Robust features for automatic estimation of physical parameters from speech

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.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.identifier.citationIEEE Region 10 Annual International Conference, Proceedings/TENCON, 2017, Vol.2017-December, , pp.1515-1519en_US
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/6990
dc.titleRobust features for automatic estimation of physical parameters from speechen_US
dc.typeBook chapteren_US

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