micah-hirsch Goto Github PK

data-viz-using-ggplot2

This repository contains the data and code used for a guest lecture on data visualization using ggplot2 in R. The guest lecture was given for Dr. Thea Knowles' class

le-cognitive-study

This repository holds the data preparation and analysis code for the cognitive listening effort study.

learning-python

I am learning how to code in Python. So this repository will contain my scripts with practice problems and notes.

listening-effort-in-dysarthria

This is the repository for my dissertation project investigating listening effort in dysarthric speech. The details of this repository will be updated as this project continues

older_adult_pl_study_analysis

This repository contains the data processing and analysis scripts for the older adult perceptual learning study.

preliminary-listener-comfort-scale-analysis

This is the code for preliminary analysis on the first draft of the Listener Comfort Scale. 10 participants listened to either a talker with dysarthria or a talker with no motor speech disorder and completed the draft version of the listener comfort scale and the rating scale from Schölderle et al. (2019).

sensor-effects-project

This repo contains the data prep and analysis code for the sensor effects project, led by Dr. Yunjung Kim.

slp-intelligibility-of-dysarthric-speech

In this repository, the cleaned dataset and analysis code for the project "The reliability and validity of speech language pathologists' estimations of speech intelligibility in dysarthria" is provided. This project's main objective was to establish the reliability and validity of SLPs' intelligibility estimations of dysarthric speech. The results showed that the SLPs' intelligibility estimations were generally predictive of naive listener intelligibility. However, the interrater reliability for individual SLP ratings was moderate. All data cleaning and analyses were completed using R. These results were recently presented at the 2021 American Speech Language Hearing Association (ASHA) Convention and are currently in-preparation for publication. If you have any questions about the project or analyses, please contact either Micah Hirsch at [email protected] or Austin Thompson at [email protected].

tidy-tuesday

vowel-acoustics-as-predictors-of-speech-intelligibility-in-dysarthria

This is the data analysis and code for our project "Vowel Acoustics as Predictors of Speech Intelligibility in Dysarthria". In this repository, we provide a clean version of our data set, an Rmd file containing our analysis code, and an Rmd file containing our data prep and cleaning code. All coding was done using R. This work was presented at the 2022 Motor Speech Conference in Charleston, SC and is currently in prep for publication. If you have any questions, please contact either Micah Hirsch at [email protected] or Austin Thompson at [email protected]