Recording unique sounds was an exploratory side project that turned out to be a much bigger endeavor than I initially planned, mostly due to how interesting it became diving into the data and patterns, and learning of the steps involved.
The entire process flow is not just about recording sounds, but also deciding where to go and what type of sounds to record, extracting the raw data from .wav files, turning that data to life with visuals, and looking at patterns.
The soundtrack is published as podcasts
If you’d like to hop right into listening to some of the sounds feel free to check out the soundtrack I published as a podcast in the link below, however if you’re interested in hearing more about how the project started please continue reading on.
Listen to soundtracks here
It all started with a cable car ride
The first high quality sound recording I did was of a cable car ride from Ghiradelli Square to downtown Powell Street.
A random Saturday night after spending time researching the best devices to record high quality sounds I decided to stop by a local guitar store right before they closed to purchase a Zoom recorder. I was super excited to try it out and within a few minutes of testing at home I headed off to record sounds around the city!
Soon after a brisk walk from North Beach to Ghiradelli Square I hopped on a cable car and picked a front row seat. Given it was around 11pm at night and chilly, there were plenty of seats to pick from. I reached for the recording device out of a Trader Joe’s bag, turned it on, and started recording shortly before the ride started.
As you might expect I did indeed get a few weird looks from people sitting around me for holding a foreign looking device in one hand and gripping a handle bar in the other hand. Over time it got easier to ignore peoples expressions, but it was one of the challenges throughout the entire project recording sounds.
Ginormous file size!
Soon after getting home I transferred the sound wave file from the recording device to my Mac and I loaded the raw data into what’s called a DataFrame using Python and Pandas. My computer crashed in the process! After booting up again I checked the file size and it was almost 200MB, which means there’s a LOT of data!
After a few tries I was finally able to load the file into a dataframe to plot a visual representation of sounds during the cable car ride.
Want to guess how many data points are collected in a 19 minute cable car ride visualized in the chart above?
After a little research I learned that 44,100 records are logged per second in a 16 bit wave file. After some quick math it equates to over 50 million records in the dataset!
This got me hooked
Up until recently I worked professionally in data analytics for several years and it required consuming vast amounts of data for data wrangling, research, and story telling. But it was an entirely new experience for me to generate raw data in a pure untouched form.
I was fascinated with this new experience and the limitless learnings that could come out of collecting and analyzing patterns of sounds.
On a quick side tangent I recently left the corporate world to focus fully on growing as an independant artist, photographer, and writer. This also gives me more time to work on exploratory projects like this one recording unique sounds.
In summary this exploratory side project is about sounds and patterns
This exploratory side project is primarly focused on recording unique sounds, extracting the raw data from .wav files, turning it to life with visuals, and looking at patterns.
More short stories recording sounds
Here’s a taste of the next article I’ll write about waking up super early on a foggy Saturday morning to record the fog horns of Golden Gate Bridge. It was one of the memorable days recording sounds in this project.
You can listen to the fog horns below.
And here’s what the pattern looks like after extracting the data and turning into a data visualization.
More to come on this story soon!
Thanks so much for visiting Viz.Life. I want to thank my family, collectors, friends, and visitors for supporting me in this endeavor.
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Twitter : @VizDotLife
Discord : https://discord.gg/p65rU793