An Innovative Voice Analyzer “VA” Smart Phone Program for Quantitative Analysis of Voice Quality

Kojima, Tsuyoshi; Hori, Ryusuke; Okanoue, Yusuke; Shoji, Kazuhiko; Inoue, Masato

doi:10.1016/j.jvoice.2018.01.026

Cited by 13 publications

(9 citation statements)

References 8 publications

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“…Research has already examined the performance of several devices that can be used for recordings such as iPads ( De Decker, 2016 ; Maryn et al , 2017 ), computers ( De Decker and Nycz, 2011 ; Kojima et al , 2019 ; Vogel et al , 2014 ), and smart phones ( Grillo et al , 2016 ; Kojima et al , 2019 ; Manfredi et al , 2017 ; Uloza et al , 2015 ; Vogel et al , 2014 ; see Jannetts et al , 2019 , for a review). Other studies have examined the effects of different file formats, such as lossless Apple .m4a files ( De Decker and Nycz, 2011 ), lossy compressed .mp3 files ( Bulgin et al , 2010 ), and audio extracted from compressed video files ( De Decker and Nycz, 2011 ).…”

Section: Introductionmentioning

confidence: 99%

Comparing acoustic analyses of speech data collected remotely

Zhang

Jepson

Lohfink

et al. 2021

The Journal of the Acoustical Society of America

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Face-to-face speech data collection has been next to impossible globally as a result of the COVID-19 restrictions. To address this problem, simultaneous recordings of three repetitions of the cardinal vowels were made using a Zoom H6 Handy Recorder with an external microphone (henceforth, H6) and compared with two alternatives accessible to potential participants at home: the Zoom meeting application (henceforth, Zoom) and two lossless mobile phone applications (Awesome Voice Recorder, and Recorder; henceforth, Phone). F0 was tracked accurately by all of the devices; however, for formant analysis (F1, F2, F3), Phone performed better than Zoom, i.e., more similarly to H6, although the data extraction method (VoiceSauce, Praat) also resulted in differences. In addition, Zoom recordings exhibited unexpected drops in intensity. The results suggest that lossless format phone recordings present a viable option for at least some phonetic studies. V

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Section: Introductionmentioning

confidence: 99%

Comparing acoustic analyses of speech data collected remotely

Zhang

Jepson

Lohfink

et al. 2021

The Journal of the Acoustical Society of America

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“…Several recent studies have compared studio and smartphone recording practices, demonstrating variable robustness of acoustic parameters under smartphone recording conditions (E Lin, Hornibrook and Ormond 2012;Vogel and Maruff 2014;Uloza et al 2015;Grillo et al 2016;Manfredi et al 2017;Maryn et al 2017;Kojima et al 2018;Jannetts et al 2019). Jannetts et al (2019) compared smartphone recordings to studio equipment recordings and observed small but statistically significant systematic errors for a range of acoustic parameters (e.g.…”

Section: Reliability Of Smartphone Recordingsmentioning

confidence: 99%

Secure account-based data capture with smartphones – preliminary results from a study of articulatory precision in clinical depression

Miley

Schaeffler

Beck

et al. 2021

Linguistics Vanguard

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Smartphone technology is continuously being updated through software and hardware changes. At present, a limited number of studies have been undertaken to assess the impact of these changes on data collection for linguistic research. This paper discusses the potential of smartphones to gather reliable recordings, along with ethical considerations for storing additional personal information when working in other contexts (i.e. healthcare settings). A pilot study was undertaken using the FitvoiceTM account-based application to analyse articulatory proficiency in depressed and healthy participants. Results suggest that phonetic differences exist between these groups in terms of plosive production, and that smartphones are capable of adequately recording these minute aspects of the speech signal for analysis.

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“…An Voice Analyzer or “VA” smartphone program for quantitative analysis of voice quality proposed by Kojima et al in 2018 and further development of the system by Fujimura et al 2019 resulted in a highly accessible real-time acoustic voice analysis system ( VArt ) running the Android operating system. It also represented a new hoarseness index, i.e., a real-time Ra (Rart) [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

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

Uloza

Ulozaitė-Stanienė

Petrauskas

2022

Eur Arch Otorhinolaryngol

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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.

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An Innovative Voice Analyzer “VA” Smart Phone Program for Quantitative Analysis of Voice Quality

Cited by 13 publications

References 8 publications

Comparing acoustic analyses of speech data collected remotely

Comparing acoustic analyses of speech data collected remotely

Secure account-based data capture with smartphones – preliminary results from a study of articulatory precision in clinical depression

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

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