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Purpose: This study compares two electromagnetic articulographs manufactured by Northern Digital, Inc.: the NDI Wave System (from 2008) and the NDI Vox-EMA System (from 2020). Method: Four experiments were completed: (1) comparison of statically positioned sensors; (2) tracking dynamic movements of sensors manipulated using a motor-driven LEGO apparatus; (3) tracking small and large movements of sensors mounted in a rigid bar manipulated by hand; and (4) tracking movements of sensors rotated on a circular disc. We assessed spatial variability for statically positioned sensors, variability in the transduced Euclidean distances between sensor pairs, and missing data rates. For sensors tracking circular movements, we compared the fit between fitted ideal circles and actual trajectories. Results: The average sensor pair tracking error (i.e., the standard deviation of the Euclidean distances) was 1.37 mm for the WAVE and 0.12 mm for the VOX during automated trials at the fastest speed, and 0.35 mm for the WAVE and 0.14 mm for the VOX during the tracking of large manual movements. The average standard deviation of the fitted circle radii charted by manual circular disc movements was 0.72 mm for the WAVE sensors and 0.14 mm for the VOX sensors. There was no significant difference between the WAVE and the VOX in the number of missing frames. Conclusions: In general, the VOX system significantly outperformed the WAVE on measures of both static precision and dynamic accuracy (automated and manual). For both systems, positional precision and spatial variability were influenced by the sensors' position relative to the field generator unit (worse when further away).

Purpose: This study compares two electromagnetic articulographs manufactured by Northern Digital, Inc.: the NDI Wave System (from 2008) and the NDI Vox-EMA System (from 2020). Method: Four experiments were completed: (a) comparison of statically positioned sensors, (b) tracking dynamic movements of sensors manipulated using a motor-driven LEGO apparatus, (c) tracking small and large movements of sensors mounted in a rigid bar manipulated by hand, and (d) tracking movements of sensors rotated on a circular disc. We assessed spatial variability for statically positioned sensors, variability in the transduced Euclidean distances between sensor pairs, and missing data rates. For sensors tracking circular movements, we compared the fit between fitted ideal circles and actual trajectories. Results: The average sensor pair tracking error (i.e., the standard deviation of the Euclidean distances) was 1.37 mm for the WAVE and 0.12 mm for the VOX during automated trials at the fastest speed, and 0.35 mm for the WAVE and 0.14 mm for the VOX during the tracking of large manual movements. The average standard deviation of the fitted circle radii charted by manual circular disc movements was 0.72 mm for the WAVE sensors and 0.14 mm for the VOX sensors. There was no significant difference between the WAVE and the VOX in the number of missing frames. Conclusions: In general, the VOX system significantly outperformed the WAVE on measures of both static precision and dynamic accuracy (automated and manual). For both systems, positional precision and spatial variability were influenced by the sensors' position relative to the field generator unit (worse when further away). Supplemental Material: https://doi.org/10.23641/asha. 14787846, Electromagnetic articulography (EMA) has been used for more than 3 decades in the study of speech and other processes involving movements of the articulators (e.g., mastication or deglutition; Hoole & [...]

Purpose: The purpose of this study was to quantify sentence-level articulatory kinematics in individuals treated for oral squamous cell carcinoma (ITOC) compared to control speakers while also assessing the effect of treatment site (jaw vs. tongue). Furthermore, this study aimed to assess the relation between articulatory-kinematic measures and self-reported speech problems. Method: Articulatory-kinematic data from the tongue tip, tongue back, and jaw were collected using electromagnetic articulography in nine Dutch ITOC and eight control speakers. To quantify articulatory kinematics, the two-dimensional articulatory working space (AWS; in mm² ), one-dimensional anteroposterior range of motion (AP-ROM; in mm), and superior-inferior range of motion (SIROM in mm) were calculated and examined. Self-reported speech problems were assessed with the Speech Handicap Index (SHI). Results: Compared to a sex-matched control group, ITOC showed significantly smaller AWS, AP-ROM, and SI-ROM for both the tongue tip and tongue back sensor, but no significant differences were observed for the jaw sensor. This pattern was found for both individuals treated for tongue and jaw tumors. Moderate nonsignificant correlations were found between the SHI and the AWS of the tongue back and jaw sensors. Conclusions: Despite large individual variation, ITOC showed reduced one- and two-dimensional tongue, but not jaw, movements compared to control speakers and treatment for tongue and jaw tumors resulted in smaller tongue movements. A larger sample size is needed to establish a more generalizable connection between the AWS and the SHI. Further research should explore how these kinematic changes in ITOC are related to acoustic and perceptual measures of speech. [ABSTRACT FROM AUTHOR]

Alcohol intoxication is known to affect many aspects of human behavior and cognition; one of such affected systems is articulation during speech production. Although much research has revealed that alcohol negatively impacts pronunciation in a first language (L1), there is only initial evidence suggesting a potential beneficial effect of inebriation on articulation in a non-native language (L2). The aim of this study was thus to compare the effect of alcohol consumption on pronunciation in an L1 and an L2. Participants who had ingested different amounts of alcohol provided speech samples in their L1 (Dutch) and L2 (English), and native speakers of each language subsequently rated the pronunciation of these samples on their intelligibility (for the L1) and accent nativelikeness (for the L2). These data were analyzed with generalized additive mixed modeling. Participants' blood alcohol concentration indeed negatively affected pronunciation in L1, but it produced no significant effect on the L2 accent ratings. The expected negative impact of alcohol on L1 articulation can be explained by reduction in fine motor control. We present two hypotheses to account for the absence of any effects of intoxication on L2 pronunciation: (1) there may be a reduction in L1 interference on L2 speech due to decreased motor control or (2) alcohol may produce a differential effect on each of the two linguistic subsystems. [ABSTRACT FROM AUTHOR]

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