On a cold winter evening, I was walking through the woods near my home. Away from the noise of city traffic, the only sound I could hear was birds singing somewhere in the distance.
After a few minutes, I stopped near a tree to rest. A small bird landed on a branch and began to sing. It was peaceful. No movement, no distraction — just the bird’s song. But as I listened quietly, a question surfaced in my mind:
“What is the bird singing about?”
I could hear the rhythm, notice the changes in pitch — but I didn’t understand its meaning. We know birds use songs to communicate. That means other birds can somehow decode that information. But to me, it was a mystery.
Out of curiosity, I opened the voice recorder on my phone and recorded the bird's song. I didn’t think much of it at the time.
Months later, while scrolling through old files, I came across that recording again. By then, I had been learning about nonlinear dynamics, fractals, and chaos theory. I had also started coding in Python. That’s when the idea hit me:
“What if I applied these mathematical tools to the bird song I recorded?”
So I did. I started experimenting with time series analysis, using techniques like delay coordinate embedding — and slowly, beautiful patterns began to emerge from the data. Spirals, loops, and attractors hidden in the sound.
That small experiment turned into an ongoing exploration. I began analyzing other bird recordings and found that each one had its own unique patterns. I wondered: Can we extract meaning from these shapes? Can we understand the language of birds in a new way?
This curiosity led me to dive into many different areas — from chaos theory and biomechanics, to perception, predictive coding, and even the theory of mind.
I don’t claim to have answers. But this project is a reflection of that journey — an attempt to understand something simple and beautiful using the tools of science and imagination.