Sparse representation based quasi-clean speech construction for speech quality assessment under complex environments
Sparse representation based quasi-clean speech construction for speech quality assessment under complex environments
复制标题
基于稀疏表示的准干净语音构建，用于复杂环境下的语音质量评估
DOI：
10.1049/iet-spr.2016.0555
复制
发表时间：
2017
影响因子：
1.7
通讯作者：
Yanxiong Li
中科院分区：
文献类型：
--
作者：
Weili Zhou（学生）;Qianhua He;Yalou Wang;Yanxiong Li
A non-intrusive speech quality assessment method for complex environments was proposed. In the proposed approach, a new sparse representation-based speech reconstruction algorithm was presented to acquire the quasi-clean speech from the noisy degraded signal. Firstly, an over-complete dictionary of the clean speech power spectrum was learned by the K-singular value decomposition algorithm. Then in the sparse representation stage, the stopping residue error was adaptively achieved according to the estimated cross-correlation and the noise spectrum which was adjusted by a posteriori SNR-weighted factor, and the orthogonal matching pursuit approach was applied to reconstruct the clean speech spectrum from the noisy speech. The quasi-clean speech was considered as the reference to a modified PESQ perceptual model, and the mean opinion score of the noisy degraded speech was achieved via the distortions estimation between the quasi-clean speech and the degraded speech. Experimental results show that the proposed approach obtains a correlation coefficient of 0.925 on.NOIZEUS complex environment database, which is 99% similar to the performance of the intrusive standard ITU-T PESQ, and 7.1% outperforms non-intrusive standard ITU-T P.563.
