@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} }