Arlington, Virginia
March 12, 2023
March 12, 2023
March 14, 2023
Diversity and Professional Engineering Education Papers
9
10.18260/1-2--44998
https://peer.asee.org/44998
61
Chang Ren is a lab member of the Human-Computer Interaction Lab of Dr. Cheryl Seals from the Department of Computer Science and Software Engineering at Auburn University. Chang received a master's degree in computer science from Auburn University in 2018, and currently studying for a Ph.D. Chang's current research focuses on designing an ASR-based speech training system for young children with speech disorders by incorporating gamification techniques to increase children's motivation for speech therapy through a more interactive experience.
Dr. Cheryl Denise Seals is a professor in Auburn University's Department of Computer Science and Software Engineering. She graduated with a B.S. C.S. from Grambling State University, M.S. C.S. from North Carolina A&T State University, and a Ph.D. C.S. from Virginia Tech. Seals conducts research in Human-Centered Articffidial Intelligence U & HCI with an emphasis on visual programming of educational simulations, user interface design & evaluation, and educational gaming technologies. Dr. Seals also works with computing outreach initiatives to improve CS education at all levels by a focused approach to increase the computing pipeline by getting students interested in STEM disciplines and future technology careers. One of these initiatives is the iAAMCS (Institute for African American Mentoring in Computing Sciences) & STARS Alliance (starsalliance.org) with programs in K-12 outreach, community service, student leadership, and computing diversity research.
Dongji Feng a passionate NLP Ph.D. candidate working with Dr.Santu in BDI Lab . His interesting areas are Information Retrieval(IR), Natural Language Processing (NLP) and related evaluation metrics.
A speech disorder refers to the inability to correctly form the sounds of words. It can affect a child's communication and academic performance and their level of interaction with peers and adults. Approximately one-in-ten children develop differently than their peers and may need support. Practical pronunciation training requires prolonged supervised practice and interaction. However, such instruction is limited to children with long-term exposure to speech-language pathologists (SLPs), determined by the shortage of highly skilled speech therapists.
In this study, we proposed a computer-based speech therapy system for young children using ASR technology in a personalized and accessible manner that mimics the knowledge of speech therapists. The proposed method with the phone-level ASR model applied high-resolution Mel-frequency cepstral coefficients as features and bidirectional Long-Short Term Memory as an encoder. The Speech Exemplar and Evaluation Database (SEED) data set, including the disordered and non-disordered speech of young children, was used for training and testing. We aim to increase young children's motivation to complete speech therapy through a more interactive game experience during this work. We will collaborate with participatory design partners (i.e., experts in communications disorders) to refine system requirements. Based on these interactions and a review of previous system versions, we will refine the design of an interactive user interface to incorporate the model to improve engagement and provide intuitive, consistent, and well-designed automatically derived feedback for young children and begin iterative prototype development.
Ren, C., & Seals, C., & Feng, D. (2023, March), Designing an ASR-based Interactive Game for Enhancing Speech Therapy to encourage young children to adhere to therapy protocols: A Case Study in User Interface Design Paper presented at ASEE Southeast Section Conference, Arlington, Virginia. 10.18260/1-2--44998
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