Nonlinear Dynamic Analysis and Perturbation Measurement Used for Discriminating Pathological Voices and Their Correlations With Perceptual Evaluation.

OBJECTIVE: 1. To investigate the discriminatory and diagnostic power of nonlinear dynamic analysis measures concerning voices from normal, benign, and malignant voice disorders. 2. To study the correlations of nonlinear dynamic analysis measures with perceptual ratings to evaluate the reliability of the objective acoustic analysis in predicting severity of voice. METHOD: The perturbation analysis metrics used were Jitter%, Shimmer%, and signal-to-noise ratio. The nonlinear dynamic analysis metrics used were spectrum convergence ratio (SCR), nonlinear energy difference ratio (NEDR), and rate of divergence (ROD). Subjects were enrolled and divided into three groups based on laryngeal pathology: normal, benign, and malignant. Vowel sound and reading samples were recorded. Perceptual evaluation was applied to these voice samples to investigate correlations between metrics and auditory perception. RESULT: Each metric was capable of discriminating laryngeal pathology, except for SCR in the case of distinguishing between benign and malignant pathologies. Perturbation analysis parameters had a moderate ability to differentiate between normal and benign pathologies, but were unable to characterize malignant pathologies for certain diseases, such as Reinke's edema. All metrics significantly correlated with perceptual G scores. Nonlinear dynamic analysis was superior when applied to cases of severe dysphonia, where linear metrics such as Jitter% and Shimmer% tended to lose utility. NEDR and ROD were successful at differentiating between the different pathologies, whereas SCR could not discriminate between the benign and malignant groups. CONCLUSION: Perturbation and nonlinear dynamic analyses are comparable in their discriminating power with respect to normal and benign voices, and normal and malignant voices. The nonlinear dynamic analysis metrics NEDR and ROD may be superior in clinical settings with respect to discriminating voice pathology ranging from mild pathological voice to severe dysphonia, and with respect to discriminating benign and malignant voice. SCR was found unable to discriminate pathological voices.

A Novel Acoustic Evaluation Method for the Diagnosis of Adductor Spasmodic Dysphonia.

INTRODUCTION: Adductor spasmodic dysphonia (ADSD) is characterized by involuntary laryngeal muscle spasms. Due to the lack of a quantitative evaluation method, most measurements have demonstrated difficulty in validity and reliability for diagnosing ADSD. This study aimed to establish a novel indicator for ADSD and determine its diagnostic effects. METHODS: We investigated 98 voice samples from 49 patients with ADSD and 49 healthy subjects. A sustained vowel was recorded by a high-definition audio recorder. Voice samples underwent regular acoustic evaluation and a novel global dimension method. Global dimension (GD), Jitter, Shimmer, HNR, Frequency shift, and CPPS were measured for both groups. RESULTS: Statistical analysis revealed that the global dimension method effectively differentiated ADSD patients from healthy subjects (P<0.001, D'>0.8). Subsequent multiclass receiver operating characteristic analysis demonstrated that GD possessed the most significant classification accuracy (AUC = 0.988) compared with other acoustic parameters. CONCLUSION: GD was an effective metric for objective differentiation between ADSD patients and healthy subjects. This metric could assist clinicians in the diagnosis of ADSD patients.

Introduction of Voice Type Component (VTC) as an Effective Acoustic Voice Analysis Method in Tele-evaluation.

OBJECTIVE: Telepractice in voice health care and evaluation services has attracted much attention in recent years. Multiple studies have proven the effectiveness of voice therapy with telepractice. However, voice evaluations are still mostly conducted in person due to the lack of sensitive acoustic analysis methods. METHODS: This study examined various acoustic analysis methods for voice evaluation in telepractice. Eighteen female elementary school teachers with self-reported voice disorders volunteered to participate in the study. Speech samples were collected before and after the interventions using two voice sampling methods concurrently. One set of data was collected using the traditional voice sample collection method by the therapist in person. The second set of data was collected on the same speech samples using the clients' own smartphones, and the collected voice samples were later sent to the researcher for further acoustic analysis. The voice type component (VTC) measurement represented the proportion of different VTCs in a voice by measuring the chaos and intrinsic dimension. RESULTS: Voice analyses were conducted on both sets of data, and the correlation between the two sampling procedures was analyzed. It appears that the VTC could be a more reliable method for producing acoustic analysis results with voice samples collected from smartphones compared to other objective voice assessment procedures. This reliability has been demonstrated via statistical analysis, including correlation coefficient, pairwise t test, d-prime, and area under the curve. The results of this study highlighted the VTC as an effective and accurate acoustic analysis method in tele-evaluation. CONCLUSIONS: This feasible voice sampling method, which utilizes participants' own smartphones, will reduce barriers to accessing limited voice specialists due to distance and will decrease the cost of care by minimizing expenses associated with travel and additional equipment for voice sampling. Ultimately, this approach will enhance the effectiveness of voice care delivered through telepractice to patients in remote and underserved areas.

