MFCCpiirteiksi

MFCCpiirteiksi is a Finnish term that translates to "MFCC features" or "MFCC coefficients" in English. MFCC stands for Mel-frequency cepstral coefficients. These are a set of features widely used in speech recognition and audio processing.

The MFCC features are derived from an audio signal by first applying a Mel filter bank to the signal's power spectrum. The Mel scale is a perceptual scale of pitches judged by listeners to be equal in distance from one another. After filtering, the logarithm of the filter bank energies is taken. Finally, a discrete cosine transform (DCT) is applied to these log energies. The resulting coefficients are the MFCCs.

The MFCCs are designed to represent the short-term power spectrum of a sound, in a way that is characteristic of human auditory perception. They effectively capture the spectral envelope of the sound. Typically, a small number of the lowest-order MFCCs are retained, as they are considered to contain the most important information about the speech signal for recognition tasks. The higher-order coefficients tend to represent finer spectral details and noise, which are often less relevant.

These features are particularly effective because they decorrelate the spectral information, making them easier for machine learning models to process. They are a standard component in many modern speech recognition systems, as well as in other audio analysis applications such as speaker identification and music genre classification.