Speech Compression using Analysis by Synthesis

Linear prediction plays a fundamental role in all aspects of speech. Its use seems natural and obvious since for a speech signal the value of its current sample can be well modeled as a linear combination of its past values. Calculation for predictor coefficients with the help of automatic code generation gives the solution for early and efficient computing. Automatic code generation is a fast paced technology with lots of new capabilities and customer experiences. In this, Simulink is the leading environment for modeling and simulating a broad range of dynamic systems. It is the foundation for Model-Based Design, with support for multi-domain modeling and simulation, automatic code generation for production use and real-time testing, and a range of capabilities for verification and validation. With its open architecture and APIs, the integration of models from other tools or languages such as C\C++ is possible. Also embedded coder with Simulink can generate C code for target specific applications. The proposed system implements a model based design by using the linear prediction coefficients of the encoded speech data and prove to be the promising method for speech compression.