Estimating multiple physical parameters from speech data

Simple item page
dc.contributor.authorKalluri, S.B.
dc.contributor.authorVijayakumar, A.
dc.contributor.authorVijayasenan, D.
dc.contributor.authorSingh, R.
dc.date.accessioned2026-02-06T06:39:01Z
dc.date.issued2016
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.
dc.identifier.citationIEEE International Workshop on Machine Learning for Signal Processing, MLSP, 2016, Vol.2016-November, , p. -
dc.identifier.issn21610363
dc.identifier.urihttps://doi.org/10.1109/MLSP.2016.7738873
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/32023
dc.publisherIEEE Computer Society help@computer.org
dc.subjectHeight
dc.subjectPhysical parameters
dc.subjectShoulder size
dc.subjectSpeech forensics
dc.subjectWaist size
dc.subjectWeight
dc.titleEstimating multiple physical parameters from speech data

Files

Collections

Conference Papers