Aging-Related Decline in Phonated and Whispered Speech Perception Not Compensated For by Increased Duration and Intensity: Evidence From Mandarin-Speaking Adult Listeners.

PURPOSE: This study aimed to examine how aging and modifications of critical acoustic parameters may affect the perception of whispered speech as a degraded signal. METHOD: Forty Mandarin-speaking adults were included in the study. Part 1 of the study compared the perception of Mandarin lexical tones, vowels, and syllables in older and younger adults in whispered versus phonated speech conditions. Parts 2 and 3 further examined how modification of duration and intensity cues contributed to the perceptual outcomes. RESULTS: Perception of whispered tones was compromised in older and younger adults. Older adults identified lexical tones less accurately than their younger counterparts, particularly for phonated T2 and T3 and whispered T3. Aging also negatively affected the vowel identification of /i, u/ in the whispered condition. Syllable-level accuracy was largely dependent on the accuracy of lexical tones and vowels. Furthermore, reduced duration led to the decreased accuracy of phonated T3 and whispered T2 and T3 but increased accuracy of phonated T4. Reduced intensity lowered the recognition accuracy for phonated vowels /i, ɤ, o, y/ in older adults and /i, u/ in younger adults, and it also lowered the accuracy of whispered vowels /a, ɤ/ in older adults. Contrary to our expectation, increased duration and intensity did not improve older adults' speech perception in either phonated or whispered conditions. CONCLUSIONS: The results suggest that aging adversely affected speech perception in both phonated and whispered conditions with more challenges in identifying whispered speech for older adults. While older adults' diminished performance may be potentially due to problems with processing the degraded temporal and spectral information of the target speech sounds, it cannot be simply compensated for by increasing the duration and intensity of the target sounds beyond the audible level.

Chaos Behavior Analysis of Alaryngeal Voices Including Esophageal and Tracheoesophageal Voices.

HYPOTHESIS/OBJECTIVES: This study's objective was to develop a method to evaluate the chaotic characteristic of alaryngeal speech. The proposed method will be capable of distinguishing between normal and alaryngeal voices, including esophageal (SE) and tracheoesophageal (TE) voices. It has been previously shown that alaryngeal voices exhibit chaotic characteristics due to the aperiodicity of their signals. The proposed method will be applied for future use to quantify both chaos behavior (CB) and the difference between SE and TE voices. STUDY DESIGN: A total of 74 voice recordings including 34 normal and 40 alaryngeal (26 SE and 14 TE) were used in the study. Voice samples were analyzed to distinguish alaryngeal voices from normal voices and to investigate different chaotic characteristics of SE and TE speech. METHODS: A chaotic distribution detection-based method was used to investigate the CB of alaryngeal voices. This CB was used to detect the difference between SE and TE voice types. Quantification of the CB parameter was performed. Statistical analyses were used to compare the results of the CB analysis for both the SE and TE voices. RESULTS: Statistical analysis revealed that CB effectively differentiated between all normal and alaryngeal voice types (p < 0.01). Subsequent multiclass receiver operating characteristic (ROC) analysis demonstrated that CB (area under the curve) possessed the greatest classification accuracy relative to correlation dimension (D2). CONCLUSIONS: The CB metric shows strong promise as an accurate, useful metric for objective differentiation between all normal and alaryngaeal, SE and TE voice types. The CB calculations showed expected results, as SE voices have significantly more CB than TE voices, constituting substantial improvement over previous methods and becoming the first SE and TE classification method. This metric can help clinicians obtain additional acoustic information when monitoring the efficacy of treatment for patients undergoing total laryngectomies.

Comparison Between Combination of Resonant Voice Therapy and Vocal Hygiene Education and Vocal Hygiene Education Only for Female Elementary School Teachers.

