Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tablets
IntroductionThe Bridge2AI-Voice. Consortium is developing affordable and accessible voice data to assist in the identification of vocal biomarkers of disease in adults and children. Initial experiments were designed to establish voice recording procedures to be used in research labs and clinical set...
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Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Digital Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1610772/full |
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| author | Shaheen N. Awan Yael Bensoussan Stephanie Watts Micah Boyer Robert Budinsky Ruth H. Bahr |
| author_facet | Shaheen N. Awan Yael Bensoussan Stephanie Watts Micah Boyer Robert Budinsky Ruth H. Bahr |
| author_sort | Shaheen N. Awan |
| collection | DOAJ |
| description | IntroductionThe Bridge2AI-Voice. Consortium is developing affordable and accessible voice data to assist in the identification of vocal biomarkers of disease in adults and children. Initial experiments were designed to establish voice recording procedures to be used in research labs and clinical settings, as well as in quiet environments outside of the clinic. The focus has been on isolated vowel productions, which provide a vocal signal that is representative of the biomechanics of the larynx within a static vocal tract. The current experiment considers the impact of sentence productions on the measurement of several acoustic parameters.MethodsVoice recordings from 24 individuals representing a wide range of typical and disordered voices were analyzed. Two CAPE-V sentences were recorded via a head-and-torso model using (1) a research quality, clinical standard microphone/preamplifier/audio interface and (2) smartphones and tablets using their internal microphones and an attached external headset microphone. Mouth-to-microphone distances and environmental noise levels were controlled. Measures of fundamental frequency (F0) and spectral and cepstral measures of voice quality valid for use in sentence contexts were analyzed across recording conditions.ResultsCepstral peak prominence (CPP) values were sensitive to microphone type, noise, and sentence type conditions. Nevertheless, strong linear relationships were observed across recording methods compared to the clinical standard. Measures of F0 obtained using autocorrelation correlated strongly across recording methods, whereas F0 measures obtained from the CPP (CPP F0) were highly variable and poorly correlated across recording methods and noise conditions. The L/H ratio (a measure of spectral tilt) was significantly affected by recording condition but not background noise, and measures of L/H ratio were also observed to correlate strongly across recording methods and noise conditions.DiscussionCurrent findings revealed that different recording methods can produce significantly different acoustic measures of voice with sentence-level materials. Since microphone characteristics (e.g., frequency response; use of noise cancellation), mouth-to-microphone distances, and background noise conditions can have significant effects on spectral and cepstral assessment of voice, it is essential that recording methods and conditions are explicitly described when designing voice data collection projects and comparing datasets as it may have an impact on voice analysis. Future investigations should evaluate consistency of results among multiple examples of the same device. |
| format | Article |
| id | doaj-art-750cd59ca1f64ca49307a54b0902f20b |
| institution | DOAJ |
| issn | 2673-253X |
| language | English |
| publishDate | 2025-07-01 |
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| series | Frontiers in Digital Health |
| spelling | doaj-art-750cd59ca1f64ca49307a54b0902f20b2025-08-20T03:17:24ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2025-07-01710.3389/fdgth.2025.16107721610772Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tabletsShaheen N. Awan0Yael Bensoussan1Stephanie Watts2Micah Boyer3Robert Budinsky4Ruth H. Bahr5School of Communication Sciences and Disorders & The Communication Technologies Research Center, University of Central Florida, Orlando, FL, United StatesDepartment of Otolaryngology—Head Neck Surgery, University of South Florida Morsani College of Medicine, Tampa, FL, United StatesDepartment of Otolaryngology—Head Neck Surgery, University of South Florida Morsani College of Medicine, Tampa, FL, United StatesDepartment of Otolaryngology—Head Neck Surgery, University of South Florida Morsani College of Medicine, Tampa, FL, United StatesDepartment of Communication Sciences and Disorders, University of South Florida, Tampa, FL, United StatesDepartment of Communication Sciences and Disorders, University of South Florida, Tampa, FL, United StatesIntroductionThe Bridge2AI-Voice. Consortium is developing affordable and accessible voice data to assist in the identification of vocal biomarkers of disease in adults and children. Initial experiments were designed to establish voice recording procedures to be used in research labs and clinical settings, as well as in quiet environments outside of the clinic. The focus has been on isolated vowel productions, which provide a vocal signal that is representative of the biomechanics of the larynx within a static vocal tract. The current experiment considers the impact of sentence productions on the measurement of several acoustic parameters.MethodsVoice recordings from 24 individuals representing a wide range of typical and disordered voices were analyzed. Two CAPE-V sentences were recorded via a head-and-torso model using (1) a research quality, clinical standard microphone/preamplifier/audio interface and (2) smartphones and tablets using their internal microphones and an attached external headset microphone. Mouth-to-microphone distances and environmental noise levels were controlled. Measures of fundamental frequency (F0) and spectral and cepstral measures of voice quality valid for use in sentence contexts were analyzed across recording conditions.ResultsCepstral peak prominence (CPP) values were sensitive to microphone type, noise, and sentence type conditions. Nevertheless, strong linear relationships were observed across recording methods compared to the clinical standard. Measures of F0 obtained using autocorrelation correlated strongly across recording methods, whereas F0 measures obtained from the CPP (CPP F0) were highly variable and poorly correlated across recording methods and noise conditions. The L/H ratio (a measure of spectral tilt) was significantly affected by recording condition but not background noise, and measures of L/H ratio were also observed to correlate strongly across recording methods and noise conditions.DiscussionCurrent findings revealed that different recording methods can produce significantly different acoustic measures of voice with sentence-level materials. Since microphone characteristics (e.g., frequency response; use of noise cancellation), mouth-to-microphone distances, and background noise conditions can have significant effects on spectral and cepstral assessment of voice, it is essential that recording methods and conditions are explicitly described when designing voice data collection projects and comparing datasets as it may have an impact on voice analysis. Future investigations should evaluate consistency of results among multiple examples of the same device.https://www.frontiersin.org/articles/10.3389/fdgth.2025.1610772/fullvoice analysisacoustic analysismobile devicescepstral analysisspectral tiltbackground noise |
| spellingShingle | Shaheen N. Awan Yael Bensoussan Stephanie Watts Micah Boyer Robert Budinsky Ruth H. Bahr Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tablets Frontiers in Digital Health voice analysis acoustic analysis mobile devices cepstral analysis spectral tilt background noise |
| title | Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tablets |
| title_full | Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tablets |
| title_fullStr | Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tablets |
| title_full_unstemmed | Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tablets |
| title_short | Influence of recording instrumentation on measurements of voice in sentence contexts: use of smartphones and tablets |
| title_sort | influence of recording instrumentation on measurements of voice in sentence contexts use of smartphones and tablets |
| topic | voice analysis acoustic analysis mobile devices cepstral analysis spectral tilt background noise |
| url | https://www.frontiersin.org/articles/10.3389/fdgth.2025.1610772/full |
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