Use TorchAudio to Prepare Audio Data for Deep Learning - Real Python
Briefly

The article introduces essential technical terms related to audio processing, emphasizing the importance of understanding waveforms, amplitude, and frequency. A waveform visualizes sound as it travels, highlighting amplitude as the loudness indicator and frequency as the rate at which sound waves repeat. Concepts like decibels (dB) and hertz (Hz) are vital for manipulating audio and grasping how different sound properties interact. Each term is crucial for anyone looking to handle audio data effectively, especially in a technical environment like TorchAudio.
A waveform is the visual representation of sound as it travels through air over time, capturing the pressure changes in audio.
Amplitude reflects the strength of a sound wave, indicating how loud the sound is. It's an important aspect of audio processing.
Frequency is measured in hertz (Hz) and determines how many times a sound wave repeats in a second, influencing musical notes.
In digital audio, amplitude is measured in decibels (dB) or a normalized value between -1 and 1, affecting volume adjustments.
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