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Summary Laryngeal images obtained via high-speed videoendoscopy are an invaluable source of information for the advancement of voice science because they can capture the true cycle-to-cycle vibratory characteristics of the vocal folds in addition to the transient behaviors of the phonatory mechanism, such as onset, offset, and breaks. This information is obtained through relating the spatial and temporal features from acquired images using objective measurements or subjective assessments. While these images are calibrated temporally, a great challenge is the lack of spatial calibration. Recently, a laser-projection system allowing for spatial calibration was developed. However, various sources of optical distortions deviate the images from reflecting the reality. The main purpose of this study was to evaluate the effect of the fiberoptic flexible endoscope distortions on the calibration of images acquired by the laser-projection system. Specifically, it is shown that two sources of nonlinear distortions could deviate captured images from reality. The first distortion stems from the wide-angle lens used in flexible endoscopes. It is shown that endoscopic images have a significantly higher spatial resolution in the center of the field of view than in its periphery. The difference between the two could lead to as high as 26.4% error in calibrated horizontal measurements. The second distortion stems from variation in the imaging angle. It is shown that the disparity between spatial resolution in the center and periphery of endoscopic images increases as the imaging angle deviates from the perpendicular position. Furthermore, it is shown that when the imaging angle varies, the symmetry of the distortion is also affected significantly. The combined distortions could lead to calibrated horizontal measurement errors as high as 65.7%. The implications of the findings on objective measurements and subjective visual assessments are discussed. These findings can contribute to the refinement of the methods for clinical assessment of voice disorders. Considering that the studied phenomena are due to optical principles, the findings of this study, especially those related to the effects of the imaging angle, can provide further insights regarding other endoscopic instruments (eg, distal-chip and rigid endoscopes) and procedures (eg, gastroendoscopy and colonoscopy).

The design specifications and experimental characteristics of a newly developed laser-projection transnasal flexible endoscope coupled with a high-speed videoendoscopy (HSV) system are provided. The hardware and software design of the proposed system benefits from the combination of structured green light projection and laser triangulation techniques, which provide the capability of calibrated absolute measurements of the laryngeal structures along the horizontal and vertical planes during phonation. Visual inspection of in-vivo acquired images demonstrated sharp contrast between laser points and background, confirming successful design of the system. Objective analyses were carried out for assessing the irradiance of the system and the penetration of the green laser light into the red and blue channels in the recorded images. The analysis showed that the system has irradiance of 372 W/m(2) at a working distance of 20 mm, which is well within the safety limits, indicating minimal risk of usage of the device on human subjects. Additionally, the color penetration analysis showed that, with probability of 90%, the ratio of contamination of the red channel from the green laser light is less than 0.002. This indicates minimal effect of the laser projection on the measurements performed on the red data channel, making the system applicable for calibrated 3D spatial-temporal segmentation and data-driven subject-specific modeling, which is important for further advancing voice science and clinical voice assessment.

Summary The ability to provide absolute calibrated measurement of the laryngeal structures during phonation is of paramount importance to voice science and clinical practice. Calibrated three-dimensional measurement could provide essential information for modeling purposes, for studying the developmental aspects of vocal fold vibration, for refining functional voice assessment and treatment outcomes evaluation, and for more accurate staging and grading of laryngeal disease. Recently, a laser-calibrated transnasal fiberoptic endoscope compatible with high-speed videoendoscopy (HSV) and capable of providing three-dimensional measurements was developed. The optical principle employed is to project a grid of 7 × 7 green laser points across the field of view (FOV) at an angle relative to the imaging axis, such that (after calibration) the position of each laser point within the FOV encodes the vertical distance from the tip of the endoscope to the laryngeal tissues. The purpose of this study was to develop a precise method for vertical calibration of the endoscope. Investigating the position of the laser points showed that, besides the vertical distance, they also depend on the parameters of the lens coupler, including the FOV position within the image frame and the rotation angle of the endoscope. The presented automatic calibration method was developed to compensate for the effect of these parameters. Statistical image processing and pattern recognition were used to detect the FOV, the center of FOV, and the fiducial marker. This step normalizes the HSV frames to a standard coordinate system and removes the dependence of the laser-point positions on the parameters of the lens coupler. Then, using a statistical learning technique, a calibration protocol was developed to model the trajectories of all laser points as the working distance was varied. Finally, a set of experiments was conducted to measure the accuracy and reliability of every step of the procedure. The system was able to measure absolute vertical distance with mean percent error in the range of 1.7% to 4.7%, depending on the working distance.

