scholarly journals Assistive Model to Generate Chord Progressions Using Genetic Programming with Artificial Immune Properties

2020 ◽  
Vol 10 (17) ◽  
pp. 6039
Author(s):  
María Navarro-Cáceres ◽  
Javier Félix Merchán Sánchez-Jara ◽  
Valderi Reis Quietinho Leithardt ◽  
Raúl García-Ovejero
Keyword(s):  
Artificial Immune System ◽  
Objective Measure ◽  
Musical Composition ◽  
Perceptual Quality ◽  
Voice Leading ◽  
Artificial Immune ◽  
Tonal Music ◽  
Perceptual Evaluation ◽  
Perceptual Distance

In Western tonal music, tension in chord progressions plays an important role in defining the path that a musical composition should follow. The creation of chord progressions that reflects such tension profiles can be challenging for novice composers, as it depends on many subjective factors, and also is regulated by multiple theoretical principles. This work presents ChordAIS-Gen, a tool to assist the users to generate chord progressions that comply with a concrete tension profile. We propose an objective measure capable of capturing the tension profile of a chord progression according to different tonal music parameters, namely, consonance, hierarchical tension, voice leading and perceptual distance. This measure is optimized into a Genetic Program algorithm mixed with an Artificial Immune System called Opt-aiNet. Opt-aiNet is capable of finding multiple optima in parallel, resulting in multiple candidate solutions for the next chord in a sequence. To validate the objective function, we performed a listening test to evaluate the perceptual quality of the candidate solutions proposed by our system. Most listeners rated the chord progressions proposed by ChordAIS-Gen as better candidates than the progressions discarded. Thus, we propose to use the objective values as a proxy for the perceptual evaluation of chord progressions and compare the performance of ChordAIS-Gen with chord progressions generators.

Singular Values Decomposition and Lifting Wavelet Transform for Speech Signal Embedding into Digital Image

2019 ◽  
Vol 12 (2) ◽  
pp. 138-151
Author(s):  
Mourad Talbi ◽  
Med Salim Bouhlel
Keyword(s):  
Wavelet Transform ◽  
Speech Signal ◽  
Signal To Noise Ratio ◽  
Perceptual Quality ◽  
Lifting Wavelet Transform ◽  
Signal To Noise ◽  
Perceptual Evaluation ◽  
Lifting Wavelet ◽  
Noise Ratio

Background: In this paper, we propose a secure image watermarking technique which is applied to grayscale and color images. It consists in applying the SVD (Singular Value Decomposition) in the Lifting Wavelet Transform domain for embedding a speech image (the watermark) into the host image. Methods: It also uses signature in the embedding and extraction steps. Its performance is justified by the computation of PSNR (Pick Signal to Noise Ratio), SSIM (Structural Similarity), SNR (Signal to Noise Ratio), SegSNR (Segmental SNR) and PESQ (Perceptual Evaluation Speech Quality). Results: The PSNR and SSIM are used for evaluating the perceptual quality of the watermarked image compared to the original image. The SNR, SegSNR and PESQ are used for evaluating the perceptual quality of the reconstructed or extracted speech signal compared to the original speech signal. Conclusion: The Results obtained from computation of PSNR, SSIM, SNR, SegSNR and PESQ show the performance of the proposed technique.

scholarly journals Voice Conversion Using a Perceptual Criterion

2020 ◽  
Vol 10 (8) ◽  
pp. 2884
Author(s):  
Ki-Seung Lee
Keyword(s):  
Voice Conversion ◽  
Spectral Envelope ◽  
Perceptual Quality ◽  
Speech Signals ◽  
Perceptual Evaluation ◽  
Perceptual Distance ◽  
Modification Factor ◽  
Maximum Improvement ◽  
Validation Tests ◽  
Conversion Rules

In voice conversion (VC), it is highly desirable to obtain transformed speech signals that are perceptually close to a target speaker’s voice. To this end, a perceptually meaningful criterion where the human auditory system was taken into consideration in measuring the distances between the converted and the target voices was adopted in the proposed VC scheme. The conversion rules for the features associated with the spectral envelope and the pitch modification factor were jointly constructed so that perceptual distance measurement was minimized. This minimization problem was solved using a deep neural network (DNN) framework where input features and target features were derived from source speech signals and time-aligned version of target speech signals, respectively. The validation tests were carried out for the CMU ARCTIC database to evaluate the effectiveness of the proposed method, especially in terms of perceptual quality. The experimental results showed that the proposed method yielded perceptually preferred results compared with independent conversion using conventional mean-square error (MSE) criterion. The maximum improvement in perceptual evaluation of speech quality (PESQ) was 0.312, compared with the conventional VC method.

A Relative Fractal Dimension Spectrum for a Perceptual Complexity Measure

2011 ◽  
pp. 381-395
Author(s):  
W. Kinsner ◽  
R. Dansereau
Keyword(s):  
Fractal Dimension ◽  
Probability Distributions ◽  
Objective Measure ◽  
Mean Opinion Score ◽  
Perceptual Quality ◽  
Dimension Spectrum ◽  
Opinion Score ◽  
Single Scale ◽  
Scale Measure

This article presents a derivation of a new relative fractal dimension spectrum, DRq, to measure the dis-similarity between two finite probability distributions originating from various signals. This measure is an extension of the Kullback-Leibler (KL) distance and the Rényi fractal dimension spectrum, Dq. Like the KL distance, DRq determines the dissimilarity between two probability distibutions X and Y of the same size, but does it at different scales, while the scalar KL distance is a single-scale measure. Like the Rényi fractal dimension spectrum, the DRq is also a bounded vectorial measure obtained at different scales and for different moment orders, q. However, unlike the Dq, all the elements of the new DRq become zero when X and Y are the same. Experimental results show that this objective measure is consistent with the subjective mean-opinion-score (MOS) when evaluating the perceptual quality of images reconstructed after their compression. Thus, it could also be used in other areas of cognitive informatics.

