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Bounded conditional mean imputation

Introduction

The source code and examples are related to our work on bounded conditional mean imputation (BCMI). We have studied truncated posterior mean imputation1 (TPMI) and truncated conditional mean imputation2 (TCMI). TPMI and TCMI substitute unreliable feature components with GMM-MMSE estimates. For reference, we include cluster-based imputation3 that substitutes unreliable feature components with GMM-MAP estimates.

Reference: U. Remes, A. Ramírez López, K. Palomäki, and M. Kurimo, Bounded conditional mean imputation with observation uncertainties and acoustic model adaptation, IEEE/ACM TASLP, 23(7), pp. 1198-1208, 2015.

For more information, contact: Ulpu Remes, Ana Ramírez López, Kalle Palomäki, Mikko Kurimo

Matlab functions

DOWNLOAD (2.2 MB) includes reconstruction and mask estimation functions with a demo.

Main functions:

tpmi.m
Bounded conditional mean imputation with TPMI1

tcmi.m
Bounded conditional mean imputation with TCMI2

mapi.m
GMM-MAP based reconstruction/cluster-based imputation3 implementation uses the quadratic programming toolbox

Notes

Links


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References +


Last modified Ulpu Remes