OBJECTIVE: The study compares the rehabilitation outcome of two voice intervention methods for female elementary school teachers with self-reported voice disorders. METHODS: A total of 34 female teachers from two primary schools volunteered in the study. Participants from one school were assigned to the experimental group (16 teachers), who received the combination of vocal hygiene education and resonant voice therapy. Participants from the other school were assigned to the control group (18 teachers), who received vocal hygiene education only. Pre- and post-treatment data were compared. RESULT: The total score of the Voice Handicap Index (VHI) decreased significantly from 12.19 ± 8.58 to 8.63 ± 7.27 (P < 0.05); the functional score of VHI significantly decreased from 5.38 ± 3.9 to 3.81 ± 3.62 (P < 0.05). No statistical significance was found in physiological and emotional scores of VHI. No statistical significance was found in the control group. In the experimental group, the maximum phonation time was increased from 14.34 ± 6.80s to 17.21 ± 6.06s (P < 0.05), Jitter decreased from 0.45% ± 0.13% to 0.26% ± 0.05% (P < 0.05), and Shimmer decreased from 0.21 ± 0.10. to 0.12 ± 0.03 (P < 0.05). Furthermore, the harmonic to noise ratio increased from 23.06 ± 2.99 to 25.23 ± 1.92 (P < 0.05), Spectrum Convergence Ratio increased from 0.53 ± 0.12 to 0.60 ± 0.11 (P < 0.05), yet no statistical significance was found in Nonlinear Energy Difference Ratio data for the experimental group. No statistical significance was found in the control group. In the auditory perception assessment (GRBAS), the G score decreased from 1.19 ± 0.54 to 0.81 ± 0.40 (P < 0.05), and the R score decreased from 1.19 ± 0.54 to 0.75 ± 0.45 (P < 0.05) in the experimental group. No statistical significance was found in the B, A, and S scores in the experimental group; moreover, none of the GRBAS scores in the control group demonstrated statistical significance. In the voice type component profile (VTC), the proportion of VTC1 of the experimental group increased significantly, while the proportions of VTC3 and VTC4 decreased significantly, indicating the improvement of voice quality was obvious after the intervention. The proportions of VTC of the control group did not demonstrate significant change. CONCLUSION: The results of this study show that a combination of vocal hygiene education and resonant voice therapy can significantly improve the voice function of professional voice users and effectively improve their voice quality. In this study, the professional voice users receiving vocal hygiene education only did not show significant improvement of their voice quality.

Probability-Based Best Sample Selection for Acoustic Analysis of Normal and Disordered Voices.

PURPOSE: Acoustic analysis is a commonly used method for quantitatively measuring vocal fold function. The accuracy of acoustic analysis depends upon the operator selecting a stable segment of the voice sample to analyze. This paper proposes a novel method to more accurately and reliably select a stable voice segment. STUDY DESIGN: Four selection methods were implemented to evaluate each raw audio signal and determine the most stable segment of each signal: The proposed modal periodogram method, the moving window method, the midvowel method, and the whole vowel method. Acoustic parameters of interest-namely perturbation (jitter), correlation dimension (D2), and spectrum convergence ratio (SCR)-were calculated for 48 phonation samples to evaluate each method. METHODS: The proposed modal periodogram method utilizes a minimum mean-square error based approach to calculate a stable modal periodogram and obtain the most stable segment. The Wilcoxon Signed-Rank test was used to compare jitter, D2, and SCR values acquired using the modal periodogram method against the current standard segment selection methods. RESULTS: The modal periodogram method yielded significantly lower D2 values, and a significantly higher SCR for both normal and disordered voice samples (P < 0.01). This indicates that the modal periodogram method is more apt for selecting a stable audio segment than the other selection methods.

Effectiveness and Feasibility of Telepractice on Voice Therapy for Female Teachers in Elementary Schools with Self-Reported Voice Disorders.

PURPOSE: The purpose of this study is to explore the effectiveness of telepractice in voice intervention for female teachers in elementary schools with self-reported voice disorders. METHODS: Thirty-five female elementary school teachers with self-reported voice disorders volunteered to participate in the study. They were divided into a telepractice voice intervention group (experimental group N=18) and a face-to-face voice intervention group (control group N=17) based on their employment setting. The exact same treatment protocol was applied to both groups of subjects, except that the intervention group was seen through telepractice, and the control group was seen face-to-face. The treatment protocol includes vocal hygiene education and resonant voice therapy twice a week for a total of eight sessions. Auditory perceptual analysis, acoustic assessment, aerodynamic assessment and self-assessment protocol were conducted before the intervention and one week after the last intervention, and the differences before and after interventions within each group and between groups were compared. RESULTS: There was no significant difference in baseline data including age, working years, and voice symptoms between the two groups. Both groups showed significant improvement (P<0.05) in all voice assessment before and after the treatment sessions, except for the Voice Handicap Index-10 (VHI-10) assessment. No statistical difference was found in other pre- and post-intervention voice assessment changes between the two study groups. The control group presented higher improvement in the total score, and the two subdomain assessments of physiology and emotion. CONCLUSIONS: Telepractice voice intervention can effectively improve the voice quality of female teachers in elementary schools, and telepractice therapy can be an effective alternative to face-to-face voice intervention.

