Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/6990
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBabu, K.S.
dc.contributor.authorVijayasenan, D.
dc.date.accessioned2020-03-30T09:46:34Z-
dc.date.available2020-03-30T09:46:34Z-
dc.date.issued2017
dc.identifier.citationIEEE Region 10 Annual International Conference, Proceedings/TENCON, 2017, Vol.2017-December, , pp.1515-1519en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/6990-
dc.description.abstractEstimating 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.en_US
dc.titleRobust features for automatic estimation of physical parameters from speechen_US
dc.typeBook chapteren_US
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.