Refining algorithmic estimation of relative fundamental frequency: Accounting for sample characteristics and fundamental frequency estimation method.

Relative fundamental frequency (RFF) is a promising acoustic measure for evaluating voice disorders. Yet, the accuracy of the current RFF algorithm varies across a broad range of vocal signals. The authors investigated how fundamental frequency (fo) estimation and sample characteristics impact the relationship between manual and semi-automated RFF estimates. Acoustic recordings were collected from 227 individuals with and 256 individuals without voice disorders. Common fo estimation techniques were compared to the autocorrelation method currently implemented in the RFF algorithm. Pitch strength-based categories were constructed using a training set (1158 samples), and algorithm thresholds were tuned to each category. RFF was then computed on an independent test set (291 samples) using category-specific thresholds and compared against manual RFF via mean bias error (MBE) and root-mean-square error (RMSE). Auditory-SWIPE' for fo estimation led to the greatest correspondence with manual RFF and was implemented in concert with category-specific thresholds. Refining fo estimation and accounting for sample characteristics led to increased correspondence with manual RFF [MBE = 0.01 semitones (ST), RMSE = 0.28 ST] compared to the unmodified algorithm (MBE = 0.90 ST, RMSE = 0.34 ST), reducing the MBE and RMSE of semi-automated RFF estimates by 88.4% and 17.3%, respectively.

Optimized and Predictive Phonemic Interfaces for Augmentative and Alternative Communication.

Purpose We empirically assessed the results of computational optimization and prediction in communication interfaces that were designed to allow individuals with severe motor speech disorders to select phonemes and generate speech output. Method Interface layouts were either random or optimized, in which phoneme targets that were likely to be selected together were located in proximity. Target sizes were either static or predictive, such that likely targets were dynamically enlarged following each selection. Communication interfaces were evaluated by 36 users without motor impairments using an alternate access method. Each user was assigned to 1 of 4 interfaces varying in layout and whether prediction was implemented (random/static, random/predictive, optimized/static, optimized/predictive) and participated in 12 sessions over a 3-week period. Six participants with severe motor impairments used both the optimized/static and optimized/predictive interfaces in 1-2 sessions. Results In individuals without motor impairments, prediction provided significantly faster communication rates during training (Sessions 1-9), as users were learning the interface target locations and the novel access method. After training, optimization acted to significantly increase communication rates. The optimization likely became relevant only after training when participants knew the target locations and moved directly to the targets. Participants with motor impairments could use the interfaces with alternate access methods and generally rated the interface with prediction as preferred. Conclusions Optimization and prediction led to increases in communication rates in users without motor impairments. Predictive interfaces were preferred by users with motor impairments. Future research is needed to translate these results into clinical practice. Supplemental Material https://doi.org/10.23641/asha.8636948.

Pitch Shifting With the Commercially Available Eventide Eclipse: Intended and Unintended Changes to the Speech Signal.

Purpose This study details the intended and unintended consequences of pitch shifting with the commercially available Eventide Eclipse. Method Ten vocally healthy participants ( M = 22.0 years; 6 cisgender females, 4 cisgender males) produced a sustained /ɑ/, creating an input signal. This input signal was processed in near real time by the Eventide Eclipse to create an output signal that was either not shifted (0 cents), shifted +100 cents, or shifted -100 cents. Shifts occurred either throughout the entire vocalization or for a 200-ms period after vocal onset. Results Input signals were compared to output signals to examine potential changes. Average pitch-shift magnitudes were within 1 cent of the intended pitch shift. Measured pitch-shift length for intended 200-ms shifts was between 5.9% and 21.7% less than expected, based on the portion of shift selected for measurement. The delay between input and output signals was an average of 11.1 ms. Trials shifted +100 cents had a longer delay than trials shifted -100 or 0 cents. The first 2 formants (F1, F2) shifted in the direction of the pitch shift, with F1 shifting 6.5% and F2 shifting 6.0%. Conclusions The Eventide Eclipse is an accurate pitch-shifting hardware that can be used to explore voice and vocal motor control. The pitch-shifting algorithm shifts all frequencies, resulting in a subsequent change in F1 and F2 during pitch-shifted trials. Researchers using this device should be mindful of stimuli selection to avoid confusion during data interpretation.