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基于正弦模型的线性预测低速率语音编码算法研究

Research on Linear Predictive Speech Coding Based on Sinusoidal Model at Low-Bit-Rates

【作者】 黄鹤

【导师】 鲍长春;

【作者基本信息】 北京工业大学 , 电路与系统, 2002, 硕士

【摘要】 随着通信网的不断发展,高质量的低速率语音编码成为目前研究的热点。本文以北京工业大学通信与信号处理研究室开发的2.4kb/s谐波激励线性预测(HELP)低速率语音编码算法为基础,针对进一步提高语音质量的问题,研究了一系列改进方法。 首先,本文通过对HELP算法的深入分析,根据语音信号谐波相关程度能反映浊音度强弱的性质,开发了一种基于最小均方误差准则的谐波相关浊音度参数提取方法。其次,本文开发了一种高效频域基音检测方法,使基音检测结果精确到分数样点。最后本文根据最小相位假设研究了一种谐波相位的恢复方法。计算机仿真及主观试听结果表明,本文提出的这些改进方案有效地改善了2.4kb/sHELP语音编码的语音质量。

【Abstract】 With the development of the Telecommunication network, high quality speech coding at low bit rates has become research focus. Some new methods are presented in this paper to improve the quality of Harmonic Excited Linear Predictive (HELP) coding which Telecommunication and Signal Processing Laboratory in Beijing Polythenic University develop.First, after deeply investigating HELP model, a harmonic related voicing detection algorithm based on MSE criterion is developed, with the knowledge that voicing algorithm can be showed by degree of harmonic relation. Second, efficient pitch detection is developed in frequency domain, which find fractional pitch. Finally, harmonic phase reconstruction that exploits minimum-phase model is proposed. Computer simulation and subject listening test show that the algorithm of this paper can efficiently improve the quality of reconstructed speech of 2.4kb/s HELP speech coding.

  • 【分类号】TN912.3
  • 【被引频次】3
  • 【下载频次】226
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