Sketch-Based User Authentication With a Novel String Edit Distance Model

2018 ◽  
Vol 48 (3) ◽  
pp. 460-472
Author(s):  
Kaspar Riesen ◽  
Thomas Hanne ◽  
Roman Schmidt
Keyword(s):  
Edit Distance ◽  
User Authentication ◽  
String Edit Distance ◽  
Distance Model

Invariance of edit-distance to tempo in rhythm similarity

2020 ◽  
pp. 030573562097103
Author(s):  
Matthew Moritz ◽  
Matthew Heard ◽  
Hyun-Woong Kim ◽  
Yune S Lee
Keyword(s):  
Edit Distance ◽  
Ecological Validity ◽  
Perceptual Similarity ◽  
Music Psychology ◽  
Mantel Tests ◽  
Distance Model ◽  
Minimum Number ◽  
History Of ◽  
Similarity Ratings ◽  
Similarity Judgments

Despite the long history of music psychology, rhythm similarity perception remains largely unexplored. Several studies suggest that edit-distance—the minimum number of notational changes required to transform one rhythm into another—predicts similarity judgments. However, the ecological validity of edit-distance remains elusive. We investigated whether the edit-distance model can predict perceptual similarity between rhythms that also differed in a fundamental characteristic of music—tempo. Eighteen participants rated the similarity between a series of rhythms presented in a pairwise fashion. The edit-distance of these rhythms varied from 1 to 4, and tempo was set at either 90 or 150 beats per minute (BPM). A test of congruence among distance matrices (CADM) indicated significant inter-participant reliability of ratings, and non-metric multidimensional scaling (nMDS) visualized that the ratings were clustered based upon both tempo and whether rhythms shared an identical onset pattern, a novel effect we termed rhythm primacy. Finally, Mantel tests revealed significant correlations of edit-distance with similarity ratings on both within- and between-tempo rhythms. Our findings corroborated that the edit-distance predicts rhythm similarity and demonstrated that the edit-distance accounts for similarity of rhythms that are markedly different in tempo. This suggests that rhythmic gestalt is invariant to differences in tempo.

An Edit-Distance Model for the Approximate Matching of Timed Strings

2009 ◽  
Vol 31 (4) ◽  
pp. 736-741 ◽  
Author(s):  
S. Dobrisek ◽  
J. Zibert ◽  
N. Pavesic ◽  
F. Mihelic
Keyword(s):  
Edit Distance ◽  
Approximate Matching ◽  
Distance Model

scholarly journals Learning string-edit distance

1998 ◽  
Vol 20 (5) ◽  
pp. 522-532 ◽  
Author(s):  
E.S. Ristad ◽  
P.N. Yianilos
Keyword(s):  
Edit Distance ◽  
String Edit Distance

GEOMETRIC APPROACH TO DATA MINING

2001 ◽  
Vol 01 (02) ◽  
pp. 363-386
Author(s):  
WLADIMIR RODRIGUEZ ◽  
MARK LAST ◽  
ABRAHAM KANDEL ◽  
HORST BUNKE
Keyword(s):  
Data Mining ◽  
Edit Distance ◽  
Geometric Approach ◽  
Symbolic Representation ◽  
Pattern Identification ◽  
Curve Matching ◽  
Distance Computation ◽  
String Edit Distance

In this paper, a new, geometric approach to pattern identification in data mining is presented. It is based on applying string edit distance computation to measuring the similarity between multi-dimensional curves. The string edit distance computation is extended to allow the possibility of using strings, where each element is a vector rather than just a symbol. We discuss an approach for representing 3D-curves using the curvature and the tension as their symbolic representation. This transformation preserves all the information contained in the original 3D-curve. We validate this approach through experiments using synthetic and digitalized data. In particular, the proposed approach is suitable to measure the similarity of 3D-curves invariant under translation, rotation, and scaling. It also can be applied for partial curve matching.

Phonetic distance and dialect clustering on the Qinghai-Tibet plateau

2017 ◽  
Vol 40 (2) ◽  
pp. 161-178
Author(s):  
Abe Powell ◽  
Hiroyuki Suzuki
Keyword(s):  
Edit Distance ◽  
Distance Matrix ◽  
Tibet Plateau ◽  
The Tibetan Plateau ◽  
Linguistic Features ◽  
Equal Degree ◽  
String Edit Distance ◽  
Eastern Border ◽  
Phonetic Distance ◽  
Qinghai Tibet Plateau

Abstract The goal of this paper is to use string edit distance to describe the synchronic relationship between the Tibetan speech varieties located on the Northeastern edge of the Tibetan Plateau. String edit distance provides a statistical way to compare a large number of linguistic features, in essence producing a statistical bundle of isoglosses. In this way, it can be used as a tool in dialect mapping and synchronic clustering. In this paper, the aggregate distance matrix produced by string edit distance reveals that the great degree of phonetic continuity on the grasslands of the northeastern edge of the plateau is matched by an equal degree of phonetic discontinuity in the mountains forming the eastern border of the plateau. While the dialects located on the grasslands can be grouped together into one cluster, the dialects in the mountains can be grouped together into six clusters.

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