Application of DSP techniques to speech communication involves three main topics:

1. Representation of speech signals in digital form

Speech signals can be represented into two broups. They are:

• Waveform representations are concerned with preserving the "Wave Shape' of the analog specch signal through a sampling and quantization process. Some of the waveform coding techniques are Adaptive Pulse Code Modulation (APCM), Differential Pulse Code Modulation (DPCM) and Adaptive Differential Pulse Code Modulation (ADPCM).
• Parametric representations are concerned with representing the speech signal as the output of a model for speech production. The speech signal is sampled and quantized and then processed to obtain the parameters of the mode. The parameters of this model are classified as either excitation parameters (i.e, related to the source of speech sounds) or vocal tract response parameters (i.e., related to the individual speech sounds). Some of the parametric methods of speech coding are Linear Prediction Coding (LPC), Mel-Frequency Cepstrum Coefficients $(\mathrm{MFCC})$ , Code Excited Linear Predictive Coding $(\mathrm{CELP})$ and Vector Sum Excited Linear Prediction (VSELP).

2. Implementation of sophisticated processing techniques

With the help of signal processing techniques the digitally represented voice signal is transformed into alternate forms which are more appropriate to specific applications. It includes

• Speech coding: It is the process of capturing the speech of a person and processing it to transmit over a communication channel. Speech coding is applied in the area of telephony, narrow-band cellular radio, military communication etc.
• Speech Enhancement: It is a process of minimizing the derogatory effects of noise on the performance of speech communication, source coding etc. Speech enhancement is applied in the areas where the performance of equipment is improved in noisy atmosphere like, factories etc.

3. Type of applications

The major applications of DSP techniques in speech processing are divided into three groups:

• Speech Analysis: It is used in automatic speech recognition, speaker verification and speaker identification. Other applications include banking from distant location, information retrieval systems etc.
• Speech Synthesis: It is used in reading machines for the automatic conversion of written text into speech, and retrieval of data from computers in speech form by remote access through terminals or telephones.
• Speech Analysis and Synthesis: Speech data compression for an efficient use of the transmission medium is an example of the use of speech analysis followed by synthesis. Other applications are in voice alarms, reading machines for the dumb or blind, data-base enquiry services, voice scrambling for secure transmission, etc.