scholarly journals A Computational Model of Tonal Tension Profile of Chord Progressions in the Tonal Interval Space

Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1291
Author(s):  
María Navarro-Cáceres ◽  
Marcelo Caetano ◽  
Gilberto Bernardes ◽  
Mercedes Sánchez-Barba ◽  
Javier Merchán Sánchez-Jara
Keyword(s):  
State Of The Art ◽  
Objective Measure ◽  
Global Changes ◽  
Voice Leading ◽  
Relative Importance ◽  
Tonal Music ◽  
Harmonic Motion ◽  
Proposed Model ◽  
Interval Space ◽  
Over Time

In tonal music, musical tension is strongly associated with musical expression, particularly with expectations and emotions. Most listeners are able to perceive musical tension subjectively, yet musical tension is difficult to be measured objectively, as it is connected with musical parameters such as rhythm, dynamics, melody, harmony, and timbre. Musical tension specifically associated with melodic and harmonic motion is called tonal tension. In this article, we are interested in perceived changes of tonal tension over time for chord progressions, dubbed tonal tension profiles. We propose an objective measure capable of capturing tension profile according to different tonal music parameters, namely, tonal distance, dissonance, voice leading, and hierarchical tension. We performed two experiments to validate the proposed model of tonal tension profile and compared against Lerdahl’s model and MorpheuS across 12 chord progressions. Our results show that the considered four tonal parameters contribute differently to the perception of tonal tension. In our model, their relative importance adopts the following weights, summing to unity: dissonance (0.402), hierarchical tension (0.246), tonal distance (0.202), and voice leading (0.193). The assumption that listeners perceive global changes in tonal tension as prototypical profiles is strongly suggested in our results, which outperform the state-of-the-art models.

scholarly journals Micro Artificial Immune System for Traffic Light Control

2020 ◽  
Vol 10 (21) ◽  
pp. 7933
Author(s):  
Raul Galvan-Correa ◽  
Mauricio Olguin-Carbajal ◽  
Juan Carlos Herrera-Lozada ◽  
Jacobo Sandoval-Gutierrez ◽  
José Félix Serrano-Talamantes ◽  
...  
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Flow Simulation ◽  
Specific Region ◽  
Urban Mobility ◽  
Artificial Immune ◽  
Traffic Light ◽  
Traffic Lights ◽  
Traffic Light Control

A new bio-inspired meta-heuristic, called the micro artificial immune system (MAIS), has been developed in order to reduce the rates of pollution for a specific region of Mexico City through the optimization of vehicular flow. Simulation of urban mobility (SUMO) was used to simulate the effects of the programming of the traffic lights obtained by the MAIS. Currently, pollution and travel times from one place to another are increasing due to the number of inhabitants that live in big cities, which has generated a decrease in people’s quality of life. Hence, we propose the optimization of the programming of the sequences of traffic lights through this bio-inspired meta-heuristic. The obtained results show that the MAIS outperforms most of the algorithms tested in this research.

Artificial Immune System for Multi-Area Economic Dispatch

2013 ◽  
Vol 14 (6) ◽  
pp. 581-590 ◽  
Author(s):  
Shankha Suvra De ◽  
Abhik Hazra ◽  
Mousumi Basu
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Clonal Selection ◽  
Economic Dispatch ◽  
Artificial Immune ◽  
Promising Alternative ◽  
Alternative Approach ◽  
Real Coded Genetic Algorithm ◽  
Tournament Selection

Abstract This article presents artificial immune system for solving multi-area economic dispatch (MAED) problem with tie line constraints considering transmission losses, multiple fuels, valve-point loading and prohibited operating zones. Artificial immune system is based on the clonal selection principle which implements adaptive cloning, hyper mutation, aging operator and tournament selection. The effectiveness of the proposed algorithm has been verified on three different test systems, both small and large, involving varying degree of complexity. Compared with differential evolution, evolutionary programming and real-coded genetic algorithm, considering the quality of the solution obtained, the proposed algorithm seems to be a promising alternative approach for solving the MAED problems in practical power system.

scholarly journals Artificial Immune System (AIS)-Based Location Management Scheme in Mobile Cellular Networks

2018 ◽  
Author(s):  
Sanjay Kumar Biswash ◽  
Mahasweta Sarkar ◽  
Dhirendra Kumar Sharma
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Location Management ◽  
Personal Communication ◽  
Rule Base ◽  
Base System ◽  
Artificial Immune ◽  
Signaling Cost ◽  
Management Procedure

In this paper, we are proposing a bio-inspired location management (LM) technique for personal communication system (PSC). It is based on artificial immune system (AIS), with self-adaptation and self-updates attributes in order to perform the location management, and work helps to achieve the better quality of service (QoS) and quality of experience (QoE) for the mobile users. Here, we are suggesting a modified mobile switching center (MSC) architecture, and an adaptive self-modified location management procedure. The proposed mobile switching centre architecture has an advantage of rule-based and fact-based system to store the rules and fact related to location management procedure, and it shows the intelligent behavior of system. The mobile switching centre calculates the best method for location management and rule-base system trigged the rules to perform the techniques. The system stores the result (techniques for location management) in fact-base system for future use. The efficiency and effectiveness of the proposed techniques been analyzed, and it observed that the proposed system has 45-50% improvement in performance over the current location management techniques. Here, we are taking the performance parameters such as signaling cost, database update cost, overhead measurement, mobility management cost.

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