MIT EECS Undergraduate Research and Innovation Scholar
Using Speech-Related Measurements for Acoustic Cues to Simultaneous Detection and Classification of Glides in English
Electrical Engineering and Computer Science
- Machine Learning
Speech production analysis for children with speech language impairments
My project will focus on using the acoustic cue system developed in the Speech Communication Group to analyze the speech of children. To gain a better understanding of the mechanisms underlying language delay and disorder in children important acoustic landmarks in child speech recordings elicited through non-word repetition tasks have been hand-labeled. Non-word repetition tasks have been shown to distinguish children with speech language impairments in the past. My project will build on previous work by labeling these speech samples for other landmark-related cues specifically those of place and voicing and adding to the existing speech processing package to enable the automatic detection of landmark cues in the speech of both typically developing and atypically developing children.
As a student studying Computer Science and Brain and Cognitive Sciences I am interested in how research in computer science can illuminate the workings of the brain. Through this project I hope to learn about the landscape of speech processing technology. I am excited to do work that will shed light on a still-elusive aspect of human function and help children challenged by speech disorders!