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MAXIMUM A-POSTERIORI ESTIMATION OF MISSING SAMPLES WITH CONTINUITY CONSTRAINT IN ELECTROMAGNETIC ARTICULOGRAPHY DATA

Sujith, P and Ghosh, Prasanta Kumar (2014) MAXIMUM A-POSTERIORI ESTIMATION OF MISSING SAMPLES WITH CONTINUITY CONSTRAINT IN ELECTROMAGNETIC ARTICULOGRAPHY DATA. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), MAY 04-09, 2014, Florence, ITALY.

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Official URL: http://dx.doi.org/ 10.1109/ICASSP.2014.6853735

Abstract

Electromagnetic Articulography (EMA) technique is used to record the kinematics of different articulators while one speaks. EMA data often contains missing segments due to sensor failure. In this work, we propose a maximum a-posteriori (MAP) estimation with continuity constraint to recover the missing samples in the articulatory trajectories recorded using EMA. In this approach, we combine the benefits of statistical MAP estimation as well as the temporal continuity of the articulatory trajectories. Experiments on articulatory corpus using different missing segment durations show that the proposed continuity constraint results in a 30% reduction in average root mean squared error in estimation over statistical estimation of missing segments without any continuity constraint.

Item Type: Conference Proceedings
Additional Information: Copyright for this article belongs to the IEEE USA
Keywords: EMA data; Missing sample estimation; Gaussian mixture model; Continuity constraint
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Division of Electrical Sciences > Electrical Engineering
Depositing User: Id for Latest eprints
Date Deposited: 12 Jan 2015 07:02
Last Modified: 12 Jan 2015 07:02
URI: http://eprints.iisc.ac.in/id/eprint/50611

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