Longitudinal Changes in Pitch-Related Acoustic Characteristics of the Voice Throughout the Menstrual Cycle:...

Identifying subtle changes in the menstrual cycle is crucial for effective fertility tracking and understanding reproductive health.

The aim of the study is to explore how fundamental frequency features vary between menstrual phases using daily voice recordings.

This study analyzed smartphone-collected voice recordings from 16 naturally cycling female participants, collected every day for 1 full menstrual cycle. Fundamental frequency features (mean, SD, 5th percentile, and 95th percentile) were extracted from each voice recording. Ovulation was estimated using luteinizing hormone urine tests taken every morning. The analysis included comparisons of these features between the follicular and luteal phases and the application of changepoint detection algorithms to assess changes and pinpoint the day in which the shifts in vocal pitch occur.

The fundamental frequency SD was 9.0% (SD 2.9%) lower in the luteal phase compared to the follicular phase (95% CI 3.4%-14.7%; P=.002), and the 5th percentile of the fundamental frequency was 8.8% (SD 3.6%) higher (95% CI 1.7%-16.0%; P=.01). No significant differences were found between phases in mean fundamental frequency or the 95th percentile of the fundamental frequency (P=.65 and P=.07). Changepoint detection, applied separately to each feature, identified the point in time when vocal frequency behaviors shifted. For the fundamental frequency SD and 5th percentile, 81% (n=13) of participants exhibited shifts within the fertile window (P=.03). In comparison, only 63% (n=10; P=.24) and 50% (n=8; P=.50) of participants had shifts in the fertile window for the mean and 95th percentile of the fundamental frequency, respectively.

These findings indicate that subtle variations in vocal pitch may reflect changes associated with the menstrual cycle, suggesting the potential for developing a noninvasive and convenient method for monitoring reproductive health. Changepoint detection may provide a promising avenue for future work in longitudinal fertility analysis.