Inferring Subjective Ratings for In-car Speech Using Objective Measures

This project explores how computer algorithms will be used to predict the intelligibility and quality of in-car speech processed by hearing aids. Hearing impaired listeners graded in-car speech for a set of conditions. The conditions include seating position of talker, seating position of speaker, levels of background noise, and hearing aid processing methods. Each hearing impaired participant graded processed speech using multiple criteria. For each assessment criteria, a function is generated that maps the assessed criteria to the result of each computer algorithm. These functions are then used to predict human gradings for new speech signals.

Melih Yayli
Faculty Supervisor: 
Ian C Bruce
Partner University: