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Echo-hiding has been widely studied for audio watermarking. This study proposes a more secure echo-hiding method based on modified pseudo-noise (PN) sequence and robust principal component analysis (RPCA). In the proposed method, the RPCA is used to decompose the original audio signal into low-rank and sparse parts and then a pair of opposite modified PN sequences is employed to embed watermarks. The modified PN sequence improves the robustness of watermark detection by providing additional correlation peaks. Meanwhile, benefit from the RPCA and the opposite PN sequences, the security of the proposed method is improved since watermarks cannot be detected from the whole signal even if the PN sequence is known, which is an obvious improvement compared with the previous PN-based echo-hiding methods. In the watermark detection process, the authors make use of the low-rank and sparse characteristics of the watermarked signal to detect watermarks from the low-rank and sparse parts, respectively. Based on this basic framework, they also propose a multi-bit embedding scheme, which obtains a doubled embedding capacity compared with the previous PN-based echo-hiding methods. The proposed method was evaluated with respect to inaudibility, security, and robustness. The experiment results verified the effectiveness of the proposed method.

This work proposes a simple but effective attention mechanism, namely Skip Attention (SA), for monaural singing voice separation (MSVS). First, the SA, embedded in the convolutional encoder-decoder network (CEDN), realizes an attention-driven and dependency modeling for the repetitive structures of the music source. Second, the SA, replacing the popular skip connection in the CEDN, effectively controls the flow of the low-level (vocal and musical) features to the output and improves the feature sensitivity and accuracy for MSVS. Finally, we implement the proposed SA on the Stacked Hourglass Network (SHN), namely Skip Attention SHN (SA-SHN). Quantitative and qualitative evaluation results have shown that the proposed SA-SHN achieves significant performance improvement on the MIR-1K dataset (compared to the state-of-the-art SHN) and competitive MSVS performance on the DSD100 dataset (compared to the state-of-the-art DenseNet), even without using any data augmentation methods.

Speech tampering has brought serious problems to speech security. Information hiding method can be used for tampering detection if it can satisfy several competitive requirements, e.g., inaudibility, robustness, blindness, and fragility. According to preliminary analysis, spectral envelope and formants are important indicators of tampering, since tampering the speech will unavoidably modify the shape of the spectral envelope and the locations/magnitudes of the formants. By taking advantage of this, this paper proposes a spectral manipulations based information hiding method for tampering detection in sparse domain. To robustly extract the embedded information, the Robust Principal Component Analysis (RPCA) is employed to decompose the original speech into sparse component and low-rank component. The sparse component which contains the main spectral envelope and formant structure is selected for information hiding/embedding via spectral manipulations, by controlling the shape and power of formants with line spectral frequencies (LSFs). Evaluation results suggest that the proposed method can satisfy inaudibility, robustness, and fragility. Furthermore, it is able to detect both the temporal tampering and acoustic feature based tampering with reasonable accuracy.

We build up phononic crystals (PCs) by attaching triangular pillars symmetrically to the double sides of a thin plate in the triangular lattice. The degeneracy of multiple Dirac cones is simultaneously lifted for the same PC plate, due to the mirror-inversion symmetry breaking caused by the rotation of triangular pillars; opposite Berry curves and valley Chern number are got at the lower and upper branches of each valley band. The multi-branch topological protected edge states are then created on the interface between PC plates with opposite topological phase. Interestingly enough, those edge states present various transverse symmetries and distinct robustness against sample imperfection such as cavity defect, rotation angle disorder, or sharp bending. Our results present the rich behaviors of multiple branches of topological edges.

International audience; We demonstrate experimentally and theoretically the broadband sub-diffraction and ultra-high energy density focusing of elastic wave inside planar gradient-index (GRIN) plate lenses based on thickness variation. The full width at half maximum is ~0.40 times the minimum wavelength inside the lens λ0 or ~1/11 times the incident wavelength in the background plate λB. We analytically elucidate the underlying physical mechanism as the rapid oscillations in the propagator function at the focal distance. Our design displays several advantages including the broadband sub-diffraction behavior, three-order of magnitudes higher energy intensity at the focal point, and focusing capacity with a narrow transverse width of the lens, over the usual metastructure and/or phononic crystal based GRIN lenses. The broadband sub-diffraction and ultra-high energy density focusing can be used for energy harvesting and signal sensing.

