Restricted Research - Award List, Note/Discussion Page

Fiscal Year: 2023

2298  The University of Texas at San Antonio  (144186)

Principal Investigator: Wang,Wei

Total Amount of Contract, Award, or Gift (Annual before 2011): $ 770,939

Exceeds $250,000 (Is it flagged?): Yes

Start and End Dates: 6/15/22 - 5/31/25

Restricted Research: YES

Academic Discipline: none

Department, Center, School, or Institute: CAPRI

Title of Contract, Award, or Gift: Programming and Machine Learning Education for Students with Vision Impairments through Compilers, AI and Cloud Technologies - 2202632

Name of Granting or Contracting Agency/Entity: National Science Foundation (LOC)
CFDA Link: NSF
47.076

Program Title: none
CFDA Linked: Education and Human Resources

Note:

SAMs 1.1.1 In this project, the PIs propose to develop a novel screen reader for computer programs written in Python. This new screen reader will be able to understand the structure of computer programs and statements, and output proper speech accordingly. The new screen reader will utilize Python interpreter’s syntax analysis to understand programs and statements. Moreover, based on AI-enabled voice recognition, the PIs plan to support voice-based navigation commands, such as locating a specific variable declaration or move cursors to a specific token in a statement. Both the screen reader and the voice-based code navigation system will be integrated into Jupyter notebook and offered through the cloud to allow students and educators from the whole country to benefit from it. The cloud-based solution also allows more sophisticated and accurate voice recognition systems to be employed without requiring the students to have powerful and expensive computers. The PIs will evaluate the effectiveness of the proposed new screen reader and voice-based code navigation system in teaching programming and machine learning. They will also investigate and evaluate different speech styles and voice commands to determine the most effective style and necessary voice commands. Additional feedback will also be collected from the students to further improve these tools in the future.

Discussion: No discussion notes

 

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