An Assessment of Different Praat Versions for Acoustic Measures Analyzed Automatically by VoiceEvalU8 and Manually by Two Raters

Grillo, Elizabeth U.; Wolfberg, Jeremy

doi:10.1016/j.jvoice.2020.12.003

Cited by 12 publications

(9 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This work demonstrated that acoustic measures including AVQI captured automatically by VoiceEvalU8 in the client's environment (the participants were instructed to be in a quiet room) were similar to acoustic measures captured manually by two raters using different Praat versions. The average AVQI value of 19 vocally healthy females was consistent with normative female data in the literature [ 31 ]. The results of the studies mentioned above enabled us to presume the feasibility of voice recordings captured with smartphone in an ordinary clinical setting for the estimation of AVQI.…”

Section: Introductionsupporting

confidence: 84%

An iOS-based VoiceScreen application: feasibility for use in clinical settings—a pilot study

Uloza

Ulozaitė-Stanienė

Petrauskas

2022

Eur Arch Otorhinolaryngol

View full text Add to dashboard Cite

Objectives To elaborate the application suitable for smartphones for estimation of Acoustic Voice Quality Index (AVQI) and evaluate its usability in the clinical setting. Methods An elaborated AVQI automatization and background noise monitoring functions were implemented into a mobile “ VoiceScreen” application running the iOS operating system. A study group consisted of 103 adult individuals with normal voices ( n = 30) and 73 patients with pathological voices. Voice recordings were performed in the clinical setting with “ VoiceScreen” app using iPhone 8 microphones. Voices of 30 patients were recorded before and 1 month after phonosurgical intervention. To evaluate the diagnostic accuracy differentiating normal and pathological voice, the receiver-operating characteristic statistics, i.e., area under the curve (AUC), sensitivity and specificity, and correct classification rate (CCR) were used. Results A high level of precision of AVQI in discriminating between normal and dysphonic voices was yielded with corresponding AUC = 0.937. The AVQI cutoff score of 3.4 demonstrated a sensitivity of 86.3% and specificity of 95.6% with a CCR of 89.2%. The preoperative mean value of the AVQI [6.01(SD 2.39)] in the post-phonosurgical follow-up group decreased to 2.00 (SD 1.08). No statistically significant differences ( p = 0.216) between AVQI measurements in a normal voice and 1-month follow-up after phonosurgery groups were revealed. Conclusions The “ VoiceScreen ” app represents an accurate and robust tool for voice quality measurement and demonstrates the potential to be used in clinical settings as a sensitive measure of voice changes across phonosurgical treatment outcomes. Supplementary Information The online version contains supplementary material available at 10.1007/s00405-022-07546-w.

show abstract

Section: Introductionsupporting

confidence: 84%

An iOS-based VoiceScreen application: feasibility for use in clinical settings—a pilot study

Uloza

Ulozaitė-Stanienė

Petrauskas

2022

Eur Arch Otorhinolaryngol

View full text Add to dashboard Cite

show abstract

“…The multivariate structures of the VWI, AVQI, and ABI, on the other hand, depend on a linear regression model which incorporates pertinent acoustic parameters; they consist of both continuous speech and sustained vowel sounds in the acoustic evaluation, and the processing of signals employs freeware Praat algorithms, and can thus be standardized and made automated. This has already been realized in several applications available for AVQI estimation: VoiceEvalU8 [ 48 ], A Comprehensive Application for Grading Severity of Voice [ 29 ], VoiceScreen, version 4.4.22 [ 49 ], and ABI assessment: VOXplot, version 2.0 [ 50 ]. As a result, the registration of the AVQI, ABI, and VWI as an “ecologically valid” MAVI may be readily accomplished using specific programs, even without the presence of trained staff, allowing individuals to self-assess their voice quality.…”

Section: Discussionmentioning

confidence: 99%

Accuracy Analysis of the Multiparametric Acoustic Voice Indices, the VWI, AVQI, ABI, and DSI Measures, in Differentiating between Normal and Dysphonic Voices

Uloza,

Pribuišis,

Ulozaite-Staniene

et al. 2023

JCM

View full text Add to dashboard Cite

The study aimed to investigate and compare the accuracy and robustness of the multiparametric acoustic voice indices (MAVIs), namely the Dysphonia Severity Index (DSI), Acoustic Voice Quality Index (AVQI), Acoustic Breathiness Index (ABI), and Voice Wellness Index (VWI) measures in differentiating normal and dysphonic voices. The study group consisted of 129 adult individuals including 49 with normal voices and 80 patients with pathological voices. The diagnostic accuracy of the investigated MAVI in differentiating between normal and pathological voices was assessed using receiver operating characteristics (ROC). Moderate to strong positive linear correlations were observed between different MAVIs. The ROC statistical analysis revealed that all used measurements manifested in a high level of accuracy (area under the curve (AUC) of 0.80 and greater) and an acceptable level of sensitivity and specificity in discriminating between normal and pathological voices. However, with AUC 0.99, the VWI demonstrated the highest diagnostic accuracy. The highest Youden index equaled 0.93, revealing that a VWI cut-off of 4.45 corresponds with highly acceptable sensitivity (97.50%) and specificity (95.92%). In conclusion, the VWI was found to be beneficial in describing differences in voice quality status and discriminating between normal and dysphonic voices based on clinical diagnosis, i.e., dysphonia type, implying the VWI’s reliable voice screening potential.

show abstract

“…Telehealth was deemed to be reliable for the majority of individuals and only 4% required face-to-face evaluation ( Duffy et al., 1997 ). Since then, considerable advancements in technology have enabled greater accuracy in obtaining acoustic, aerodynamic and auditory-perceptual measures through video conferencing and mobile applications in quiet and noisy environments ( Choi et al., 2022 ; Grillo & Wolfberg, 2020 ; Uloza et al., 2021 ; van der Woerd et al., 2020 ; Weerathunge et al., 2021 ).…”

Section: Telehealth In Voice Carementioning

confidence: 99%

“…They found no within-subject variability in acoustic measures between these methods. A recent study by Grillo and Wolfberg (2020) compared acoustic analyses using VoiceEvalU8, a mobile application that collects acoustic, aerodynamic and auditory-perceptual data, and manually by two raters. Nineteen healthy speakers used their personal iPhone or Android device with VoiceEvalU8 to record themselves sustaining a vowel, reading a phrase and during connected speech.…”

Section: Telehealth In Voice Carementioning

confidence: 99%

Addressing disparities in speech-language pathology and laryngology services with telehealth

Rameau

Cox

Sussman

et al. 2023

Journal of Communication Disorders

View full text Add to dashboard Cite

An Assessment of Different Praat Versions for Acoustic Measures Analyzed Automatically by VoiceEvalU8 and Manually by Two Raters

Cited by 12 publications

References 24 publications

An iOS-based VoiceScreen application: feasibility for use in clinical settings—a pilot study

An iOS-based VoiceScreen application: feasibility for use in clinical settings—a pilot study

Accuracy Analysis of the Multiparametric Acoustic Voice Indices, the VWI, AVQI, ABI, and DSI Measures, in Differentiating between Normal and Dysphonic Voices

Addressing disparities in speech-language pathology and laryngology services with telehealth

Contact Info

Product

Resources

About