The method reported here realizes an inaudible echo-hiding based speech watermarking by using sparse subspace clustering (SSC). Speech signal is first analyzed with SSC to obtain its sparse and low-rank components. Watermarks are embedded as the echoes of the sparse component for robust extraction. Self-compensated echoes consisting of two independent echo kernels are designed to have similar delay offsets but opposite amplitudes. A one-bit watermark is embedded by separately performing the echo kernels on the sparse and low-rank components. As a result, the sound distortion caused by one echo signal can be quickly compensated by the other echo signal, which enables better inaudibility. Since the embedded echoes have the same sparsity as the sparse component, watermarks can be extracted with a basic cepstrum analysis even if the echo kernels are not directly performed on the original speech. The evaluation results verify the feasibility and effectiveness of this method.

The recent deep learning methods can offer state-of-the-art performance for Monaural Singing Voice Separation (MSVS). In these deep methods, the recurrent neural network (RNN) is widely employed. This work proposes a novel type of Deep RNN (DRNN), namely Proximal DRNN (P-DRNN) for MSVS, which improves the conventional Stacked RNN (S-RNN) by introducing a novel interlayer structure. The interlayer structure is derived from an optimization problem for Monaural Source Separation (MSS). Accordingly, this enables a new hierarchical processing in the proposed P-DRNN with the explicit state transfers between different layers and the skip connections from the inputs, which are efficient for source separation. Finally, the proposed approach is evaluated on the MIR-IK dataset to verify its effectiveness. The numerical results show that the P-DRNN performs better than the conventional S-RNN and several recent MSVS methods.

International audience; The modern acoustic circuits have experienced significant progress with the development of artificial structures, including phononic crystals, metamaterials or metasurfaces. Among the most intensive topics, the reconfigurable acoustic guides are achieved through several mechanisms. In this work, we report on the rainbow guiding for the lowest-order antisymmetric Lamb (A0) mode in a phononic crystal plate, where the linear waveguides are constituted by erecting aligned pillars either solid or hollow. We show both numerically and experimentally that the whispering gallery modes (WGMs) in the hollow pillars can be generated by the defect mode that propagates in the waveguide. Then, the reemission of A0 mode by the WGMs to the outer lateral areas can lead to spatial control of frequency selective wave guidance called ‘rainbow guiding’. Our approach allows for an accurate control of the wave guiding and facilitates the integration of waveguides within other devices in the acoustic circuits.

There have been serious issues concerning the protection of speech signals from malicious tampering. Digital watermarking has been paid much attention in solving this problem. This paper proposes a tampering detection approach based on speech watermarking by modifying the line spectral frequencies (LSFs). Watermarks are embedded into LSFs that derived from linear prediction (LP) analysis with dither modulation-quantization index modulation (DM-QIM). Minor modifications to LSFs introduced by quantization not only enable the watermarks to be inaudible to human auditory system but also provide the possibility of robustness against meaningful processing and fragility against tampering. We evaluated the proposed approach with objective evaluations with respect to inaudibility, robustness, and fragility. The results indicated that the proposed approach for tampering detection not only satisfied inaudibility but also provided good robustness against meaningful processing and fragility against malicious tampering.

Parameters of geomorphological characteristics are critical for research on yardangs. However, methods which are low-cost, accurate, and automatic or semi-automatic for extracting these parameters are limited. We present here semi-automatic techniques for this purpose. They are object-based image analysis (OBIA) and Canny edge detection (CED), using free, very high spatial resolution images from Google Earth. We chose yardang fields in Dunhuang of west China to test the methods. Our results showed that the extractions registered an overall accuracy of 92.26% with a Kappa coefficient of agreement of 0.82 at a segmentation scale of 52 using the OBIA method, and the exaction of yardangs had the highest accuracy at medium segmentation scales (138, 145). Using CED, we resampled the experimental image subset to a series of lower spatial resolutions for eliminating noise. The total length of yardang boundaries showed a logarithmically decreasing (R2 = 0.904) trend with decreasing spatial resolution, and there was also a linear relationship between yardang median widths and spatial resolutions (R2 = 0.95). Despite the difficulty of identifying shadows, the CED method achieved an overall accuracy of 89.23% with a kappa coefficient of agreement of 0.72, similar to that of the OBIA method at medium segmentation scale (138).

