The Current State and Future Possibilities of Mobile Phone "Voice Analyser" Applications, in Relation to Otorhinolaryngology

Voice disorder recognition using machine learning: a scoping review protocol

INTRODUCTION

Over the past decade, several machine learning (ML) algorithms have been investigated to assess their efficacy in detecting voice disorders. Literature indicates that ML algorithms can detect voice disorders with high accuracy. This suggests that ML has the potential to assist clinicians in the analysis and treatment outcome evaluation of voice disorders. However, despite numerous research studies, none of the algorithms have been sufficiently reliable to be used in clinical settings. Through this review, we aim to identify critical issues that have inhibited the use of ML algorithms in clinical settings by identifying standard audio tasks, acoustic features, processing algorithms and environmental factors that affect the efficacy of those algorithms.

METHODS

We will search the following databases: Web of Science, Scopus, Compendex, CINAHL, Medline, IEEE Explore and Embase. Our search strategy has been developed with the assistance of the university library staff to accommodate the different syntactical requirements. The literature search will include the period between 2013 and 2023, and will be confined to articles published in English. We will exclude editorials, ongoing studies and working papers. The selection, extraction and analysis of the search data will be conducted using the 'Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews' system. The same system will also be used for the synthesis of the results.

ETHICS AND DISSEMINATION

This scoping review does not require ethics approval as the review solely consists of peer-reviewed publications. The findings will be presented in peer-reviewed publications related to voice pathology.

Utility of Smart Phones as a Voice Acquisition Device for Assessing Pre and Post Treatment Voice Using PRAAT

Voice assessment before and after treatment helps the clinician to assess the effectiveness of the treatment given and facilitates comparison between different treatment modalities. Voice handicap index -10(VHI-10) questionnaire is a tool which allows the voice to be evaluated subjectively from the patient's perspective. PRAAT is a freely available, software programme that acoustically analyse voice signals. Smart phones are widely used and the high quality of the embedded microphone in it makes it a suitable and easily available voice recording device. This study aims at using PRAAT and VHI-10 questionnaire in evaluating voice before and after treatment. The utility of smart phones as a voice acquisition device is also explored in the study. Prospective, observational study, carried out from 1st November 2019 to 30th September 2021in the ENT out- patient department at a tertiary hospital in Punjab. 58 patients complaining of dysphonia were enrolled consecutively in the study. All patients underwent detailed history, examination of the larynx using 70-degree rigid laryngoscope. The voice handicap was scored by (VHI-10) questionnaire and acoustic evaluation of voice was done using the PRAAT software. Patients' voice was further evaluated 3 months post-therapy with VHI 10 questionnaire and acoustic analysis. The parameters measured on PRAAT were mean pitch, jitter (local), shimmer (local), and mean harmonics to noise ratio (HNR). The voice was recorded using a smart phone and later transferred onto a laptop for analysis. The pre and post treatment acoustic parameters and VHI-10 scores were compared and correlated. There was significant difference (p < 0.001) between the pre and post treatment VHI-10 scores and all the acoustic parameters measured except for median pitch (p = 0.995). A poor positive correlation was found between the pre treatment VHI-10 scores and jitter(r = 0.188, p = 0.157) and shimmer (r = 0.288, p = 0.028) values. A negative correlation was observed between pre treatment VHI-10 scores and pitch (r = - 0.151, p = 0.259) and HNR(r = - 0.424, p = 0.001). Post treatment VHI-10 scores showed positive correlation with jitter (r = 0.302, p = 0.021) and shimmer (0.162, p = 0.225) values and negative correlation with pitch (r = - 0.10, p = 0.457) and HNR (r = - 0.356, p = 0.006) values. We found significant differences in the VHI-10 scores and PRAAT voice analysis results before and after treatment in patients complaining with voice change (dysphonia). VHI-10 questionnaire and PRAAT are good and convenient tools for assessing the voice subjectively and objectively. Only a poor to fair correlation was found between VHI-10 scores and PRAAT analysis results. More studies must be done to confirm the utility of smart phones as a voice acquisition device and PRAAT software in voice analysis.

Reliability of Universal-Platform-Based Voice Screen Application in AVQI Measurements Captured with Different Smartphones

The aim of the study was to develop a universal-platform-based (UPB) application suitable for different smartphones for estimation of the Acoustic Voice Quality Index (AVQI) and evaluate its reliability in AVQI measurements and normal and pathological voice differentiation. Our study group consisted of 135 adult individuals, including 49 with normal voices and 86 patients with pathological voices. The developed UPB "Voice Screen" application installed on five iOS and Android smartphones was used for AVQI estimation. The AVQI measures calculated from voice recordings obtained from a reference studio microphone were compared with AVQI results obtained using smartphones. The diagnostic accuracy of differentiating normal and pathological voices was evaluated by applying receiver-operating characteristics. One-way ANOVA analysis did not detect statistically significant differences between mean AVQI scores revealed using a studio microphone and different smartphones (F = 0.759; p = 0.58). Almost perfect direct linear correlations (r = 0.991-0.987) were observed between the AVQI results obtained with a studio microphone and different smartphones. An acceptable level of precision of the AVQI in discriminating between normal and pathological voices was yielded, with areas under the curve (AUC) displaying 0.834-0.862. There were no statistically significant differences between the AUCs (p > 0.05) obtained from studio and smartphones' microphones. The significant difference revealed between the AUCs was only 0.028. The UPB "Voice Screen" application represented an accurate and robust tool for voice quality measurements and normal vs. pathological voice screening purposes, demonstrating the potential to be used by patients and clinicians for voice assessment, employing both iOS and Android smartphones.

