log-mel energies

Log-mel energies are a type of feature extraction commonly used in audio signal processing and machine learning. They are created by first dividing an audio signal into small segments, and then calculating the power spectrum of each segment using a Fourier transform. The power spectrum is then converted to mel-scale frequencies, which are used to create a mel-spectrogram. Finally, the logarithm of the mel-spectrogram values are taken, resulting in the log-mel energies. These features are often used as inputs for machine learning algorithms that classify or analyze audio signals.