Reliability of perceptions of voice quality: evidence from a problem asthma clinic population

<p>Introduction: Methods of perceptual voice evaluation have yet to achieve satisfactory consistency; complete acceptance of a recognised clinical protocol is still some way off.</p> <p>Materials and methods: Three speech and language therapists rated the voices of 43 patients attending the problem asthma clinic of a teaching hospital, according to the grade-roughness-breathiness-asthenicity-strain (GRBAS) scale and other perceptual categories.</p> <p>Results and analysis: Use of the GRBAS scale achieved only a 64.7 per cent inter-rater reliability and a 69.6 per cent intra-rater reliability for the grade component. One rater achieved a higher degree of consistency. Improved concordance on the GRBAS scale was observed for subjects with laryngeal abnormalities. Raters failed to reach any useful level of agreement in the other categories employed, except for perceived gender.</p> <p>Discussion: These results should sound a note of caution regarding routine adoption of the GRBAS scale for characterising voice quality for clinical purposes. The importance of training and the use of perceptual anchors for reliable perceptual rating need to be further investigated.</p&gt

Automatic Detection of Laryngeal Pathology on Sustained Vowels Using Short-Term Cepstral Parameters: Analysis of Performance and Theoretical Justification

The majority of speech signal analysis procedures for automatic detection of laryngeal pathologies mainly rely on parameters extracted from time domain processing. Moreover, calculation of these parameters often requires prior pitch period estimation; therefore, their validity heavily depends on the robustness of pitch detection. Within this paper, an alternative approach based on cepstral- domain processing is presented which has the advantage of not requiring pitch estimation, thus providing a gain in both simplicity and robustness. While the proposed scheme is similar to solutions based on Mel-frequency cepstral parameters, already present in literature, it has an easier physical interpretation while achieving similar performance standards

A software system for pathological voice acoustic analysis

International audienceA software system for pathological voice analysis using only the resources of a personal computer with a sound card is proposed. The system is written on the basis of specific methods and algorithms for pathological voice analysis and allows evaluation of: 1) Pitch period (To); 2) Degree of unvoiceness; 3) Pitch perturbation and amplitude perturbation quotients; 4) Dissimilarity of surfaces of the pitch pulses; 5) Ratio aperiodic/periodic components in cepstra; 6) Ratio {energy in the cepstral pitch pulse}-to-{total cepstral energy}; 7) Harmonics-to-noise ratio; 8) Degree of hoarseness; 9) Ratio low-to-high frequency energies; 10) Glottal Closing Quotient. The voices of 400 persons were analyzed - 100 (50 females/50 males) normal speakers and 300 (100 females/200 males) patients. The statistical analysis shows very significant changes in PPQ, DH, DPP, DUV, APR, HNR and PECM, and significant changes in APQ and CQ

Spectral analysis of pathological acoustic speech waveforms

Biomedical engineering is the application of engineering principles and techniques to the medical field. The design and problem solving skills of engineering are combined with medical and biological science, which improves medical disorder diagnosis and treatment. The purpose of this study is to develop an automated procedure for detecting excessive jitter in speech signals, which is useful for differentiating normal from pathologic speech. The fundamental motivation for this research is that tools are needed by speech pathologists and laryngologists for use in the early detection and treatment of laryngeal disorders. Acoustical analysis of speech was performed to analyze various features of a speech signal. Earlier research established a relation between pitch period jitter and harmonic bandwidth. This concept was used for detecting laryngeal disorders in speech since pathologic speech has been found to have larger amounts of jitter than normal speech. Our study was performed using vowel samples from the voice disorder database recorded at the Massachusetts Eye and Ear Infirmary (MEEI) in1994. The KAYPENTAX company markets this database. Software development was conducted using MATLAB, a user-friendly programming language which has been applied widely for signal processing. An algorithm was developed to compute harmonic bandwidths for various speech samples of sustained vowel sounds. Open and closed tests were conducted on 23 samples of pathologic and normal speech samples each. Classification results showed 69.56% probability of correct detection of pathologic speech samples during an open test

Acoustic, myoelectric, and aerodynamic parameters of euphonic and dysphonic voices: a systematic review of clinical studies

At present, there is no clinical consensus on the concept of normal and dysphonic voices. For many years, the establishment of a consensus on the terminology related to normal and pathological voices has been studied, in order to facilitate the communication between professionals in the field of the voice. Aim: systematically review the literature to compare and learn more precisely the measurable and objective characteristics of the acoustic, aerodynamic and surface electromyographic parameters of the normal and dysphonic voices. Methods: The PRISMA 2020 methodology was used as a review protocol together with the PICO procedure to answer the research question through six databases. Results: In total, 467 articles were found. After duplicate records were removed from the selection, the inclusion and exclusion criteria were applied and 19 articles were eligible. A qualitative synthesis of the included studies is presented in terms of their methodology and results. Conclusions: Studying the acoustic, aerodynamic, and electromyographic parameters with more precision, in both normal and dysphonic voices, will allow health professionals working in the field of voice (speech therapy, otorhinolaryngology, phoniatrics, etc.) to establish a diagnostic and detailed consensus of the vocal pathology, enhancing the communication and generalization of results worldwide

Differentiation of voice disorders using objective parameters from harmonic waveform modeling in high-speed digital imaging

High-speed digital imaging (HSDI) has recently become clinically available for the direct observation of vocal fold movement in the last 20 years. However, before it can become routinely used in the clinical setting, a universal means of objectively analyzing and interpreting the HSDI data must be established. In this study, preliminary data was gathered for five parameters used to objectively analyze vocal fold vibratory patterns observed with HSDI. The parameters investigated were established by Ikuma, Kunduk, and McWhorter (2012a) and were previously studied with a small sample (N=8) comparing pre and post-phonosurgical removal of benign lesions. The five parameters included fundamental frequency standard deviation (F0SD), harmonics-to-noise ratio (HNR) mean, open quotient (OQ) mean, speed index (SI) mean, and relative glottal gap (RGG) mean. The current study aimed to statistically and visually analyze measurements of the five objective parameters for differences between pathology groups with different etiologies. High-speed videos (N=50) were divided into five groups based on one of the following medical diagnoses: normal voice, vocal fold nodules, polyps, true vocal fold motion impairment (TVFMI), and adductor spasmodic dysphonia (ADSD). Statistical analysis showed that HNR mean differentiated normal voices from ADSD voices and that F0 mean differentiated ADSD voices from all groups except vocal fold nodules (p \u3c 0.005). Visual analysis revealed a strong trend for RGG mean to differentiate vocal fold nodules from all other groups. Less prominent visual trends for OQ mean and SI mean were also noted