We introduce a new recursion that reduces the complexity of training
a semi-Markov model with continuous output distributions. We show
that the cost of training is proportional to M2 + D, compared to
M2 D with the standard recursion, where M is the observation vector
length and D is the maximum allowed duration.
%0 Journal Article
%1 Mitchell1995
%A MITCHELL, C.
%A HARPER, M.
%A JAMIESON, L.
%D 1995
%J IEEE Transactions on Speech and Audio Processing
%K continuous distributions duration, markov models, output
%N 3
%P 213-217
%T On the complexity of explicit duration $HMMs$
%V 3
%X We introduce a new recursion that reduces the complexity of training
a semi-Markov model with continuous output distributions. We show
that the cost of training is proportional to M2 + D, compared to
M2 D with the standard recursion, where M is the observation vector
length and D is the maximum allowed duration.
@article{Mitchell1995,
abstract = {We introduce a new recursion that reduces the complexity of training
a semi-Markov model with continuous output distributions. We show
that the cost of training is proportional to M2 + D, compared to
M2 D with the standard recursion, where M is the observation vector
length and D is the maximum allowed duration.},
added-at = {2011-08-05T23:55:06.000+0200},
author = {MITCHELL, C. and HARPER, M. and JAMIESON, L.},
biburl = {https://www.bibsonomy.org/bibtex/2b28e999765e507d729d9b7aa1b46d6b8/lgmarujo},
interhash = {96c3870850baaa1dfdb36d7ad662f777},
intrahash = {b28e999765e507d729d9b7aa1b46d6b8},
journal = {IEEE Transactions on Speech and Audio Processing},
keywords = {continuous distributions duration, markov models, output},
number = 3,
pages = {213-217},
timestamp = {2011-08-05T23:55:06.000+0200},
title = {On the complexity of explicit duration $HMMs$},
volume = 3,
year = 1995
}