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dtw.bib
@article{tormene_matching_2009,
title = {Matching incomplete time series with dynamic time
warping: An algorithm and an application to
post-stroke rehabilitation},
volume = 45,
url = {http://www.ncbi.nlm.nih.gov/pubmed/19111449},
journal = {Artificial Intelligence in Medicine},
author = {Tormene, P. and Giorgino, Toni and Quaglini, S. and
Stefanelli, M.},
year = 2009,
keywords = {Clinical Data Mining}
}
@article{giorgino_computing_2009,
title = {Computing and Visualizing Dynamic Time Warping
Alignments in R: The dtw Package},
volume = 31,
url = {http://www.jstatsoft.org/v31/i07},
number = 7,
journal = {Journal of Statistical Software},
author = {Giorgino, Toni},
year = 2009,
pages = {1-24}
}
@inproceedings{mori_early_2006,
title = {Early Recognition and Prediction of Gestures},
volume = 3,
doi = {http://dx.doi.org/10.1109/ICPR.2006.467},
booktitle = {Proc. 18th International Conference on Pattern
Recognition {ICPR} 2006},
publisher = {{IEEE} Computer Society},
author = {Mori, A. and Uchida, S. and Kurazume, R. and
Taniguchi, R. and Hasegawa, T. and Sakoe, H. and
Werner, Bob},
year = 2006,
keywords = {gesture prediction, gesture recognition, humanoid
control, image motion analysis, motion prediction},
pages = {560--563},
},
@article{sakoe_two-level_1979,
title = {Two-level {DP-matching} -- A dynamic
programming-based pattern matching algorithm for
connected word recognition},
volume = 27,
number = 6,
journal = {Acoustics, Speech, and Signal Processing [see also
{IEEE} Transactions on Signal Processing], {IEEE}
Transactions on},
author = {Sakoe, H.},
year = 1979,
pages = {588--595},
},
@article{sakoe_dynamic_1978,
title = {Dynamic programming algorithm optimization for
spoken word recognition},
volume = 26,
abstract = {This paper reports on an optimum dynamic progxamming
({DP)} based time- normalization algorithm for
spoken word recognition. First, a general principle
of time-normalization is given using time- warping
function. Then, two time-normalized distance
definitions, called symmetric and asymmetric forms,
are derived from the principle. These two forms are
compared with each other through theoretical
discussions and experimental studies. The symmetric
form algorithm superiority is established. A new
technique, called slope constraint, is successfully
introduced, in which the warping function slope is
restricted so as to improve discrimination between
words in different categories. The effective slope
constraint characteristic is qualitatively analyzed,
and the optimum slope constraint condition is
determined through experiments. The optimized
algorithm is then extensively subjected to
experimental comparison with various
{DP-algorithms}, previously applied to spoken word
recognition by different research groups. The
experiment shows that the present algorithm gives no
more than about two-thirds errors, even compared to
the best conventional algorithm.},
number = 1,
journal = {Acoustics, Speech, and Signal Processing [see also
{IEEE} Transactions on Signal Processing], {IEEE}
Transactions on},
author = {Sakoe, H. and Chiba, S.},
month = feb,
year = 1978,
pages = {43--49},
},
@inproceedings{sakoe_dynamic_1971,
title = {A Dynamic Programming Approach to Continuous Speech
Recognition},
volume = 3,
booktitle = {Proceedings of the Seventh International Congress on
Acoustics, Budapest},
publisher = {Akad\'emiai Kiad\'o},
author = {Sakoe, Hiroaki and Chiba, Seibi},
year = 1971,
keywords = {2000 book nlp},
pages = {65--69},
}
@article{hohne_temporal_1983,
title = {On temporal alignment of sentences of natural and
synthetic speech},
volume = 31,
issn = {0096-3518},
doi = {10.1109/TASSP.1983.1164174},
abstract = {One way to improve the quality of synthetic speech,
and to learn about temporal aspects of speech
recognition, is to study the problem of time
aligning pairs of spoken sentences. For example, one
could evaluate various sets of duration rules for
synthesis by comparing the time alignments of speech
sounds within synthetic sentences to those of
naturally spoken sentences. In this manner, an
improved set of sound duration rules could be
obtained by applying some objective measure to the
alignment scores. For speech recognition
applications, one could obtain automatic labeling of
continuous speech from a hand-marked prototype to
obtain models and/or statistical data on sounds
within sentences. A key question in the use of
automatic alignment of sentence length utterances is
whether the time warping methods, developed for
isolated word recognition, could be extended to the
problem of time aligning sentence length utterances
(up to several seconds long). A second key question