Clinical diagnosis of voice disorder and evaluation of therapy outcome heavily rely on accurate quantification of voice quality, which is closely tied to the physiology and function of the laryngeal mechanism. Considering the evaluation methodology of the voice, two main categories of auditory-perceptual assessment and acoustic analysis can be identified. This article presents a new approach for acoustic analysis of voice quality, which brings several advantages to the field. The proposed approach is non-parametric in the sense that it does not require the estimation of the fundamental frequency or spectral response of the vocal tract. This reduces the computational complexity of the measurement and reduces the possible errors due to inaccurate estimation of those parameters. Additionally, the method does not make any assumption about the phonetic context and hence has the potential to be applied to connected speech. The proposed method benefits from the multiresolution structure of the wavelet analysis for estimating the noisy component of a voice in the spectro-temporal domain. The informativeness of the estimated noise for voice quality distinction is examined based on different noise-quantification approaches. It is shown that deviation from the model of the human auditory system (HAS) leads to performance improvement. Through several analyses, it is argued that using models of HAS for quantification of the noise leads to significant loss of information relevant to voice quality. Findings from this article suggest that perception-based measures of voice quality are highly restricted in capturing important aspects of acoustic that could assist with voice quality distinctions. This characteristic is inherent to HAS and cannot be alleviated, highlighting a significant limitation of perception-based measures.

Evidence-based practice and precision medicine can significantly benefit from the ability to perform calibrated spatial measurements (eg, mm) from endoscopic images. However, calibrated measurements are not readily available from laryngeal images. Laser-projection endoscopes can provide the required information for performing calibrated spatial measurements, but their applications require a process known as calibration. During calibration, a set of benchtop recordings are used to determine the effect of confounding factors of spatial measurements, and also to learn their proper compensation strategies. Calibration benchtop recordings are acquired from flat surfaces and at a perpendicular imaging angle which is significantly different from in-vivo situations, where a three-dimensional (3D) surface gets recorded at a semi-unknown imaging angle. The aim of this study was to quantify changes in calibrated vertical and horizontal measurement accuracies as we move from the controlled condition of calibration to more realistic and uncontrolled settings.A flat surface was positioned in front of a calibrated laser-projection transnasal fiberoptic endoscope at different working distances and imaging angles. Calibrated vertical and horizontal measurement errors were computed from each condition. Multiple linear regression analyses were used to quantify the dependence of vertical and horizontal measurement errors on the imaging angle and working distance. Next, a 3D-printed surface was positioned in front of the laser-projection endoscope at different working distances. Calibrated vertical and horizontal measurement errors were computed from each condition and then they were compared to measurement errors from a flat surface positioned at comparable working distances.The outcome of analyses supported a significant effect of imaging angle on calibrated vertical measurement accuracy, while no significant effect of imaging angle on calibrated horizontal measurement accuracy was established. Additionally, the result of multiple linear regression analyses showed that the coefficient of imaging angle was two times larger than the working distance, which further highlights the significant effect of imaging angle on vertical measurement accuracy. Comparing the magnitude of calibrated vertical and horizontal measurement errors between the 3D surface and a flat surface suggested a significant effect of surface topology on calibrated measurement accuracies.The mean percent magnitude of error of vertical and horizontal measurement errors from the 3D surface were respectively around 6% and 11%, at most working distances, which are acceptable for many applications. However, the significant effect of imaging angle and surface topology on measurement errors highlights the need for further research on these confounding factors. It also suggests that significant improvements in measurement accuracies may be achieved if these factors are properly accounted for during the calibration process. Last but not least, this study highlights the need for the evaluation of laser-projection endoscopes in uncontrolled and more realistic settings. Specifically, evaluations of laser-projection endoscopes in very controlled settings could significantly overestimate their accuracies and hence it will not represent their actual performances during in-vivo data acquisitions.

