@inproceedings{1ddb5ae244104ae29d75e76be998de9c,
title = "A robust framework for tamper detection in digital recorded voice signals",
abstract = "This paper focuses on the tampering detection and pinpointing the manipulated region in digital recorded voice signals via blind semi-fragile watermark embedded in the frequency domain using the Fast Fourier Transform and Quantization Index Modulation-Dither Modulation. The proposed method has been evaluated with several male and female recorded voice signals. The designed method can provide non-audible perceptible difference between the original and the watermarked voice signals obtaining an average Signal-to-Noise Ratio of 44dB, providing resistance to various MP3 compression rates. The simulation results of the parallel implementation of the proposed technique on multicore central processing unit platform has shown efficient performance in a real-time environment.",
keywords = "Inaudibility, Multi-core central processing unit, Parallel programing, Quantization Index Modulation-Dither Modulation, Speech watermarking, Tamper detection",
author = "Adriana Bernal-Pati{\~n}o and Ponomaryov, {Volodymyr I.} and Rogelio Reyes-Reyes and Clara Cruz-Ramos",
note = "Publisher Copyright: Copyright {\textcopyright} 2019 SPIE.; Real-Time Image Processing and Deep Learning 2019 ; Conference date: 15-04-2019 Through 16-04-2019",
year = "2019",
doi = "10.1117/12.2518495",
language = "Ingl{\'e}s",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Nasser Kehtarnavaz and Carlsohn, {Matthias F.}",
booktitle = "Real-Time Image Processing and Deep Learning 2019",
address = "Estados Unidos",
}