is the reliability and accuracy of such an
alignment. In this paper we investigate these
questions. It is shown that, with some simple
modifications, the dynamic time warping procedures
used for isolated word recognition apply almost as
well to alignment of sentence length utterances. It
is also shown that, on the average, the uncertainty
in the location of significant events within the
sentence is much smaller than the event durations
although the largest errors are longer than some
event durations. Hence, one must apply caution in
using the time alignment contour for synthesis or
recognition applications.},
number = 4,
journal = {{IEEE} Transactions on Acoustics, Speech and Signal
Processing},
author = {Hohne, H. and Coker, C. and Levinson, {S.E.} and
Rabiner, L.},
year = 1983,
keywords = {Acoustic testing, Automatic testing, Helium,
Labeling, Prototypes, Speech analysis, Speech
recognition, Speech synthesis, Synthesizers,
Uncertainty},
pages = {807--813},
}
@article{myers_performance_1980,
title = {Performance tradeoffs in dynamic time warping
algorithms for isolated word recognition},
volume = 28,
number = 6,
journal = {{IEEE} Transactions on Acoustics, Speech and Signal
Processing},
author = {Myers, C. and Rabiner, L. and Rosenberg, A.},
year = 1980,
pages = {623--635},
},
@article{rabiner_speaker-independent_1979,
title = {Speaker-independent recognition of isolated words
using clustering techniques},
volume = 27,
number = 4,
journal = {{IEEE} Transactions on Acoustics, Speech and Signal
Processing},
author = {Rabiner, L. and Levinson, S. and Rosenberg, A. and
Wilpon, J.},
year = 1979,
pages = {336--349},
},
@article{rabiner_considerations_1978,
title = {Considerations in dynamic time warping algorithms
for discrete word recognition},
volume = 26,
number = 6,
journal = {{IEEE} Transactions on Acoustics, Speech and Signal
Processing},
author = {Rabiner, L. and Rosenberg, A. and Levinson, S.},
year = 1978,
pages = {575--582},
}
@book{rabiner_fundamentals_1993,
title = {Fundamentals of speech recognition},
publisher = {Prentice-Hall, Inc.},
author = {Rabiner, Lawrence and Juang, Biing-Hwang},
year = 1993,
}
@article{velichko_automatic_1970,
title = {Automatic recognition of 200 words},
volume = 2,
issn = {0020-7373},
url =
{http://www.sciencedirect.com/science/article/pii/S0020737370800086},
doi = {10.1016/S0020-7373(70)80008-6},
abstract = {Experiments on the automatic recognition of 203
Russian words are described. The experimental
vocabulary includes terms of the language,
{ALGOL-60} together with others. The logarithmic
characteristics of acoustic signal in five bands are
extracted as features. The measure of similarity
between the words of standard and control sequences
is calculated by the words maximizing a definite
functional using dynamic programming. The average
reliability of recognition for one speaker obtained
for experiments using 5000 words is 0.95. The
computational time for recognition is 2-4 sec.},
number = 3,
urldate = {2013-04-07},
journal = {International Journal of Man-Machine Studies},
author = {Velichko, {V.M.} and Zagoruyko, {N.G.}},
month = jul,
year = 1970,
keywords = {2000 book nlp},
pages = {223--234}
}
@article{myers_performance_1980,
title = {Performance tradeoffs in dynamic time warping
algorithms for isolated word recognition},
volume = 28,
number = 6,
journal = {{IEEE} Transactions on Acoustics, Speech and Signal
Processing},
author = {Myers, C. and Rabiner, L. and Rosenberg, A.},
year = 1980,
pages = {623--635}
}
@phdthesis{myers_comparative_1980,
title = {A Comparative Study Of Several Dynamic Time Warping
Algorithms For Speech Recognition},
school = {{MIT}},
author = {Myers, C. S.},
year = 1980,
}
@article{waterman_dynamic_1985,
title = {A dynamic programming algorithm to find all
solutions in a neighborhood of the optimum},
volume = {77},
issn = {0025-5564},
url =
{http://www.sciencedirect.com/science/article/pii/0025556485900963},
doi = {10.1016/0025-5564(85)90096-3},
abstract = {Just after he introduced dynamic programming,
Richard Bellman with R. Kalaba in 1960 gave a method
for finding Kth best policies. Their method has been
modified since then, but it is still not practical
for many problems. This paper describes a new
technique which modifies the usual backtracking
procedure and lists all near-optimal policies. This
practical algorithm is very much in the spirit of
the original formulation of dynamic programming. An
application to matching biological sequences is
given.},
number = {1-2},
urldate = {2013-04-15},
journal = {Mathematical Biosciences},
author = {Waterman, Michael S. and Byers, Thomas H.},
month = dec,
year = {1985},
pages = {179--188}
}