Feature extraction

1. Speech Processing
Feature Extraction
By.Mohamed Essam

2. Sound Feature
Sound features can be used to detect speakers, detect the
gender, the age, diseases and much more through the voice.

3. Energy
The energy of a signal is the total magnitude of the signal,
i.e. how loud the signal is(Can use it as a classifier if
someone anger or not..
. It is defined as:
[E(x) = sum_n {mid x(n) mid}^2]

4. Tempo
(BPM).
An estimate of the tempo in Beats Per Minute:
the rate of speed of a musical piece or passage .
Like a heartbeat, it can also be thought of as the 'pulse' of
the music. Tempo is measured in BPM, or beats pe
-can indicate that someone are arrested.

5. Zero Crossing Rate
The zero-crossing rate (ZCR) is the rate at which a signal
changes from positive to zero to negative or from negative to
zero to positive. Its value has been widely used in both
speech recognition and music information retrieval, being a
key feature to classify percussive sounds. is an indicator
function.

7. Spectrogram
Ever heard of a spectrogram? It’s a 2D plot between time and
frequency where each point in the plot represents the
amplitude of a particular frequency at a particular time in
terms of intensity of color. In simple terms, the spectrogram
is a spectrum (broad range of colors) of frequencies as it
varies with time.

9. Spectral Centroid
The spectral centroid is a measure used in
digital signal processing to characterise a
spectrum. It indicates where the center of mass
of the spectrum is located. Perceptually, it has a
robust connection with the impression of
brightness of a sound.

10. Spectral Centroid
The spectral centroid is a measure that
indicates where the “center of mass” of the
spectrum is. Perceptually, it has a robust
connection with the impression of “brightness”
of a sound, and therefore is used to
characterise musical timbre.