first ten notes are four beats long, and the eleventh is eight beats. The longer note at the end places emphasis on the final growth number for that 12 hour period. Faster steps further up the scale sonify neon‘s more abundant 12 hour growth period.

Looking at the graph, it is easy to hear that the growth patterns of pink and neon invert at the 12-24 hour sampling unit. Pink leaps from .25 to .7, while neon short stretches from .6 to .75. Again, note duration and number of steps will sonify these contrasts in the data.

While a sense of growth is captured by the movement up the scale, there is not yet a sense of increasing density. To get at this, I decided to sustain the top note of each 12 hour sampling unit. As example, pink’s F and neon’s C would continue softly to the end of the 48 measures. This would follow for the last note of each 12 hour cycle and will create the sense of sonic density.

Enough talk, lets have a listen!

neon 48 hour growth pattern

pink 48 hour growth pattern

These are the 48 ms versions of the patterns. So 48 4/4 measures at 120 BPM really stretches out these relationships making it harder to hear the movement of the data. Ableton Live has a function that allows me to collapse the sequence from 48 measures to 24 measures and still maintain the rhythmic integrity of the phrase. WoW! Then the phrase can collapse to 12 measures. All of these phrases will likely be a part of the Sourdough Song, but I am still deciding which version (24ms or 12ms) conveys the data more clearly. One of the researchers on the project said the longer growth articulations conveyed the anticipation the bakers feel as they wait for their starters to grow.

Here is the 12 ms version of both strains together. See if you can hear the changes described above. Listen closely for each voice – you will hear pink holding longer tones, while neon changes tone more quickly. It helps to look at the graph while you listen.

This will likely be one a motif within The Song of Sour Dough. (What do you think of separating sourdough in the title?)

 

Sonification and Life Forms II

Since excitedly sharing the results of a sonic analysis of Lemur Gut Microbiomes, I have been working up a soundscape based on the quick sketch included in the first Sonifications and Life Forms post. (You can hear both below.) In order to get feedback on the work, I sent the first blog post to Mark Ballora, with whom I had taken a data sonification workshop in May. His response helped me realize the need to clarify my sonification process. So here is a description of the project:

The purpose of the sonification is to illustrate the changes in baby lemur microbiomes from birth to weaning. Microbiome data was captured through fecal samples taken at birth, through nursing, introduction to solid foods, regular solid foods, and two times while the babies were weaning. The sonification will illustrate changes in the type and amount of bacterial phyla present at each of the six sampling stages for all three lemur babies. In addition, the mother’s microbiome was sampled at the time she gave birth, so her profile, which was assumed not to change, provides a baseline adult profile with which to compare the babies’ changes.

There were 255 strains of bacteria collected over the course of the study. These fell into 95 classes and 35 phylum. I focused on the phylum, as my plan was to assign a note value to each bacterial data point, so I needed a smaller data set. The data set was narrowed further (and made more interesting) by focusing on a family: a mother Pryxis, and her triplets, Carne, Puck and Titan. This group allows us to not only hear the variety of changes in the babies’ microbiomes, but compare the changes as well.

The original data set included 9 lemur babies and 7 mothers. So the first step was to go through the phylum data sheets and pull out the profiles for Pryxis, Carne, Puck and Titan. A phylum profile would be the type and amount of each phyla present at each data collection point. The profile changes over time at each collection point. The microbiomes of these four lemurs housed 15 phylum (at a density of >.001) out of the 35 found in the entire study group.

The next step was to assign a note value to each phyla. Since there are only 13 notes available in the chromatic scale, some phylum would need to be on the same note, albeit a different octave. Same note, different octave will lend a tonal consonance to the profiles. So what might this consonance represent? There were 5 phylum that had the greatest density and presence in all the samples, so I assigned those to the note G from octave 1 to 5. The remaining 10 phylum were assigned note values based on their presence throughout the profiles, and on their consonance/dissonance with the tonal center G.