Evaluating the Voice Type Component Distributions of Excised Larynx Phonations at Three Subglottal Pressures.

Purpose The excised canine larynx provides an advantageous experimental framework in the study of voice physiology. In recent years, signal processing methods have been applied to analyze phonations in excised canine larynx experiments. However, phonations have a highly complex and nonstationary nature corresponding to different proportions of regular and chaotic signal elements. Current nonlinear dynamic methods that are used to assess the degree of irregularity in the voice fail to recognize the distribution of voice type components (VTCs). Method Based on measures of intrinsic dimension, this article presents a method to analyze the VTC distribution of phonations in excised canine larynx experiments. Thirty-nine phonation samples from 13 excised canine larynges at three different subglottal pressures were analyzed. Results Phonation produced with subglottal pressures above phonation instability pressure (PIP) and below phonation threshold pressure (PTP) resulted in high proportions of Voice Types 3 and 4, characterized by chaotic and noisy signals. Phonation produced with pressure between PTP and PIP contained mostly Type 1 voice, characterized by a regular and nearly periodic signal. Mean proportions of all VTCs varied significantly in comparisons of phonations produced with Sub-PTP and PTP as well as in comparisons of phonations produced with PTP and PIP. Conclusions Across all VTCs, the VTC profiles of normal and abnormal phonation differ significantly. Normal phonation is strongly associated with VTC1 (Voice Type Component 1), whereas abnormal phonation exhibits increased VTC4 (Voice Type Component 4). The study further demonstrates the ability of intrinsic dimension to successfully detect multiple voice types in an acoustic signal and highlights the need for expanded use of intrinsic dimension in human voice. Supplemental Material https://doi.org/10.23641/asha.14417585.

Quantification of Voice Type Components Present in Human Phonation Using a Modified Diffusive Chaos Technique.

PURPOSE: Signal typing has been used to categorize healthy and disordered voices; however, human voices are likely comprised of differing proportions of periodic type 1 elements, type 2 elements that are periodic with modulations, aperiodic type 3 elements, and stochastic type 4 elements. A novel diffusive chaos method is presented to detect the distribution of voice types within a signal with the goal of providing an objective and clinically useful tool for evaluating the voice. It was predicted that continuous calculation of the diffusive chaos parameter throughout the voice sample would allow for construction of comprehensive voice type component profiles (VTCP). METHODS: One hundred thirty-five voice samples of sustained /a/ vowels were randomly selected from the Disordered Voice Database Model 4337. All samples were classified according to the voice type paradigm using spectrogram analysis, yielding 34 type 1, 35 type 2, 42 type 3, and 24 type 4 voice samples. All samples were then analyzed using the diffusive chaos method, and VTCPs were generated to show the distribution of the 4 voice type components (VTC). RESULTS: The proportions of VTC1 varied significantly between the majority of the traditional voice types (P < .001). Three of the 4 VTCs of type 3 voices were significantly different from the VTCs of type 4 voices (P < .001). These results were compared to calculations of spectrum convergence ratio, which did not vary significantly between voice types 1 and 2 or 2 and 3. CONCLUSION: The diffusive chaos method demonstrates proficiency in generating comprehensive VTCPs for disordered voices with varying severity. In contrast to acoustic parameters that provide a single measure of disorder, VTCPs can be used to detect subtler changes by observing variations in each VTC over time. This method also provides the advantage of quantifying stochastic noise components that are due to breathiness in the voice.

An Objective Parameter to Classify Voice Signals Based on Variation in Energy Distribution.

