The multi-bit watermarking method for speech signals in the time-frequency domain

Al-khassaweneh, Mahmood; Al-zoubi, Hussien; Aviyente, Selin

doi:10.3233/ica-2010-0329

ICA

2010

DOI: 10.3233/ica-2010-0329

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The multi-bit watermarking method for speech signals in the time-frequency domain

Mahmood Al-khassaweneh

Hussien Al-zoubi

Selin Aviyente

Abstract: In this paper, we introduce a new multi-bit watermarking method for speech signals in the joint time-frequency domain. For this purpose, we compute the Wigner distribution of the speech signal and embed the watermark in a subset of time-frequency cells. The problem of synthesizing the signal from the watermarked Wigner distribution is discussed and a simple algorithm to reconstruct the speech signal from its Wigner distribution is proposed. The performance of the proposed watermarking algorithm is illustrated … Show more

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Cited by 4 publications

References 28 publications

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Towards Artificial Speech Therapy: A Neural System for Impaired Speech Segmentation

Iliya

Neri

2016

Int. J. Neur. Syst.

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This paper presents a neural system-based technique for segmenting short impaired speech utterances into silent, unvoiced, and voiced sections. Moreover, the proposed technique identifies those points of the (voiced) speech where the spectrum becomes steady. The resulting technique thus aims at detecting that limited section of the speech which contains the information about the potential impairment of the speech. This section is of interest to the speech therapist as it corresponds to the possibly incorrect movements of speech organs (lower lip and tongue with respect to the vocal tract). Two segmentation models to detect and identify the various sections of the disordered (impaired) speech signals have been developed and compared. The first makes use of a combination of four artificial neural networks. The second is based on a support vector machine (SVM). The SVM has been trained by means of an ad hoc nested algorithm whose outer layer is a metaheuristic while the inner layer is a convex optimization algorithm. Several metaheuristics have been tested and compared leading to the conclusion that some variants of the compact differential evolution (CDE) algorithm appears to be well-suited to address this problem. Numerical results show that the SVM model with a radial basis function is capable of effective detection of the portion of speech that is of interest to a therapist. The best performance has been achieved when the system is trained by the nested algorithm whose outer layer is hybrid-population-based/CDE. A population-based approach displays the best performance for the isolation of silence/noise sections, and the detection of unvoiced sections. On the other hand, a compact approach appears to be clearly well-suited to detect the beginning of the steady state of the voiced signal. Both the proposed segmentation models display outperformed two modern segmentation techniques based on Gaussian mixture model and deep learning.

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Towards Artificial Speech Therapy: A Neural System for Impaired Speech Segmentation

Iliya

Neri

2016

Int. J. Neur. Syst.

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A Digital Watermarking Algorithm for Color Image Based on DWT

2013

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Spatio-temporal resolution enhancement of vocal tract MRI sequences based on image registration

Martins

Mascarenhas

Suazo

2011

ICA

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Dynamic magnetic resonance imaging (MRI) is an emerging technique for studying speech production. In general, vocal tract image sequences are acquired during the speech of a word or phoneme. Sequences allow the identification of shapes taken by the vocal tract during speech production. However, there is no prior knowledge about the spatial and temporal resolution requirements, which are expected to vary for different speech tasks. Available approaches try to enhance the resolution of the images by empowering the acquisition devices, which can be very expensive. In this paper, we propose an alternative approach to enhance temporal resolution based solely on the observed image sequences. We use a previous non-rigid image registration method, which provides an intuitive background for temporal resolution enhancement. Based on a motion compensated interpolation (MCI) approach, intermediate images are coherent with the movement present in the whole sequence. Results indicate the effectiveness of our approach.

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The multi-bit watermarking method for speech signals in the time-frequency domain

Cited by 4 publications

References 28 publications

Towards Artificial Speech Therapy: A Neural System for Impaired Speech Segmentation

Towards Artificial Speech Therapy: A Neural System for Impaired Speech Segmentation

A Digital Watermarking Algorithm for Color Image Based on DWT

Spatio-temporal resolution enhancement of vocal tract MRI sequences based on image registration

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