Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorKalluri, S.B.
dc.contributor.authorVijayakumar, A.
dc.contributor.authorVijayasenan, D.
dc.contributor.authorSingh, R.
dc.identifier.citationIEEE International Workshop on Machine Learning for Signal Processing, MLSP, 2016, Vol.2016-November, , pp.-en_US
dc.description.abstractIn this work, we explore prediction of different physical parameters from speech data. We aim to predict shoulder size and waist size of people from speech data in addition to the conventional height and weight parameters. A data-set with this information is created from 207 volunteers. A bag of words representation based on log magnitude spectrum is used as features. A support vector regression predicts the physical parameters from the bag of the words representation. The system is able to achieve a root mean square error of 6.6 cm for height estimation, 2.6cm for shoulder size, 7.1cm for waist size and 8.9 kg for weight estimation. The results of height estimation is on par with state of the art results. � 2016 IEEE.en_US
dc.titleEstimating multiple physical parameters from speech dataen_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.