K-L Divergence based Confusion Network Generation Algorithm Guided with Maximum Posteriori Arc

Mangu L, Brill E, and Stolcke A. Finding consensus in speechrecognition: Word error minimization and other applicationsof confusion networks[J].Computer Speech and Language.2000,14(4):373-400[2]Tur G, Wright J, and Gorin A, et al.. Improving spokenlanguage understanding using word confusion networks.Proceedings of ICSLP, Denver, Colorado, 2002: 1137-1140.[3]Bertoldi N and Federico M. A new decoder for spokenlanguage translation based on confusion networks. IEEEASRU Workshop, Cancun, Mexico, 2005: 134-140.[4]Xue J and Zhao Y X. Random forests-based confidenceannotation using novel feature from confusion network.Proceedings of ICASSP, Toulouse, France, 2006: 1149-1152.Hillard D and Ostendorf M. Compensation forward posteriorestimation bias in confusion networks. Proceedings ofICASSP, Toulouse, France, 2006: 1153-1156.[5]Hakkani-Tur D and Riccardi G. A general algorithm for wordgraph matrix decomposition. Proceedings of ICASSP, HongKong, China, 2003: 596-599.[6]Xue J and Zhao Y X. Improving confusion network algorithmand shortest path search from word lattice. Proceedings ofICASSP, Philadelphia, PA, 2005: 853-856.[7]Kullback S and Leibler R A. On information and sufficiency[J].Ann. Math. Stat.1951, 22(1):79-86[8]Liu P, Soong F K, and Zhou J L. Effective estimation ofKullback-Leibler divergence between speech models. Tech.Rep., Microsoft Research Asia, 2005.[9]Chang E, Shi Y, and Zhou J L, et al.. Speech lab in a box: aMandarin speech toolbox to Jumpstart speech relatedresearch. Proceedings of Eurospeech, Aalborg, Denmark,2001: 2799-2802.