⏱️Time domain features describe the sound over time, providing information about amplitude, energy, and more.
🔊Frequency domain features focus on the frequency components of the sound, describing characteristics like spectral centroid and spectral spread.
🌀Time-frequency domain features combine time and frequency information, providing an overview of the sound's characteristics at different moments.
What are time domain features?
—Time domain features describe the sound over time, capturing properties like amplitude, energy, and temporal patterns.
What are frequency domain features?
—Frequency domain features focus on the frequency components of the sound, describing characteristics like spectral centroid, spectral flux, and spectral spread.
What are time-frequency domain features?
—Time-frequency domain features combine time and frequency information, providing a comprehensive view of the sound's characteristics at different moments.
How are time-frequency domain features obtained?
—Time-frequency domain features are obtained by applying the Short-Time Fourier Transform (STFT) to the time domain representation of the sound, resulting in a spectrogram.
Why are these categorization strategies important?
—These strategies help in understanding and analyzing audio signals for various applications, such as audio classification, music information retrieval, and audio processing.
00:00Introduction to strategies for categorizing audio features.
02:56Description of time domain features and their relevance in analyzing the sound over time.
04:36Explanation of frequency domain features and their focus on the frequency components of the sound.
08:20Introduction to time-frequency domain features, combining time and frequency information for a comprehensive understanding of the sound.
13:10Overview of spectrograms as a time-frequency domain feature obtained through the Short-Time Fourier Transform (STFT).
15:49Summary of the importance and applications of categorization strategies for audio features.