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

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.

Mobile Phone Applications Voice Tools and Voice Pitch Analyzer Validated With LingWAVES to Measure Voice Frequency

OBJECTIVES

Voice frequency can be measured to assess the voice change in transgender men and women during treatment. There are many applications that can analyze voice frequency. This validation study aimed to compare the ability to measure voice frequency of the mobile phone applications "Voice Tools" and "Voice Pitch Analyzer" with the registration program LingWAVES as the gold standard.

STUDY DESIGN

Prospective validation study.

METHODS

A total of 45 participants of whom 20 transgender individuals were included. They were asked to read "The North Wind and the Sun" twice. The first measurement compared voice frequency measured by Voice Tools with LingWAVES while the second measurement compared Voice Pitch Analyzer with LingWAVES. The two applications that were being compared simultaneously measured the voice frequency. Pearson's regression correlations were performed to test for correlation between the mobile phone applications and LingWAVES.

RESULTS

Significant correlations were demonstrated between the measurements of Voice Tools and LingWAVES (P < 0.001) and between Voice Pitch Analyzer and LingWAVES (P < 0.001). Voice Tools overestimated voice frequency with a median deviation of 2Hz (range -4 to 20). The overestimation was more pronounced in the high ranges. Voice Pitch Analyzer showed underestimation of voice frequency in high ranges. Median deviation was -2Hz (range -16 to 14).

CONCLUSIONS

This validation study shows that voice frequency can be reliably measured with the mobile phone applications "Voice Tools" and "Voice Pitch Analyzer". Combined with the ease of use, these applications can be used to measure voice frequency in clinical practice and for research purposes.

Voice Quality in Telephone Interviews: A preliminary Acoustic Investigation

OBJECTIVES

To investigate the impact of standardized mobile phone recordings passed through a telecom channel on acoustic markers of voice quality and on its perception by voice experts in normophonic speakers.

METHODS

Continuous speech and a sustained vowel were recorded for fourteen female and ten male normophonic speakers. The recordings were done simultaneously with a head-mounted high-quality microphone and through the telephone network on a receiving smartphone. Twenty-two acoustic voice quality, breathiness and pitch-related measures were extracted from the recordings. Nine vocologists perceptually rated the G, R and B parameters of the GRBAS scale on each voice sample. The reproducibility, the recording type, the stimulus type and the gender effects, as well as the correlation between acoustic and perceptual measures were investigated.

RESULTS

The sustained vowel samples are damped after one second. Only the frequencies between 100 and 3700Hz are passed through the telecom channel and the frequency response is characterized by peaks and troughs. The acoustic measures show a good reproducibility over the three repetitions. All measures significantly differ between the recording types, except for the local jitter, the harmonics-to-noise ratio by Dejonckere and Lebacq, the period standard deviation and all six pitch measures. The AVQI score is higher in telephone recordings, while the ABI score is lower. Significant differences between genders are also found for most of the measures; while the AVQI is similar in men and women, the ABI is higher in women in both recording types. For the perceptual assessment, the interrater agreement is rather low, while the reproducibility over the three repetitions is good. Few significant differences between recording types are observed, except for lower breathiness ratings on telephone recordings. G ratings are significantly more severe on the sustained vowel on both recording types, R ratings only on telephone recordings. While roughness is rated higher in men on telephone recordings by most experts, no gender effect is observed for breathiness on either recording types. Finally, neither the AVQI nor the ABI yield strong correlations with any of the perceptual parameters.

CONCLUSIONS

Our results show that passing a voice signal through a telecom channel induces filter and noise effects that limit the use of common acoustic voice quality measures and indexes. The AVQI and ABI are both significantly impacted by the recording type. The most reliable acoustic measures seem to be pitch perturbation (local jitter and period standard deviation) as well as the harmonics-to-noise ratio from Dejonckere and Lebacq. Our results also underline that raters are not equally sensitive to the various factors, including the recording type, the stimulus type and the gender effects. Neither of the three perceptual parameters G, R and B seem to be reliably measurable on telephone recordings using the two investigated acoustic indexes. Future studies investigating the impact of voice quality in telephone conversations should thus focus on acoustic measures on continuous speech samples that are limited to the frequency response of the telecom channel and that are not too sensitive to environmental and additive noise.

