## 2 Materials and Methods
### Data Analysis  
#### 2.3.1 High-Speed Video Processing  
Technician Training  
A semi-automated algorithm was used to identify the physiological termination and initiation of vocal fold vibration from each /ifi/ production. To carry out this processing, a series of technicians used the algorithm to compute the glottic angle waveform, from which vocal fold abductory and adductory patterns were isolated. The training and experimental data processing schemes used to extract vocal fold vibratory features are described in detail below. Prior to processing experimental data, nine technicians underwent a training scheme described by [PERSON] et al. [37]. In brief, technicians were first trained to measure glottic angles (extending from the anterior commussure along the medial vocal fold edge to the vocal process) from images obtained during a flexible nasendoscopic procedure using a halogen light source and acquired at a conventional framerate of 30 frames per second. Technicians were required to meet two-way mixed-effects intraclass correlation coefficients (ICC) for consistency of agreement \(\geq\)0.80 when compared to glottic angle markings made previously by a gold-standard technician [38]. The average reliability for the nine technicians was _ICC(3,1)_ = 0.89 (SD = 0.01, range = 0.88-0.91). The nine technicians then completed training to use a semi-automated glottic angle tracking algorithm, as described in detail in [PERSON] et al. [38]. Using this algorithm, the technicians were trained to use time-aligned microphone signal and video frames captured during an /ifi/ utterance to semi-automatically estimate the glottic angle over time. Within the glottic angle tracking training, technicians were required to meet agreement standards of _ICC(3,1)_ \(\geq\) 0.80 compared to a gold-standard technician, described in [PERSON] et al. [38]. The resulting average reliability of the nine technicians was _ICC(3,1)_ = 0.85 (SD = 0.04, range = 0.80-0.91). Experimental Data Processing  
To process experimental data, technicians first determined whether each /ifi/ production was analyzable based on manual inspection of the laryngoscopic recordings. An /ifi/ production was rejected from further analysis if the glottis was obstructed (e.g., by the epiglottis), if video quality was too poor to resolve the glottis, or if an /ifi/ production at the end of the recording was incompletely captured due to the pre-defined recording length. Of the potential 9172 /ifi/ productions recorded, 12.8% were considered unusable (1173 of 9172), leaving 7999 for further processing. Technicians then used the semi-automated angle algorithm to calculate the glottic angle waveform for the usable /ifi/ productions (N = 7999). Within this analysis, each of the nine technicians was assigned to analyze a subset of the 122 speakers, wherein the assigned technician processed all /ifi/ productions of each speaker within the subset. Assigned technicians were blinded to the diagnosis of the speakers in their analysis set. For each speaker, the assigned technician determined whether the /ifi/ production was usable and, if so, obtained a quantitative estimate of the glottic angle for the production. During this process, all /ifi/ productions assigned to a technician were visually inspected to ensure that the anterior one-third of the vocal folds (anterior commussure) was visible for the semi-automated algorithm to sufficiently track the vocal folds over time. Manual intervention was implemented if algorithmic estimates of the glottic angle waveform was deemed inappropriate by the technician; if errors persisted following manual intervention, the technicians were instructed to mark the instance as unusable. The technicians accepted the fully automated results in 75.0% of cases (6000 of 7999), whereas the technicians accepted the automated results only after performing manual glottic angle intervention in 21.5% of cases (1721 of 7999).