Robust features for automatic estimation of physical parameters from speech
No Thumbnail Available
Date
2017
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
Estimating speaker's physical parameters like height, weight and shoulder size can assist in voice forensics by providing additional knowledge about the speaker. In this work, statistics of the components of background GMM are employed as features in estimating the physical parameters. These features improved the performance of height and shoulder size estimation as compared to our earlier attempt based on a Bag of Word representation. The robustness of the features is validated using two different training subsets containing different languages. © 2017 IEEE.
Description
Keywords
first order statistics, GMM-UBM, height, MFCC, Physical parameters, shoulder size, Speech forensics, SVR, weight
Citation
IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2017, Vol.2017-December, , p. 1515-1519
