NSF Award
2418277
The broader impact of this I-Corps project is the development of a language learning technology tailored for young children from various ethnic backgrounds. Currently, the world is increasingly becoming more diverse and the need for children to learn multiple languages is growing. The technology may allow children to learn how to speak in their native language and also learn how to speak English, Spanish, French, as well as other languages. The technology uses audio recordings of family members, which are then edited and crafted into fun and interactive language-learning experiences for kids. The use of family members’ voices may also provide a more personal and engaging experience for children, allowing them to feel more connected to their culture. In addition, children can make their own stories, giving them a sense of pride and ownership of their language learning. The technology may benefit natural language processing scientists and researchers who conduct race related research in universities and institutes, parents of children with ethnic backgrounds looking to use inclusive assisted technologies for speech, school districts and teachers who use edtech to assist students with the language learning process, and speech language pathologists and their practices looking to incorporate the use of language learning products from a culturally-responsive pedagogical framework.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the proposed technology. The technology is based on the prior development of diverse, equitable, and inclusive natural language processing (NLP) for the purpose of assisting young diverse learners with speech challenges. The use of natural language processing as assistive technology embedded in language learning products is becoming increasingly important for children during their language learning process. Natural language processing is used to interpret and understand spoken language, while speech recognition software is used to recognize the spoken words and convert them into text. In addition, a user interface and data storage will be used to store the recordings and play them back to compare the child’s own voice to the recorded voice of family members. The technology addresses the educational needs of children but also aligns with the broader societal goals of fostering inclusivity and diversity in this emerging field.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
