  The time domain waveform of a speech signal carries all of the auditory
information. From the phonological point of view, it little can be said on the
basis of the waveform itself. However, past research in mathematics, acoustics,
and speech technology have provided many methods for converting data that can
be considered as information if interpreted correctly. In order to find some
statistically relevant information from incoming data, it is important to have
mechanisms for reducing the information of each segment in the audio signal
into a relatively small number of parameters, or features. These features
should describe each segment in such a characteristic way that other similar
segments can be grouped together by comparing their features. There are
enormous interesting and exceptional ways to describe the speech signal in
terms of parameters. Though, they all have their strengths and weaknesses, we
have presented some of the most used methods with their importance.
