Introduction of Voice Type Component (VTC) as an Effective Acoustic Voice Analysis Method in Tele-evaluation

Telepractice in voice health care and evaluation services has attracted much attention in recent years. Multiple studies have proven the effectiveness of voice therapy with telepractice. However, voice evaluations are still mostly conducted in person due to the lack of sensitive acoustic analysis methods.

This study examined various acoustic analysis methods for voice evaluation in telepractice. Eighteen female elementary school teachers with self-reported voice disorders volunteered to participate in the study. Speech samples were collected before and after the interventions using two voice sampling methods concurrently. One set of data was collected using the traditional voice sample collection method by the therapist in person. The second set of data was collected on the same speech samples using the clients' own smartphones, and the collected voice samples were later sent to the researcher for further acoustic analysis. The voice type component (VTC) measurement represented the proportion of different VTCs in a voice by measuring the chaos and intrinsic dimension.

Voice analyses were conducted on both sets of data, and the correlation between the two sampling procedures was analyzed. It appears that the VTC could be a more reliable method for producing acoustic analysis results with voice samples collected from smartphones compared to other objective voice assessment procedures. This reliability has been demonstrated via statistical analysis, including correlation coefficient, pairwise t test, d-prime, and area under the curve. The results of this study highlighted the VTC as an effective and accurate acoustic analysis method in tele-evaluation.

This feasible voice sampling method, which utilizes participants' own smartphones, will reduce barriers to accessing limited voice specialists due to distance and will decrease the cost of care by minimizing expenses associated with travel and additional equipment for voice sampling. Ultimately, this approach will enhance the effectiveness of voice care delivered through telepractice to patients in remote and underserved areas.