Start the mic to begin.
Sound is essentially a vibration that travels through the air as a wave. In this visualizer, Frequency (measured in Hertz) represents how fast those vibrations occur—the faster the vibration, the higher the musical note. A piano's scale is built on these mathematical frequencies; for example, the note A4 is exactly 440 vibrations per second. In this graph we use the equation y = sin(2π * f * t). The 2π represents 1 full rotation or 360 degrees, which is the amount of rotation for the sinusoid to reach 1 full rotation. The f in the equation represnts the specific frequency of the sound being transmitted.
The frequecny domain provides us with all the information we need to re-create the sound depicted in the wave segment. Each bar in the bar chart represents a sinusoid at a fixed frequency. The sound produced from the piano's scale compared to other intruments used different relative amplitudes to produce the same pitch. Fourier's theormem is that it is theoretically possible to play the symphonies of Beethoven with tuning forks, in a way that is audibly indistinguishable from an orchestra.
All sound played out of digital devices such as your TV, phone, and computer is stored as data in the frequency domain, rather than the time domain. Frequencies are much easier to store because they are a set of discrete values. This allows recording software to store the best possilbe sound with the least possilbe information. When the information is played back as sound, the spectrum of remaining frequencies is reconverted into a wave in the time domain. This is done through what is called the Fast Fourier Transform, a computer algorithm that converts the wave into its frequencies in real time.
When you use Sound Mode, your microphone captures the air pressure hitting the sensor and translates it into a digital waveform. By recording a segment, we track the "envelope" or the volume peaks of your voice, allowing you to see the unique energy patterns and valleys created when you speak or sing.