In order to capture the density of each phyla, a midi velocity range was aligned with the decimal percentage of the phyla in each profile. Midi velocity settings determine the force with which the note is played. Thus the velocity ranges render a clear sense of presence or loudness to each note played. The decimal percentages ran from .001 to 1.0 and the midi velocity range runs from 1 – 127. Here is a chart of how these ranges overlap:

So for example, Protobacteria present at .25473 would be represented by the note G at octave 3 set at 40 velocity. The largest sample in all the data points captured for this project was around .9 and the smallest was .001 (this was a cutoff point as there were bacterial phylum present down to .0001 ranges.) Here is the chart for Titan showing note assignment and density values through each sample stage:

My sounding board for this data comparison is Ableton Live, a digital audio workstation (DAW). The individual lemurs are represented by a “voice”/midi instrument in Ableton. Tuck, Titan and Carne are bell-like voices that blend together, while Pryxis, the mother, is a warm, pervasive woodwind. She envelops and contains the changes in the babies’ phylum profiles.

All lemurs had a Phylum Profile Chart like the one above. In the DAW, the instrument track for Titan, for Puck and for Carne contains a midi-clip of notes of the phylum colonies present at each stage of dietary change, which were then laid out as a “scene” in Ableton. As example, Titan’s Phylum Profile at birth was

Protobacteria (Note value=G3) set at 101/127 in intensity

Euryarcheatae (Note Value=A2) set at 34/127

Firmicutes (Note Value=G2) set at 11/127

Cyanobacteria (Note Value=A#4) set at 1/127

Other Bacteria (Note Value=B3) set at 1/127

Spirochaetae (Note Value=G5) set at 1/127

Titan’s Birth Phylum Profile is the multi octave chord GAA#B. Three of the phylum were barely present, so those tones are almost inaudible in the chord. However, 2 Gs and the A ring out. The total number of phylum present in each dietary stage varied from 3 to 14, so the multi octave chord becomes more dense and dissonant when the phylum are so varied. Here is a look at the tracks (individual lemur voices) and the “scenes” (which are the phylum profiles from all 3 babies at each stage.)

The first sketch was just the mother’s phylum profile droning under the three babies’ profiles expressed as a stacked megachord. All 3 baby profiles rang out together four times at each stage, starting with birth and ending with the second wean. What could be heard was a homogeneity and consonance between the Mother and babies at birth that gradually became more diverse and dissonant as solid food was introduce. However, by the second wean, the babies’ and mother’s profiles become more consonant again. The researcher said this illustrated the conclusions of her study.

As a soundscape artist, I felt there was more here than just that basic chordal movement. The babies’ phylum profiles were quite different from each other as well, which is lost in the chord presentation. For example, Carne’s birth profile has only 3 phylum, while Titan has twice that amount. One way to hear this level of contrast in the baby profiles is to articulate the chords into riffs. Now we can hear the interplay of the changes in their microbiomes. In addition, we can hear how consonnant/dissonant and dense the phylum become as outside food is introduced into their systems. Titan’s phylum profiles arpeggiate down, Puck’s go up and Carne’s go down then up. A practiced deep listener could key in on a particular profile and follow it through to the end. I played around with rhythmic shifts to create more movement in the stages where the phylum profile were incredibly dense and diverse. The last two arpeggiating riffs you will hear are all of the phylum notes sounding through twice. And listen for the elevated levels of Protobacteria in all 3 profiles at birth – that G3 rings out at that point.

As I put this full family profile together, another more nuanced movement in the data appeared. In the chord rendering, I heard the data get more dissonant and dense from nursing through first wean, and then the phylum thinned out and became more consonant at the last wean. In the riff rendering, I can hear a contraction and more consonance at the Intro to Solid Foods stage as well as the second Wean. That was not clear in the chord presentation. When I checked my data records, there was a drop in the number of phylum present between Nurse and Intro stages. I love that a nuance appeared in the listening that made me go back and check the data. That is exactly how I hope this process will work.

Some other things for future consideration:

Aligning each phylum tone to a particular beat might help the listener hear the differences from stage to stage more clearly.

When assigning notes to data points, closer attention to the harmonic overtone series might help clarify the role consonance and dissonance play in hearing the data.

The voices of the baby profiles have similar timbre as a unifying element. The profiles could have very distinct voices which might make the variances in their profiles more audible.

Up next – Sourdough Songs.