Corrections to "Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: Initial results for vocal fold nodules

Citation:

M. Ghassemi, et al., “Corrections to "Learning to detect vocal hyperfunction from ambulatory neck-surface acceleration features: Initial results for vocal fold nodules,” IEEE Transactions on Biomedical Engineering, vol. 62, no. 10, pp. 2544-2544, 2015.
Paper77 KB

Abstract:

In, the third sentence of the second paragraph in Section III-D should have read as follows: “We first divided data using leave-one-out cross validation (LOOCV) to generate 12 subject subsets, where each subject subset consisted of randomly selected data across the 12 pairs. For each test subset, all windows from the 11 other subsets were then subdivided using fivefold cross validation (1/5th validation and 4/5th training in each fold).”

Publisher's Version

Original paper: http://scholar.harvard.edu/dmehta/publications/learning-detect-vocal-hyperfunction-ambulatory-neck-surface-acceleration
Last updated on 10/20/2016