COVID-19 and the resurgence of telehealth in otolaryngology

The objective of this review is to examine the impact of the ongoing Coronavirus disease 2019 (COVID-19) pandemic on the use of telehealth in Otolaryngology. The use of telemedicine rose dramatically during the pandemic to meet the need for continued patient care while allowing for physical separation of providers and patients. Telemedicine has been used to evaluate patients with a variety of pathologies including dysphonia, vertigo, and anosmia. Innovative use of at-home exams, such as video-otoscopy has aided providers in overcoming challenges associated with a highly specialized physical exam. The use of telemedicine in Otolaryngology will likely remain essential in the post-pandemic era and has promising results for improving clinical efficiency.

Uso del smartphone en telepráctica para trastornos de la voz. Una revisión desde el concepto de Mhealth

El uso de los smartphones y el concepto de mobile health (mHealth) es reciente en vocología y sus posibles beneficios en el tratamiento y entrenamiento vocal en contexto de telepráctica. Se realizó una revisión narrativa con el objetivo describir los beneficios de la mHealth a través del smartphone en el contexto de la telepráctica fonoaudiológica de los trastornos vocales. Se buscaron artículos científicos en Pubmed, ScienceDirect y Google Scholar, asociados al uso del smartphone en vocología, considerando voces humanas normales, patológicas y voces sintéticas; relacionados a la intervención, evaluación, valoración, monitoreo, prevención, intervención, supervisión, educación, consulta y entrenamiento vocal. Se revisaron 42 estudios, de los cuales fueron seleccionados 15 de acuerdo a los criterios de inclusión. Los estudios analizados se relacionan con grabación de voz para análisis acústico con smartphone, teleterapia con smartphone y dispositivos periféricos para análisis vocal y seguimiento. Se destaca el potencial de los dispositivos móviles para incrementar accecibilidad, reducir costos y favorecer el seguimiento terapéutico con medidas objetivas en diversos contextos de salud vocal.

Accuracy of Acoustic Voice Quality Index Captured With a Smartphone - Measurements With Added Ambient Noise

OBJECTIVE

To evaluate the accuracy of Acoustic Voice Quality Index (AVQI) measures obtained from voice recordings simultaneously using oral and smartphone microphones in a sound-proof room, and to compare them with AVQIs obtained from the same smartphone voice recordings with added ambient noise.

METHODS

A study group of 183 subjects with normal voices (n = 86) and various voice disorders (n = 97) was asked to read aloud a standard text and sustain the vowel /a/. The controlled ambient noise averaged at 29.61 dB SPL was added digitally to the smartphone voice recordings. Repeated measures analysis of variances (ANOVA) with Greenhouse-Geiser correction was used to evaluate AVQI changes within subjects. To evaluate the level of agreement between AVQI measurements obtained from different voice recordings Bland-Altman plots were used.

RESULTS

Repeated measures ANOVA showed that differences among AVQI results obtained from voice recordings done with oral studio microphone, recordings done with a smartphone microphone, and recordings done with a smartphone microphone with added ambient noise were not statistically significant (P = 0.07). No significant systemic differences and acceptable level of random errors in AVQI measurements of voice recordings made with oral and smartphone microphones (including added noise) were revealed.

CONCLUSION

The AVQI measures obtained from smartphone microphones voice recordings with experimentally added ambient noise revealed an acceptable agreement with results of oral microphone recordings, thus suggesting the suitability of smartphone microphone recordings performed even in the presence of acceptable ambient noise for estimation of AVQI.

Mobile Applications in Otolaryngology: A Systematic Review of the Literature, Apple App Store and the Google Play Store

OBJECTIVES

Although the last few years have seen an increased number of smartphone applications (apps) disseminated in the field of Otolaryngology (ORL), these apps vary widely in quality. The aim of this paper, therefore, is to systematically review ORL apps directed towards patients in mobile app stores and the current literature.

METHODS

The Google Play Store, Apple App Store and PubMed were searched for ORL apps for patients using various keywords pertaining to different ORL subspecialties. Apps not relevant to the scope of this research and/or duplicates, educational apps, apps promoting a business, apps requiring specific separate hardware, and apps in non-English were excluded. In PubMed, keywords pertaining to the subspecialties were combined with "mobile app" in a search query; literature reviews, editorials, case reports, conference papers, duplicate articles, and articles irrelevant to ORL apps were excluded. The quality of apps with the highest number of reviews was assessed using the "Mobile App Rating Scale" (MARS), while the quality of the articles was rated using "The Strengthening the Reporting of Observational Studies in Epidemiology" (STROBE) Statement.

RESULTS

After searching the app stores, 1074 apps were included and grouped according to their ORL subspecialties. The overall MARS score of the ten most popular apps in each category was 3.65 out of 5. A total of 636 articles were identified in the literature, and 193 were included. The mean adherence percentage of the articles to the STROBE checklist was of 84.37%.

CONCLUSIONS

Although the apps currently available need further development, their application in ORL appears promising. Further dialogue between physicians and patients, as well as formal support from professional and scientific associations, should be encouraged.