Data Viz Using ggplot2: Tips and Tricks for Creating Custom Figures in R

This project contains presentation materials from a guest lecture about using ggplot2 for data visualization in R. This guest lecture was prepared for CSD 491: Special Topics: Data Analytics in Communication Sciences and Disorders taught by Dr. Thea Knowles' at Michigan State University. This presentation was given on 4/19/2023. This project contains the presentation slides, Rmd scripts, and an R Markdown document that accompanied the presentation

Resources

The purpose of this project component is to curate and share a list of open science resources for researchers in communication science and disorders and related fields

OpenCSD

OpenCSD is a volunteer collective of researchers, clinicians, students, and educators in Communication Sciences and Disorders (CSD) aspiring to educate others and foster the use of open science practices within our field

The Effects of EMA Sensors on Speech in Individuals With and Without Dysarthria

Purpose: This study aimed to investigate the impact of electromagnetic articulography (EMA) sensor placement on acoustic and perceptual speech outcomes for speakers with and without dysarthria secondary to Parkinson’s disease (PD). Additionally, post-adaptation effects after removing EMA sensors were also examined in both speaker groups. Methods: A total of 34 speakers (21 Controls and 13 PD) completed three readings of the Caterpillar Passage: (1) Before Sensors, (2) With Sensors, and (3) After Sensors. Changes in acoustic (articulation rate, vowel space area, first and second spectral moment coefficients for fricatives) and perceptual (speech intelligibility, naturalness) measures were compared across the three time points (Before Sensors, With Sensors, and After Sensors). Results: Linear mixed-effects models indicated sensor placement effects for the spectral moment coefficients (M1 and M2) and both perceptual measures for both speaker groups. No significant post-adaptation effects were seen across all the acoustic and perceptual measures. Additionally, group differences in spectral and perceptual measures were seen, but the changes in these measures between the three time points were similar for both speaker groups. Conclusion: The results suggest that M1 and M2 and perceptual speech measures are sensitive to sensor placement and that sensor placement impacted these measures similarly for both control and PD speakers. However, limited evidence of post-adaptation effects was seen after the removal of sensors

The Effects of EMA Sensors on Speech in Individuals With and Without Dysarthria

Purpose: This study aimed to investigate the impact of electromagnetic articulography (EMA) sensor placement on acoustic and perceptual speech outcomes for speakers with and without dysarthria secondary to Parkinson’s disease (PD). Additionally, post-adaptation effects after removing EMA sensors were also examined in both speaker groups. Methods: A total of 34 speakers (21 Controls and 13 PD) completed three readings of the Caterpillar Passage: (1) Before Sensors, (2) With Sensors, and (3) After Sensors. Changes in acoustic (articulation rate, vowel space area, first and second spectral moment coefficients for fricatives) and perceptual (speech intelligibility, naturalness) measures were compared across the three time points (Before Sensors, With Sensors, and After Sensors). Results: Linear mixed-effects models indicated sensor placement effects for the spectral moment coefficients (M1 and M2) and both perceptual measures for both speaker groups. No significant post-adaptation effects were seen across all the acoustic and perceptual measures. Additionally, group differences in spectral and perceptual measures were seen, but the changes in these measures between the three time points were similar for both speaker groups. Conclusion: The results suggest that M1 and M2 and perceptual speech measures are sensitive to sensor placement and that sensor placement impacted these measures similarly for both control and PD speakers. However, limited evidence of post-adaptation effects was seen after the removal of sensors

The Reliability and Validity of Speech-Language Pathologists’ Estimations of Intelligibility in Dysarthria

This study examined the reliability and validity of speech-language pathologists’ (SLP) estimations of speech intelligibility in dysarthria, including a visual analog scale (VAS) method and a percent estimation method commonly used in clinical settings. Speech samples from 20 speakers with dysarthria of varying etiologies were used to collect orthographic transcriptions from naïve listeners n=70 and VAS ratings and percent estimations of intelligibility from SLPs n=21. Intra- and interrater reliability for the two SLP intelligibility measures were evaluated, and the relationship between these measures was assessed. Finally, linear regression was used to evaluate the relationship between the naïve listeners’ orthographic transcription scores and the two SLP intelligibility measures. The results indicated that the intrarater reliability for both SLP intelligibility measures was strong, and the interrater reliability between the SLP ratings was moderate to excellent. A moderate positive relationship between SLPs’ VAS ratings and percent estimations was also observed. Finally, both SLPs’ percent estimations and VAS ratings were predictive of naïve listeners’ orthographic transcription scores, with SLPs’ percent estimations being the strongest predictor. In conclusion, the average SLP percent estimations and VAS ratings are valid and reliable intelligibility measures. However, the validity and reliability of these measures vary between SLPs

Vowel Acoustics as Predictors of Speech Intelligibility in Dysarthria

Purpose: To examine the predictive value of a selection of acoustic vowel measures for predicting intelligibility (i.e., measured using both orthographic transcriptions [OT] and visual analog scale [VAS] ratings) in speakers with dysarthria. The following questions were posed: (1) How well do trajectory-based and token-based vowel space measures predict intelligibility? And (2) does the relationship between vowel measures and intelligibility differ based on the type of intelligibility measurement (i.e., OT vs. VAS ratings)? Method: The Grandfather Passage was read aloud by forty speakers with dysarthria of varying etiologies, including Parkinson's disease (n = 10), amyotrophic lateral sclerosis (n = 10), Huntington's disease (n = 10), and cerebellar ataxia (n = 10). Token-based (i.e., acoustic vowel space area [VSA], corner dispersion) and trajectory-based (i.e., VSA hull area, and vowel space density [VSD]) acoustic vowel measures were calculated. Naïve listeners (N = 140) were recruited via crowdsourcing to provide OT and VAS intelligibility ratings. Hierarchical linear regression models were created to model OT and VAS ratings of intelligibility using the acoustic vowel measures as predictors. Results: Traditional VSA was the sole significant predictor of speech intelligibility for both the OT and VAS models. In contrast, the trajectory-based measures were not significant predictors of intelligibility. Additionally, the OT and VAS intelligibility ratings conveyed similar information. Conclusions: The findings suggest that traditional token-based vowel measures better predict intelligibility than trajectory-based measures. Additionally, the findings suggest that VAS methods are comparable to OT methods for estimating speech intelligibility for research purposes

The Reliability and Validity of Speech Language Pathologists' Estimations of Speech Intelligibility in Dysarthria

The current study examined the reliability and validity of speech-language pathologists’ (SLP) estimations of speech intelligibility in dysarthria, including a visual analog scale (VAS) method and a percent estimation method commonly used in clinical settings. Speech samples from 20 speakers with dysarthria were used to collect orthographic transcriptions from naïve listeners (n=70) and VAS ratings and percent estimations of intelligibility from SLPs (n=21). Intra- and interrater reliability for the two SLP intelligibility measures were evaluated, and the relationship between these measures was assessed. Finally, linear regression was used to evaluate the relationship between the naïve listeners’ orthographic transcription scores and the two SLP intelligibility measures. The results indicated the intrarater agreement for both the SLP intelligibility measures was high, and the interrater agreement between the SLP ratings was moderate to excellent. Additionally, a moderate positive relationship between SLPs’ VAS ratings and percent estimations was observed. Finally, both SLPs’ percent estimations and VAS ratings were predictive of naïve listeners’ orthographic transcription scores, with SLPs’ percent estimations being the strongest predictor. In conclusion, the aggregate SLP intelligibility estimations and VAS ratings are valid and reliable measures for estimating intelligibility. However, the validity and reliability of these measures vary between SLPs