OBJECTIVE: Calibrated horizontal-plane measurements from laryngeal images could contribute significantly to refining evidence-based practice and developing patient-specific models and precision-medicine approaches. Laser-projection endoscopes can address the need for direct calibrated measures; however, these systems are not widely available. This study presents the framework for an alternative indirect horizontal-plane calibration approach. METHOD: A spatial attribute of a common object, a distinct characteristic that is maintained across images, may be used as a scale for the normalization of other spatial measurements. The outcome of this indirect approach could be used for absolute measurements (e.g., in units of mm) or relative measurements (e.g., percent change), depending on the information that is available from the common attribute. The required conditions of a common attribute for achieving a valid calibration outcome were studied. Three conditions were derived: registration accuracy of the common attribute, size consistency of the common attribute, and similarity in the vertical distance between the region of interest (ROI) (e.g., vocal fold) and the common attribute. Any common attribute satisfying these three conditions was called proper and would result in a valid indirect calibration outcome. Three tests were presented for evaluating the properness of a common attribute. A data-driven statistical method was presented that can evaluate the registration accuracy of a common attribute. The second test used variation in calibrated lengths of a common attribute under different phonatory configurations for evaluating the size consistency condition. Finally, the effect of differences between vertical distances of the ROI and the common attribute was mathematically tested and quantified. The application of the proposed framework for indirect calibration was demonstrated using a pre-existing dataset with a vocal fold as the ROI and four different common attributes (vocal fold length, vocal fold width, blood vessel on the vocal fold, and blood vessel on nearby tissue). RESULTS: The proposed registration-accuracy test was able to detect and eliminate instances of common attributes with low accuracies. The analysis suggested that among the studied four common attributes, the vocal fold length had the highest (i.e., best) registration accuracy; however, the vocal fold length exhibited the lowest (i.e., worst) size consistency. The analysis also suggested that, among the studied attributes, the vocal fold width offered the best trade-off among the three conditions and, hence, was a proper common attribute for calibrating spatial aspects of the vocal folds (length, displacement of edges, velocity, etc.). CONCLUSION: Indirect calibration is a feasible alternative for calibration of laryngeal endoscopic images, given a proper common attribute is selected. Future work is needed to systematically evaluate the effects of various phonatory conditions on the characteristics of common attributes.

Objective: Calibrated horizontal measurements (e.g., mm) from endoscopic procedures could be utilized for advancement of evidence-based practice and personalized medicine. However, the size of an object in endoscopic images is not readily calibrated and depends on multiple factors, including the distance between the endoscope and the target surface. Additionally, acquired images may have significant non-linear distortion that would further complicate calibrated measurements. This study used a recently developed in vivo laser-projection fiberoptic laryngoscope and proposes a method for calibrated spatial measurements. Method: A set of circular grids was recorded at multiple working distances. A statistical model was trained that would map from pixel length of the object, the working distance, and the spatial location of the target object into its mm length. Result: A detailed analysis of the performance of the proposed method is presented. The analyses have shown that the accuracy of the proposed method does not depend on the working distance and length of the target object. The estimated average magnitude of error was 0.27 mm, which is three times lower than the existing alternative. Conclusion: The presented method can achieve sub-millimeter accuracy in horizontal measurement. Significance: Evidence-based practice and personalized medicine could significantly benefit from the proposed method. Implications of the findings for other endoscopic procedures are also discussed.

The ability to discern variations in voice quality from speech is important for effective talker identification and robust speech processing; yet, little is known about how faithfully acoustic information relevant to variations in talkers’ voice quality is transmitted through a cochlear implant (CI) device. The present study analyzed unprocessed and CI-simulated versions of sustained /a/ vowel sounds from two groups of individuals with normal and disordered voice qualities in order to explore the effects of CI speech processing on acoustic information relevant for the distinction of voice quality. The CI-simulated voices were created by processing the vowel sounds along with 4-, 8-, 12-, 16-, 22-, and 32-channel noise-vocoders. The variations in voice quality for each voice sound was characterized by calculating mel-frequency cepstral coefficients (MFCCs). The effects of simulated CI speech processing on the acoustic distinctiveness between normal and disordered voices were then measured by calculating the Mahalanobis distance (MD) metric, as well as accuracy of support vector machines (SVMs) applied to MFCC features. The results showed that CI speech processing, as simulated by noise vocoding, is highly detrimental to the acoustic information involved in conveying voice quality distinctions. This supports the view that listeners with CIs will likely experience difficulties in perceiving voice quality variations due to the reduced spectral resolution, shedding light on challenges listeners with CIs may face for effective recognition and processing of talkers’ voices.

Automatic solution of rectangular jigsaw puzzles can be broken down into two separate steps of calculating pairwise compatibility metrics and jigsaw assembling algorithm. This work discriminates between two different sources of errors, each corresponding to one of these two steps. In this regard, type I error is defined as the imperfection of the used compatibility metric, and type II error is reserved to measure the imperfection of jigsaw assembling algorithm. Differentiating between these two types of error allows us to tweak and optimize different parts of the algorithm to achieve the best performance. Based upon these defined terms, this study argues that current jigsaw assembling algorithms mainly rely on either greedy methods or metaheuristic algorithms, which may impose a considerable amount of type II error to the final solution. This paper demonstrates that a powerful and perfect (i.e., type II error-free) jigsaw assembling algorithm is achievable by combining branch and bound technique with graph theory. This perfect jigsaw assembling algorithm is then utilized to measure the performances of various compatibility metrics and color models. The superiority of red-green-blue (RGB) color model and Mahalanobis gradient compatibility (MGC) metric in solving rectangular jigsaw puzzles is shown by providing conclusive evidence. Additionally, a mean opinion score (MOS) test is conducted to examine the accuracy of the existing metrics. According to the results from MOS test, we argue that the existing performance criteria are not concise and accurate; thus, a new accuracy metric is proposed on the basis of comparing different sub-blocks of solutions. Finally, the efficiency of jigsaw assembling algorithm is measured by proposing a new performance criterion.

