CAST: Child Automated Speech-to-Text Team
Advisor:
Description:
Many social science and education fields engage in significant research on parent-child verbal interactions. Unfortunately, many barriers exist to efficiently completing this research such as the cumbersome nature of transcribing (typically by hand) the verbal interactions that are observed or recorded during such research. Although much work has been done in adult speech-to-text, far less has been conducted with young children because of the rapidly changing nature of their speech. Using existing speech datasets, this team will develop an automated speech-to-text algorithm that works with young children (3-5 years old) and create a functional user interface.
During the 2022-2023 academic year, the CAST team will focus on iterating on the machine learning models that have been developed thus far as well as developing new algorithms that will help complete the project. The team will also begin development of a front-end user interface that will house the speech-to-text model.
Students interested in joining the CAST team must contact Dr. Purpura before joining the team.
Video Links:
- General Overview of Project- https://youtu.be/OR7JrfRWmjA
- Technical Overview of Speech-to-Text Model- https://youtu.be/CcJCInmP5HI
Relevant Technologies:
- Machine Learning
- Natural Language Processing
- Signal Processing
Prerequisites:
Python or other related programming language