Shaheen N Awan, Ruth Bahr, Stephanie Watts, Micah Boyer, Robert Budinsky, Yael Bensoussan
{"title":"从 Bridge2AI-Voice 声音实验中获得的基于证据的平板电脑录音建议。","authors":"Shaheen N Awan, Ruth Bahr, Stephanie Watts, Micah Boyer, Robert Budinsky, Yael Bensoussan","doi":"10.1016/j.jvoice.2024.08.029","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>As part of a larger goal to create best practices for voice data collection to fuel voice artificial intelligence (AI) research, the objective of this study was to investigate the ability of readily available iOS and Android tablets with and without low-cost headset microphones to produce recordings and subsequent acoustic measures of voice comparable to \"research quality\" instrumentation.</p><p><strong>Methods: </strong>Recordings of 24 sustained vowel samples representing a wide range of typical and disordered voices were played via a head-and-torso model and recorded using a research quality standard microphone/preamplifier/audio interface. Acoustic measurements from the standard were compared with two popular tablets using their built-in microphones and with low-cost headset microphones at different distances from the mouth.</p><p><strong>Results: </strong>Voice measurements obtained via tablets + headset microphones close to the mouth (2.5 and 5 cm) strongly correlated (r's > 0.90) with the research standard and resulted in no significant differences for measures of vocal frequency and perturbation. In contrast, voice measurements obtained using the tablets' built-in microphones at typical reading distances (30 and 45 cm) tended to show substantial variability in measurement, greater mean differences in voice measurements, and relatively poorer correlations vs the standard.</p><p><strong>Conclusion: </strong>Findings from this study support preliminary recommendations from the Bridge2AI-Voice Consortium recommending the use of smartphones paired with low-cost headset microphones as adequate methods of recording for large-scale voice data collection from a variety of clinical and nonclinical settings. Compared with recording using a tablet direct, a headset microphone controls for recording distance and reduces the effects of background noise, resulting in decreased variability in recording quality.</p><p><strong>Data availability: </strong>Data supporting the results reported in this article may be obtained upon request from the contact author.</p>","PeriodicalId":49954,"journal":{"name":"Journal of Voice","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evidence-Based Recommendations for Tablet Recordings From the Bridge2AI-Voice Acoustic Experiments.\",\"authors\":\"Shaheen N Awan, Ruth Bahr, Stephanie Watts, Micah Boyer, Robert Budinsky, Yael Bensoussan\",\"doi\":\"10.1016/j.jvoice.2024.08.029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>As part of a larger goal to create best practices for voice data collection to fuel voice artificial intelligence (AI) research, the objective of this study was to investigate the ability of readily available iOS and Android tablets with and without low-cost headset microphones to produce recordings and subsequent acoustic measures of voice comparable to \\\"research quality\\\" instrumentation.</p><p><strong>Methods: </strong>Recordings of 24 sustained vowel samples representing a wide range of typical and disordered voices were played via a head-and-torso model and recorded using a research quality standard microphone/preamplifier/audio interface. Acoustic measurements from the standard were compared with two popular tablets using their built-in microphones and with low-cost headset microphones at different distances from the mouth.</p><p><strong>Results: </strong>Voice measurements obtained via tablets + headset microphones close to the mouth (2.5 and 5 cm) strongly correlated (r's > 0.90) with the research standard and resulted in no significant differences for measures of vocal frequency and perturbation. In contrast, voice measurements obtained using the tablets' built-in microphones at typical reading distances (30 and 45 cm) tended to show substantial variability in measurement, greater mean differences in voice measurements, and relatively poorer correlations vs the standard.</p><p><strong>Conclusion: </strong>Findings from this study support preliminary recommendations from the Bridge2AI-Voice Consortium recommending the use of smartphones paired with low-cost headset microphones as adequate methods of recording for large-scale voice data collection from a variety of clinical and nonclinical settings. Compared with recording using a tablet direct, a headset microphone controls for recording distance and reduces the effects of background noise, resulting in decreased variability in recording quality.</p><p><strong>Data availability: </strong>Data supporting the results reported in this article may be obtained upon request from the contact author.</p>\",\"PeriodicalId\":49954,\"journal\":{\"name\":\"Journal of Voice\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Voice\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jvoice.2024.08.029\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Voice","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jvoice.2024.08.029","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY","Score":null,"Total":0}
Evidence-Based Recommendations for Tablet Recordings From the Bridge2AI-Voice Acoustic Experiments.
Background: As part of a larger goal to create best practices for voice data collection to fuel voice artificial intelligence (AI) research, the objective of this study was to investigate the ability of readily available iOS and Android tablets with and without low-cost headset microphones to produce recordings and subsequent acoustic measures of voice comparable to "research quality" instrumentation.
Methods: Recordings of 24 sustained vowel samples representing a wide range of typical and disordered voices were played via a head-and-torso model and recorded using a research quality standard microphone/preamplifier/audio interface. Acoustic measurements from the standard were compared with two popular tablets using their built-in microphones and with low-cost headset microphones at different distances from the mouth.
Results: Voice measurements obtained via tablets + headset microphones close to the mouth (2.5 and 5 cm) strongly correlated (r's > 0.90) with the research standard and resulted in no significant differences for measures of vocal frequency and perturbation. In contrast, voice measurements obtained using the tablets' built-in microphones at typical reading distances (30 and 45 cm) tended to show substantial variability in measurement, greater mean differences in voice measurements, and relatively poorer correlations vs the standard.
Conclusion: Findings from this study support preliminary recommendations from the Bridge2AI-Voice Consortium recommending the use of smartphones paired with low-cost headset microphones as adequate methods of recording for large-scale voice data collection from a variety of clinical and nonclinical settings. Compared with recording using a tablet direct, a headset microphone controls for recording distance and reduces the effects of background noise, resulting in decreased variability in recording quality.
Data availability: Data supporting the results reported in this article may be obtained upon request from the contact author.
期刊介绍:
The Journal of Voice is widely regarded as the world''s premiere journal for voice medicine and research. This peer-reviewed publication is listed in Index Medicus and is indexed by the Institute for Scientific Information. The journal contains articles written by experts throughout the world on all topics in voice sciences, voice medicine and surgery, and speech-language pathologists'' management of voice-related problems. The journal includes clinical articles, clinical research, and laboratory research. Members of the Foundation receive the journal as a benefit of membership.