Encoding Detection and Bit Rate Classification of AMR-Coded Speech Based on Deep Neural Network-Reference-Cited by-同舟云学术

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Encoding Detection and Bit Rate Classification of AMR-Coded Speech Based on Deep Neural Network

Published:2018 Issue:1 Volume:E101.D Page:269-272
ISSN:0916-8532
Container-title:IEICE Transactions on Information and Systems
language:en
Short-container-title:IEICE Trans. Inf. & Syst.

Author:

SHIN Seong-Hyeon¹,JANG Woo-Jin¹,YUN Ho-Won¹,PARK Hochong¹

Affiliation:

1. Department of Electronics Engineering, Kwangwoon University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://www.jstage.jst.go.jp/article/transinf/E101.D/1/E101.D_2017EDL8155/_pdf

Reference9 articles.

1. [1] B. D'Alessandro and Y.Q. Shi, “MP3 bit rate quality detection through frequency spectrum analysis,” Proc. 11th ACM Workshop on Multimedia and Security, pp.57-61, 2009. 10.1145/1597817.1597828

2. [2] T. Bianchi, A. De Rosa, M. Fontani, G. Rocciolo, and A. Piva, “Detection and classification of double compressed MP3 audio tracks,” Proc. 1st ACM Workshop on Information Hiding and Multimedia Security, pp.159-164, 2013. 10.1145/2482513.2482523

3. [3] D. Luo, W. Luo, R. Yang, and J. Huang, “Identifying compression history of wave audio and its applications,” ACM Trans. Multimedia Computing, Communications and Applications, vol.10, no.3, pp.30:1-30:19, 2014. 10.1145/2575978

4. [4] D. Seichter, L. Cuccovillo, and P. Aichroth, “AAC encoding detection and bitrate estimation using a convolutional neural network,” Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, pp.2069-2073, 2016. 10.1109/icassp.2016.7472041

5. [5] 3GPP TS 26.090, “Adaptive multi-rate (AMR) speech codec,” June 2002.

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