Research on Objective Evaluation of Recording Audio Restoration Based on Deep Learning Network
Joint Authors
Jin, Cong
Zhao, Wei
Wang, Hongliang
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-18
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
There are serious distortion problems in the history audio and video data.
In view of the characteristics of audio data repair, the intelligent technology of audio evaluation is explored.
As the traditional audio subjective evaluation method requires a large number of personal to audition and evaluation, the tester’s subjective sense of hearing deviation and sample space data limited the impact of the accuracy of the experiment.
Based on the deep learning network, this paper designs an objective quality evaluation system for historical audio and video data and evaluates the performance of the system and the audio signal quality from the perspective of feature extraction and network parameter selection.
Experiments show that the system has good performance in this experiment; the predictive results and subjective evaluation of the correlation and dispersion indicators are good, up to 0.91 and 0.19.
American Psychological Association (APA)
Jin, Cong& Zhao, Wei& Wang, Hongliang. 2018. Research on Objective Evaluation of Recording Audio Restoration Based on Deep Learning Network. Advances in Multimedia،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1118423
Modern Language Association (MLA)
Jin, Cong…[et al.]. Research on Objective Evaluation of Recording Audio Restoration Based on Deep Learning Network. Advances in Multimedia No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1118423
American Medical Association (AMA)
Jin, Cong& Zhao, Wei& Wang, Hongliang. Research on Objective Evaluation of Recording Audio Restoration Based on Deep Learning Network. Advances in Multimedia. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1118423
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1118423