OBJECTIVES: The purpose of this paper is to introduce an iterative nonlinear weighted method based on the variation in spectral energy distribution present in a voice signal to differentiate between four voice types: type 1 voice signals are nearly periodic, type 2 voice signals have strong modulations and subharmonics, type 3 signals are chaotic, and type 4 signals are dominated by stochastic noise. STUDY DESIGN: A total of 135 voice signal samples of the sustained vowel /a/ were obtained from the Disordered Voice Database and then individually categorized into the appropriate voice types based on the classification system described in Sprecher et al (2010). Voice samples were analyzed using the nonlinear methods of spectrum convergence ratio, rate of divergence, and nonlinear energy difference ratio (NEDR) to investigate classifier efficacy. METHODS: An iterative nonlinear weighted method based on the derivative of instantaneous frequency and Fourier transformations is applied to calculate spectral energy distributions. The distribution is then used to calculate the NEDR to classify voice signal types. RESULTS: Statistical analysis revealed that NEDR effectively differentiated between all four voice types (P < 0.001). Subsequent multiclass receiver operating characteristic analysis demonstrated that NEDR (area under the curve [95% CI] = 0.99 [0.96-1.0]) possessed the greatest classification accuracy relative to spectrum convergence ratio and rate of divergence. CONCLUSION: NEDR was shown to be an effective metric for objective differentiation between all four voice signal types. NEDR calculations occurred approximately instantaneously, constituting a substantial improvement over the tedious computational time required for calculation of previous nonlinear parameters. This metric could assist clinicians in the diagnosis of voice disorders and monitor the efficacy of treatment through observation of voice acoustical improvement over time.

Application of Local Intrinsic Dimension for Acoustical Analysis of Voice Signal Components.

PURPOSE: The overall aim of this study was to apply local intrinsic dimension ( Di) estimation to quantify high-dimensional, disordered voice and discriminate between the 4 types of voice signals. It was predicted that continuous Di analysis throughout the entire time-series would generate comprehensive descriptions of voice signal components, called voice type component profiles (VTCP), that effectively distinguish between the 4 voice types. METHOD: One hundred thirty-five voice recording samples of the sustained vowel /a/ were obtained from the Disordered Voice Database Model 4337 and spectrographically classified into the voice type paradigm. The Di and correlation dimension ( D2) were then used to objectively analyze the voice samples and compared based on voice type differentiation efficacy. RESULTS: The D2 exhibited limited effectiveness in distinguishing between the 4 voice type signals. For Di analysis, significant differences were primarily observed when comparing voice type component 1 (VTC1) and 4 (VTC4) across the 4 voice type signals ( P < .001). The 4 voice type components (VTCs) significantly differentiated between low-dimensional, type 3 and high-dimensional, type 4 signals ( P < .001). CONCLUSIONS: The Di demonstrated improvements over D2 in 2 distinct manners: enhanced resolution at high data dimensions and comprehensive description of voice signal elements.

Applied Chaos Level Test for Validation of Signal Conditions Underlying Optimal Performance of Voice Classification Methods.

Purpose: The purpose of this study is to introduce a chaos level test to evaluate linear and nonlinear voice type classification method performances under varying signal chaos conditions without subjective impression. Study Design: Voice signals were constructed with differing degrees of noise to model signal chaos. Within each noise power, 100 Monte Carlo experiments were applied to analyze the output of jitter, shimmer, correlation dimension, and spectrum convergence ratio. The computational output of the 4 classifiers was then plotted against signal chaos level to investigate the performance of these acoustic analysis methods under varying degrees of signal chaos. Method: A diffusive behavior detection-based chaos level test was used to investigate the performances of different voice classification methods. Voice signals were constructed by varying the signal-to-noise ratio to establish differing signal chaos conditions. Results: Chaos level increased sigmoidally with increasing noise power. Jitter and shimmer performed optimally when the chaos level was less than or equal to 0.01, whereas correlation dimension was capable of analyzing signals with chaos levels of less than or equal to 0.0179. Spectrum convergence ratio demonstrated proficiency in analyzing voice signals with all chaos levels investigated in this study. Conclusion: The results of this study corroborate the performance relationships observed in previous studies and, therefore, demonstrate the validity of the validation test method. The presented chaos level validation test could be broadly utilized to evaluate acoustic analysis methods and establish the most appropriate methodology for objective voice analysis in clinical practice.

An improved performance frequency estimation algorithm for passive wireless SAW resonant sensors.

Passive wireless surface acoustic wave (SAW) resonant sensors are suitable for applications in harsh environments. The traditional SAW resonant sensor system requires, however, Fourier transformation (FT) which has a resolution restriction and decreases the accuracy. In order to improve the accuracy and resolution of the measurement, the singular value decomposition (SVD)-based frequency estimation algorithm is applied for wireless SAW resonant sensor responses, which is a combination of a single tone undamped and damped sinusoid signal with the same frequency. Compared with the FT algorithm, the accuracy and the resolution of the method used in the self-developed wireless SAW resonant sensor system are validated.