摘要
在网络传输过程中宽带音频会由于高频信息的缺失导致音频质量下降,因此,本文提出了一种基于局部最小二乘支持向量机的宽带向超宽带音频频带扩展方法.根据音频频域序列的非线性特性,本文采用相空间重构和局部最小二乘支持向量机对音频信号的高频频谱细节进行预测,并结合高斯混合模型对高频子带能量进行估计,最后经过高频频谱包络调整,所提方法能够有效地恢复7k Hz^14k Hz频率范围内的高频成分.主客观测试结果表明,该方法改善了宽带音频的听觉质量,其性能优于参考音频频带扩展方法.
The auditory quality of wideband audio is generally degraded due to the lack of the high-frequency in network transmission,so this paper presents a kind of audio bandwidth extension method from wideband to super wideband based on local least square support vector machine. In the light of the nonlinearity of audio spectrum,the high-frequency fine spectrum of audio signals is predicted by using phase space reconstruction and local least square support vector machine.Combining with the estimation of high-frequency sub-band energy based on Gaussian mixture model,the proposed method can effectively recover the high-frequency components in the frequency range 7k Hz ~ 14 k Hz through the envelope adjustment of high-frequency spectrum at last. Subjective and objective testing results indicate that the proposed method improves the auditory quality of wideband audio and outperforms the reference methods of audio bandwidth extension.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2016年第9期2203-2210,共8页
Acta Electronica Sinica
基金
国家自然科学基金项目(No.61072089
No.61471014)
关键词
音频编码
频带扩展
高斯混合模型
局部最小二乘支持向量机
audio coding
bandwidth extension
Gaussian mixture model
local least square support vector machine