During the last decade, audio information hiding has attracted lots of attention due to its ability to provide a covert communication channel. On the other hand, various audio steganalysis schemes have been developed to detect the presence of any secret messages. Basically, audio steganography methods attempt to hide their messages in areas of time or frequency domains where human auditory system (HAS) does not perceive. Considering this fact, we propose a reliable audio steganalysis system based on the reversed Mel-frequency cepstral coefficients (R-MFCC) which aims to provide a model with maximum deviation from HAS model. Genetic algorithm is deployed to optimize dimension of the R-MFCC-based features. This will both speed up feature extraction and reduce the complexity of classification. The final decision is made by a trained support vector machine (SVM) to detect suspicious audio files. The proposed method achieves detection rates of 97.8% and 94.4% in the targeted (Steghide@1.563%) and universal scenarios. These results are respectively 17.3% and 20.8% higher than previous D2-MFCC based method. Based on a model with maximum deviation from human auditory system, a new steganalysis method is proposed.The method is tested on wide range of data hiding algorithms and in both targeted and universal scenarios.The proposed method improves detection rate of targeted and universal scenarios by 17.3% and 20.8%.

Previous studies have shown that the underlying process of speech generation exhibits nonlinear characteristics. Since linear features cannot represent a nonlinear system thoroughly, this paper employs new sets of non-linear measurement for assessing the quality of recorded voices. Such measurement could be exploited for implementing efficient and convenient systems for diagnosing laryngeal diseases without using invasive methods. Three sets of features based on mutual information, false neighbor fraction, and Lyapunov spectrum are investigated to this end. Furthermore, distributions of the proposed features and their discriminative property are investigated. Moreover, the described procedure benefits from the synergy between different concepts of pattern recognition. First, a genetic algorithm (GA) is invoked to find a-near optimum subset of features. Second, linear discriminant analysis (LDA) is applied to remove remaining redundancies and correlations between selected features. Finally, support vector machine (SVM) is employed for learning decision boundaries. Sensitivity and specificity of 99.3% and 94% respectively were achieved in the simulation results.

Mp3 is a very popular audio format and hence it can be a good host for carrying hidden messages. Therefore, different steganography methods have been proposed for mp3 hosts. But, current literature has only focused on steganalysis of mp3stego. In this paper we mention some of the limitations of mp3stego and argue that UnderMp3Cover (Ump3c) does not have those limitations. Ump3c makes subtle changes only to the global gain of bitstream and keeps the rest of bitstream intact. Therefore, its detection is much harder than mp3stego. To address this, joint distributions between global gain and other fields of mp3 bit stream are used. The changes are detected by measuring the mutual information from those joint distributions. Furthermore, we show that different mp3 encoders have dissimilar performances. Consequently, a novel multi-layer architecture for steganalysis of Ump3c is proposed. In this manner, the first layer detects the encoder and the second layer performs the steganalysis job. One of advantages of this architecture is that feature extraction and feature selection can be optimized for each encoder separately. We show this multi-layer architecture outperforms the conventional single-layer methods. Comparing results of the proposed method with other works shows an improvement of 20.4% in the accuracy of steganalysis., 9 pages, 7 tables, 6 figures, journal paper

Comparing popularity of mp3 and wave with the amount of works published on each of them shows mp3 steganalysis has not found adequate attention. Furthermore, investigating existing works on mp3 steganalysis shows that a major factor has been overlooked. Experimenting with different mp3 encoders shows there are subtle differences in their outputs. This shows that mp3 standard has been implemented in dissimilar fashions, which in turn could degrade performance of steganalysis if it is not addressed properly. Additionally, calibration is a powerful technique which has not found its true potential for mp3 steganalysis. This paper tries to fill these gaps. First, we present our analysis on different encoders and show they can be classified quite accurately with only four features. Then, we propose a new set of calibrated features based on quantization step. To that end, we show quantization step is a band limited signal and steganography noise affects its high frequency components more prominently. By applying a low pass filter on quantization steps, we arrive at an estimation of quantization step, which in turn is used for calibrating the features., 8 pages, 4 Tables, 10 Figures, Submitted journal paper

