Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10368526 | Computer Speech & Language | 2014 | 16 Pages |
Abstract
⺠We develop an automatic running speech intelligibility assessment method. ⺠We derive new text-independent speaker features from a phonological representation. ⺠We validate the method on a new corpus of patients treated for head and neck cancer. ⺠We show that it is as reliable as a human listener and able to track a speaker's progress.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Catherine Middag, Renee Clapham, Rob van Son, Jean-Pierre Martens,