摘要
代数码激励线性预测算法(ACELP)是目前诸多低速率语音编码标准的算法核心,包括3G语音标准VSELP、AMR、AMR-NB、AMR-WB.该算法基于码激励线性预测模型,通过对码本的有效搜索,确定基音延迟,算法时间复杂度为O(n3).本文在ACELP算法基础上,对ACELP中自适应码本搜索过程进行改进,提出E-ACELP算法.通过AMR标准中8种速率情况的仿真,E-ACELP算法码本搜索时间减少、时间复杂度下降.基于E-ACELP算法,语音编码标准性能和效率得到提高.
The algebra code - excited linear prediction (ACELP) is the core algorithm of a lot of low bit rate speech coding standards, including the 3G speech standard VSELP, AMR, AMR - NB, AMR - WB. The algorithm is based on code excited linear prediction model. The pitch delay is determined by the effective codebook search. The algorithm' s time complexity is O (n^3). Based on the ACELP,this paper proposes an improved algorithm called E - ACELP. E - ACELP reduces the time of codebook search and time complexity through the simulation of eight ratios for AMR. The performance and efficiency of the standards based on ACELP are improved.
出处
《南华大学学报(自然科学版)》
2010年第2期47-51,共5页
Journal of University of South China:Science and Technology
基金
湖南省教育厅基金资助项目(09C855)
关键词
代数码激励线性预测
自适应码本搜索
时间复杂度
algebra code - excited linear prediction
search for adaptive eodebook
time complexity