Evaluation of digital watermarking on subjective speech quality

New methods of securing the distribution of audio content have been widely deployed in the last twenty years. Their impact on perceptive quality has, however, only been seldomly the subject of recent extensive research. We review digital speech watermarking state of the art and provide subjective testing of watermarked speech samples. Latest speech watermarking techniques are listed, with their specifics and potential for further development. Their current and possible applications are evaluated. Open-source software designed to embed watermarking patterns in audio files is used to produce a set of samples that satisfies the requirements of modern speech-quality subjective assessments. The patchwork algorithm that is coded in the application is mainly considered in this analysis. Different watermark robustness levels are used, which allow determining the threshold of detection to human listeners. The subjective listening tests are conducted following ITU-T P.800 Recommendation, which precisely defines the conditions and requirements for subjective testing. Further analysis tries to determine the effects of noise and various disturbances on watermarked speech’s perceived quality. A threshold of intelligibility is estimated to allow further openings on speech compression techniques with watermarking. The impact of language or social background is evaluated through an additional experiment involving two groups of listeners. Results show significant robustness of the watermarking implementation, retaining both a reasonable net subjective audio quality and security attributes, despite mild levels of distortion and noise. Extended experiments with Chinese listeners open the door to formulate a hypothesis on perception variations with geographical and social backgrounds.

Speech Watermarking Method Using McAdams Coefficient Based on Random Forest Learning

Speech watermarking has become a promising solution for protecting the security of speech communication systems. We propose a speech watermarking method that uses the McAdams coefficient, which is commonly used for frequency harmonics adjustment. The embedding process was conducted, using bit-inverse shifting. We also developed a random forest classifier, using features related to frequency harmonics for blind detection. An objective evaluation was conducted to analyze the performance of our method in terms of the inaudibility and robustness requirements. The results indicate that our method satisfies the speech watermarking requirements with a 16 bps payload under normal conditions and numerous non-malicious signal processing operations, e.g., conversion to Ogg or MP4 format.

A Robust Digital Speech Watermarking Based on Least Significant Bit

Watermarking is a technique to ensure the original information and to validate the digital content. Watermarking is required because of the rise in the utilization of the internet in one's everyday life. As the usage of digital content is developing quickly, there are numerous occurrences where information is uncertain. Watermarking is a procedure to conceal information for authorization reasons. Watermarking is the ideal approach to make sure about the digital content. Watermarking should be possible through different strategies. Least Significant Bit Watermarking (LSBW) strategy is one of them. Right now, pixel estimations of the image are changed over into binary. The data is covered in the bits of the pixel esteems. Watermarking consistently infers embedding of furtive signal that should be robust and imperceptible within the host data. In order to cater its robustness and imperceptibility, the energy of the watermark is accommodated to the energy of speech components.