Recently, merging signal processing techniques with information security services has found a lot of attention. Steganography and steganalysis are among those trends. Like their counterparts in cryptology, steganography and steganalysis are in a constant battle. Steganography methods try to hide the presence of covert messages in innocuous-looking data, whereas steganalysis methods try to reveal existence of such messages and to break steganography methods. The stream nature of audio signals, their popularity, and their wide spread usage make them very suitable media for steganography. This has led to a very rich literature on both steganography and steganalysis of audio signals. This paper intends to conduct a comprehensive review of audio steganalysis methods aggregated over near fifteen years. Furthermore, we implement some of the most recent audio steganalysis methods and conduct a comparative analysis on their performances. Finally, the paper provides some possible directions for future researches on audio steganalysis., Submitted journal paper

The ability to recognize different voice qualities is essential for good talker identification; yet, little is known about how well voice quality cues of talkers are transmitted through the degraded speech signals delivered by cochlear implants (CIs). This study examined how CI speech filtering affects acoustic distinctiveness of individuals with and without voice disorder. Sustained /a/ vowels uttered by speakers with normal or disordered voice were processed using 4, 8, 12, 16, 22, and 32 channel noise-vocoders. The effect of CI processing on the distinctiveness of talkers with normal and disordered voices was measured using the Mahalanobis distance measure on Mel-frequency cepstral coefficients derived from samples across these groups. The analysis confirmed that CI vocoding dramatically degrades acoustic cues in frequency sub-bands that signal abnormal voicing behavior. Remarkable spectral degradation was observed in low- ( 12 kHz) bands for simulated conditions compared with unprocessed signals. These findings indicate that CI users likely have almost no ability to distinguish talkers differing in voice qualities. These results highlight challenges that CI users face for recognizing talkers differing in voice quality, due to these users’ lack of access to fine-grained spectro-temporal details in voices.

Echo hiding methods have good perceptual quality and they are robust to intentional and unintentional modifications. Unfortunately these methods are not quite transparent and are not suitable for steganography applications. Specifically, this point became more obvious after a recent steganalysis investigation where both parameters and the hidden message were extracted accurately. This work tries to alleviate this problem by introducing variable parameters into echo hiding methods. The system is tested in both active and passive warden scenarios. Comparing results of conventional and the proposed method shows that for embedding strength of 0.2, the proposed method decreases detection of echo method by 24.2% and increases its robustness to echo attacks by 16.17%.

Some of the previous audio steganalysis systems have suggested features based on human auditory system models. In contrast, this paper exploits the idea of maximum deviation from human auditory system to suggest an efficient audio steganalysis scheme. Based on this idea, an artificial ear is considered that has high resolution in high frequency region and low resolution where the frequency is low. Simulation results show that this artificial ear can virtually hear effect of steganography and distinguish between stego and clean audio signals. Proposed method achieves accuracy of 93% (StegHide@1.563% BPB) and 97% (Hide4Pgp@6.25% BPB) which are 16% and 12% higher than previous MFCC based methods. KeywordsAudio Steganalysis, Audio Steganography, Mel Cepstrum, Reversed Mel Cepstrum, Human Auditory System.

Wireless channels are highly prone to eavesdropping. To mitigate this problem encryption systems are used. Analog scrambling systems achieve confidentiality through modification of analog signals. Unfortunately, current literatures lack a thorough security analysis of these systems. In this paper security of hopping window time domain scrambler is investigated. It is shown that ciphertext of these systems is highly redundant. Based on this observation, a cryptanalysis system is proposed. Firstly, audio signal is mapped into a set of puzzles. Later, scrambling keys are found by solving these pictorial puzzles. Proposed method is compared with FWLSD which, to our best knowledge, is the only existing cryptanalysis method for these systems. Objective and subjective tests show that voices descrambled by the proposed method achieve intelligibility scores of 0.739 and 0.82 respectively. These scores are 0.37 and 0.25 higher than scores achieved by FWLSD method. Keywordsanalog scrambling system, cipher-text only attack, jigsaw puzzle, cryptanalysis.

Puzzle solving is the art of pattern recognition which has found many applications in different areas such as restoration and reconstruction of archeological findings, repairing of broken objects, solving jigsaw puzzles, molecular docking problem, etc. There are two inherent problems in solving a general jigsaw puzzle; one is how to search through possible arrangements efficiently. The other one is devising some piece matching technique. To our best knowledge, current literature lacks a thorough investigation of the first problem. This paper investigates this problem in depth. Furthermore, different metaheuristic approaches to solve this problem are explored.