Real time implementation of MELP speech compression algorithm using Blackfin processors

Cristina-Loredana Duta, L. Gheorghe, N. Tapus
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引用次数: 6

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.
使用Blackfin处理器实时实现MELP语音压缩算法
语音编码算法的大部分最新研究都是出于获得安全军事通信的需要,以便在敌对环境中有效操作。由于通信信道的带宽是军事应用中的一个敏感问题,因此通常采用低比特率的语音压缩方法。一些语音处理应用,如混合激励线性预测,其特点是在功耗、尺寸和电压供应方面有非常严格的要求。考虑到要实现的功能的复杂性和数量,以及输入信号的实时性要求和大动态范围,这些要求很难实现。为了满足这些限制,应该在各个层面进行仔细的优化,从算法层面,到系统和电路架构,再到单元库的布局和设计。这种优化的关键点包括:算法的选择、修改算法以降低计算复杂度、定点运算单元的选择、算法每个节点所需比特数的最小化,以及算法和体系结构之间的仔细匹配。本文研究了低比特率语音编码技术,主要是MELP,并解决了MELP在数字信号处理器平台上的程序优化问题。将该算法移植到定点DSP Blackfin 537上,逐级优化以满足实时性要求。所涉及的主要功能有分析、参数编码、参数解码和综合。在MELP前端的固定点源代码也在C级进行了彻底优化。内存优化技术(如数据放置和缓存)也用于减少处理时间。结果表明,基于MELP标准的低比特率通信(2400 bps)语音声码器在DSP平台上的实时实现是成功的。
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