International audience; We report on the experimental evidence of the guiding of the lowest order antisymmetric Lamb mode (A0) through a compact waveguide consisting of aligned hollow pillars in between a square-latticed array of solid pillars on a thin slab. We analyze both numerically and experimentally the guiding achievements and we highlight the role played by the whispering gallery mode of the hollow pillars. In particular, we highlight the evolution of the displacement field pattern behind the waveguide that we relate to the emission of a quadrupolar wave interacting with the surrounding solid pillars. We also show the asymmetric transmission of a compact waveguide based on the same mechanism.

Automatic design of mechanical procedures solving abstract problems is a relevant scientific challenge. In particular, automatic design of membranes systems performing some prefixed tasks is an important and useful research topic in the area of Natural Computing. In this context, deterministic membrane systems were designed in order to capture the values of polynomials with natural numbers coefficients. Following that work, this paper extends the previous result to polynomials with integer numbers coefficients.Specifically,a deterministic transitionP system using priorities in the weak interpretation, associated with an arbitrary such kind polynomial, is presented. The configuration of the unique computation of the system will be encoded by means of two distinguished objects, the values of the polynomial for natural numbers. The descriptive computational resources required by the designed membrane system are also analyzed. Scientific Research Fund of Sichuan Provincial Science and Technology Department 2015JY0257 Scientific Research Fund of Sichuan Provincial Science and Technology Department 2017FZ0010 National Natural Science Foundation of China 61672437 National Natural Science Foundation of China No 61702428 Sichuan Science and Technology Program 2018GZ0185 Sichuan Science and Technology Program 2018GZ0085 Sichuan Science and Technology Program 2017GZ0159

This paper proposes a watermarking method for speech signals based on Robust Principal Component Analysis (RPCA) and formant manipulations. As the spectrogram of speech has a relatively sparse structure, the core information of speech is extracted into a sparse matrix using RPCA so that formants can be estimated with Linear Prediction (LP) more accurately even under noise/interferences, which significantly improves the robustness of proposed method. We investigate how the formants can be controlled and manipulated to make the watermarking method effective. Watermarks are embedded into speech by controlling the shape and power of formants using the stable and robust parameter, i.e., line spectral frequencies (LSFs). Evaluations regarding inaudibility and robustness are carried out and the results suggest that the proposed method can not only satisfy inaudibility but also provide good robustness against general processing and different speech codecs which is better than the other methods.

Automatic design of P systems is an attractive research topic in the community of membrane computing. Differing from the previous work that used evolutionary algorithms to fulfill the task, this paper presents the design of a (deterministic transition) P system (without input membrane) of degree 1, capturing the value of an arbitrary k-order (k 2) polynomial p(n) by using a reasoning method. Specifically, the values of p(n) corresponding to a natural number t is equal to the multiplicity of a distinguished object of the system (the output object) in the configuration at instant t. We also discuss the descriptive computational resources required by the designed k-order polynomial P system. Ministerio de Economía y Competitividad TIN2012-37434

We investigate the propagation of surface acoustic wave through phononic crystals (PCs) that consist of composite pillars, comprising of a cap metallic pillar and a bottom epoxy pillar on the semi-infinite substrate. The computation of band structures, together with measured transmission spectra, shows the important role of the bottom pillar in engineering the band structures for its Young's modulus one order of magnitude smaller than that of the cap pillar. We also discuss the conditions of ignoring the influences of the bottom pillar in PCs featuring extremely high cap pillars. We finally modify the height of the bottom pillar to engineer the band structures of PCs, leading to, in both the simulation and experiment, Fano resonance-like transmission in the long wavelength regime.