Acoustic Character Governing Variation in Normal, Benign, and Malignant Voices

INTRODUCTION

Benign and malignant vocal fold lesions (VFLs) are growths that occur on the vocal folds. However, the treatments for these two types of lesions differ significantly. Therefore, it is imperative to use a multidisciplinary approach to properly recognize suspicious lesions. This study aimed to determine the important acoustic characteristics specific to benign and malignant VFLs.

METHODS

The acoustic model of voice quality was utilized to measure various acoustic parameters in 157 participants, including individuals with normal, benign, and malignant conditions. The study comprised 62 female and 95 male participants (43 ± 10 years). Voice samples were collected at the Shanghai Eye, Ear, Nose, and Throat Hospital of Fudan University between May 2020 and July 2021. The acoustic variables of the participants were analyzed using Principal Component Analysis (PCA) to present important acoustic characteristics that are specific to normal vocal folds, benign VFLs, and malignant VFLs. The similarities and differences in acoustic factors were also studied for benign conditions including Reinke's edema, polyps, cysts, and leukoplakia.

RESULTS

Using the PCA method, the components that accounted for the variation in the data were identified, highlighting acoustic characteristics in the normal, benign, and malignant groups. The analysis indicated that coefficients of variation in root mean square energy were observed solely within the normal group. Coefficients of variation in pitch (F0) were found to be significant only in benign voices, while higher formant frequencies and their variability were identified as contributors to the acoustic variance within the malignant group. The presence of formant dispersion (FD) as a weighted factor in PCA was exclusively noted in individuals with Reinke's edema. The amplitude ratio between subharmonics and harmonics (SHR) and its coefficients of variation were evident exclusively in the polyps group. In the case of voices with cysts, both pitch (F0) and coefficients of variation for FD were observed to contribute to variations. Additionally, higher formant frequencies and their coefficients of variation played a role in the acoustic variance among voices of patients with leukoplakia.

CONCLUSION

Experimental evidence demonstrates the utility of the PCA method in the identification of vibrational alterations in the acoustic characteristics of voice affected by lesions. Furthermore, the PCA analysis has highlighted underlying acoustic differences between various conditions such as Reinke's edema, polyps, cysts, and leukoplakia. These findings can be used in the future to develop an automated malignant voice analysis algorithm, which will facilitate timely intervention and management of vocal fold conditions.

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.

Do the Nonlinear Dynamic Acoustic Measurements, Nonlinear Energy Difference Ratio and Spectrum Convergence Ratio, Correlate with Perceptual Evaluation of Esophageal Voice Speakers?

BACKGROUND

The acoustic assessment of phonation after total laryngectomy is challenged by signal aperiodicity which makes frequency-based acoustic measures less reliable. This is important for patients who use esophageal voice since voice samples mostly include type III (highly aperiodic) and 4 (chaotic) signals. As such, using non-linear measures, which are better suited for aperiodic phonation, may be useful to investigate the relationship between acoustic signal characteristics and perception of esophageal voice quality.

OBJECTIVES

This study aimed to investigate whether nonlinear dynamic acoustic methods, nonlinear energy difference Ratio (NEDR) and spectrum convergence ratio (SCR), were correlated with perceptual measures in subjects who used esophageal phonation.

METHODS

Thirty-one subjects who had undergone total laryngectomy and use esophageal voice as a rehabilitation method were included in this study. Expert and non-expert raters listened to the esophageal voice samples from the subjects and rated vowels and connected speech samples on a scale from 1 to 7 on dysphonia severity and intelligibility. In addition, non-linear acoustic analysis was performed to calculate NEDR and SCR. Analysis from the raters was compared to the non-linear acoustic analysis to find the correlation between the variables.

RESULTS

There were no significant correlations between any of the non-linear acoustic measures NEDR and SCR and the perceptual ratings at the significance level of 0.05. Correlations were calculated for each acoustic measure among the expert raters and among the non-expert raters in both connected speech samples and sustained vowel fragments.

CONCLUSIONS

In conclusion, the nonlinear dynamic acoustic analyses of spectrum convergence ratio and nonlinear energy difference ratio do not have a significant correlation with perceptual measures of esophageal voice.

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.

Voice Signal Typing Using a Pattern Recognition Approach

Voice signal classification in three types according to their degree of periodicity, a task known as signal typing, is a relevant preprocessing step before computing any perturbation measures. However, it is a time consuming and subjective activity. This has given rise to interest in automatic systems that use objective measures to distinguish among the different signal types. The purpose of this paper is twofold. First, to propose a pattern recognition approach for automatic voice signal typing based on a multi-class linear Support Vector Machine, and using rather well-known parameters like Jitter, Shimmer, Harmonic-to-Noise Ratio, and Cepstral Prominence Peak in combination with nonlinear dynamics measures. Two novel features are also proposed as objective parameters. Second, to validate this approach using a large amount of signals coming from two well-known corpora using cross-dataset experiments to assess the generalizability of the system. A total amount of 1262 signals labeled by professional voice pathologists were used with this purpose. Statistically significant differences between all types were found for all features. Accuracies over 82.71% were estimated in all intra-datasets and inter-datasets using cross-validation. Finally, the use of posterior probabilities is proposed as a measure of the reliability of the assigned type. This could help clinicians to make a more informed decision about the type assigned to a voice. These outcomes suggest that the proposed approach can successfully discriminate among the three voice types, paving the way to a fully automatic tool for voice signal typing in the future.