High School students use LDC data
A team of students at Thomas Jefferson High School for Science and Technology in Alexandria, VA, USA, have used an LDC database for the development of a device to help autistic children recognize emotions. This team was funded by a grant from the Lemelson-MIT InvenTeam Initiative Program. InvenTeams are groups of high school students, teachers, and mentors that receive grants up to US$10,000 each to invent technological solutions to real-world problems.
The team set out to invent an emotive aid in the form of a bracelet that uses a computational algorithm to extract emotional signatures from speech and display expressed emotions in real-time during a conversation. Potential beneficiaries include children with autism, Asperger’s syndrome, or similar diseases that impair the ability to detect emotion. The algorithm employed machine learning and neural network-based techniques to improve accuracy and efficiency relative to current methods.
The students used speech samples from the LDC database, Emotional Prosody Speech and Transcripts (LDC2002S28) as well the Berlin Database of Emotional Speech for training and testing their algorithm. Although the samples proved to be too small to produce an algorithm with a high degree of accuracy, the team's algorithm did demonstrate some degree of success. The students will present their results at Eurekafest at MIT in June.
LDC thanks the InvenTeam’s teacher, Mark Hannum, and group leader, Suhas Gondi, for contributing to this article.