Please use this identifier to cite or link to this item: https://idr.l2.nitk.ac.in/jspui/handle/123456789/6990
Title: Robust features for automatic estimation of physical parameters from speech
Authors: Babu, K.S.
Vijayasenan, D.
Issue Date: 2017
Citation: IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2017, Vol.2017-December, , pp.1515-1519
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.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/6990
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.