“It feels like we're not meeting the criteria”: Examining and Mitigating the Cascading Effects of Bias in Automatic Speech Recognition in Spoken Language Interfaces.
Open Access
- 25 April 2025
- conference paper
- Published by Association for Computing Machinery (ACM)
- p. 1-13
Abstract
No abstract availableFunding Information
- NSF (National Science Foundation) (DRL 1920510)
- Learning Engineering Virtual Institutes
This publication has 88 references indexed in Scilit:
- High School English Teachers Reflect on Their Talk: A Study of Response to Automated Feedback with the Teacher Talk ToolInternational Journal of Artificial Intelligence in Education, 2024
- Improving collaborative problem-solving skills via automated feedback and scaffolding: a quasi-experimental study with CPSCoach 2.0User Modeling and User-Adapted Interaction, 2024
- Towards inclusive automatic speech recognitionComputer Speech & Language, 2023
- Hey ASR System! Why Aren’t You More Inclusive?2022
- The Promises and Challenges of Artificial Intelligence for Teachers: a Systematic Review of ResearchTechTrends, 2022
- Algorithmic injustice: a relational ethics approachPatterns, 2021
- Automatic Speech Recognition2019
- Selling students short: Racial differences in teachers’ evaluations of high, average, and low performing studentsSocial Science Research, 2015
- A Study of Automatic Speech Recognition in Noisy Classroom Environments for Automated Dialog Analysis2015
- Optimal caliper widths for propensity‐score matching when estimating differences in means and differences in proportions in observational studiesPharmaceutical Statistics, 2011