Abstract

A large part of the latest research in speech coding algorithms is motivated by the need of obtaining secure military communications, to allow effective operation in a hostile environment. Since the bandwidth of the communication channel is a sensitive problem in military applications, low bit-rate speech compression methods are mostly used. Several speech processing applications such as Mixed Excitation Linear Prediction are characterized by very strict requirements in power consumption, size, and voltage supply. These requirements are difficult to fulfill, given the complexity and number of functions to be implemented, together with the real time requirement and large dynamic range of the input signals. To meet these constraints, careful optimization should be done at all levels, ranging from algorithmic level, through system and circuit architecture, to layout and design of the cell library. The key points of this optimization are among others, the choice of the algorithms, the modification of the algorithms to reduce computational complexity, the choice of a fixed-point arithmetic unit, the minimization of the number of bits required at every node of the algorithm, and a careful match between algorithms and architecture. This paper concentrates on low bit rate speech coding technology, mainly in MELP and solved the problem of optimizing the program of MELP on Digital Signal Processor platform. The algorithm was ported onto a fixed point DSP, Blackfin 537, and stage by stage optimization was performed to meet the real time requirements. The main functions involved were analysis, parameter encoding, parameter decoding and synthesis. The fixed point source code at the MELP front end was also thoroughly optimized at the C Level. Memory optimization techniques such as data placement and caching were also used to reduce the processing time. The results we obtained show that real-time implementations of a speech vocoder based on the MELP standard for low bit rate communications (2400 bps) can be successful on DSP platforms.

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