Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Modified condensed nearest neighbor rule as applied to speaker independent word recognition
Date
1988-12
Author
Mansur, A.
Yarman Vural, Fatoş Tunay
Yalabık, Neşe
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
166
views
0
downloads
Cite This
Edited and Condensed Nearest Neighbor Rules are used in various applications in Pattern Recognition problems. In this study, modified versions of these algorithms are applied to speaker-independent isolated word recognition to select the word templates, as opposed to the clustering techniques. It is shown that the approach improves the recognition rate when compared with clustering, with the disadvantage of being more costly.
Subject Keywords
Software
,
Communication
,
Linguistics and language
,
Modelling and simulation
,
Computer vision and pattern recognition
,
Language and linguistics
,
Computer science applications
URI
https://hdl.handle.net/11511/51781
Journal
Speech Communication
DOI
https://doi.org/10.1016/0167-6393(88)90058-1
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
The use of articulator motion information in automatic speech segmentation
Akdemir, Eren; Çiloğlu, Tolga (Elsevier BV, 2008-07-01)
The use of articulator motion information in automatic speech segmentation is investigated. Automatic speech segmentation is an essential task in speech processing applications like speech synthesis where accuracy and consistency of segmentation are firmly connected to the quality of synthetic speech. The motions of upper and lower lips are incorporated into a hidden Markov model based segmentation process. The MOCHA-TIMIT database, which involves simultaneous articulatograph and microphone recordings, was ...
The syntax of relative clauses in Croatian
Gracanın Yüksek, Martına (Walter de Gruyter GmbH, 2013-01-01)
In this paper, I propose that Croatian relative clauses (RCs) introduced by the complementizer to 'what/that' do not form a homogeneous class with respect to their derivation: some are derived by movement, and some are derived by a non-movement strategy. Unless the relativized element is the subject, sto-RCs normally require a resumptive pronoun to appear in the site of relativization. However, this requirement is removed under morphological case matching between the head of the RC and the resumptive pronou...
Continuous dimensionality characterization of image structures
Felsberg, Michael; Kalkan, Sinan; Kruger, Norbert (Elsevier BV, 2009-05-04)
Intrinsic dimensionality is a concept introduced by statistics and later used in image processing to measure the dimensionality of a data set. In this paper, we introduce a continuous representation of the intrinsic dimension of an image patch in terms of its local spectrum or, equivalently, its gradient field. By making use of a cone structure and barycentric co-ordinates, we can associate three confidences to the three different ideal cases of intrinsic dimensions corresponding to homogeneous image patche...
Disparity disambiguation by fusion of signal- and symbolic-level information
Ralli, Jarno; Diaz, Javier; Kalkan, Sinan; Krueger, Norbert; Ros, Eduardo (Springer Science and Business Media LLC, 2012-01-01)
We describe a method for resolving ambiguities in low-level disparity calculations in a stereo-vision scheme by using a recurrent mechanism that we call signal-symbol loop. Due to the local nature of low-level processing it is not always possible to estimate the correct disparity values produced at this level. Symbolic abstraction of the signal produces robust, high confidence, multimodal image features which can be used to interpret the scene more accurately and therefore disambiguate low-level interpretat...
Improving the k-nearest neighbour rule: using geometrical neighbourhoods and manifold-based metrics
ALTINCAY, HAKAN (Wiley, 2011-09-01)
Sample weighting and variations in neighbourhood or data-dependent distance metric definitions are three principal directions considered for improving the k-NN classification technique. Recently, manifold-based distance metrics attracted considerable interest and computationally less demanding approximations have been developed. However, a careful comparison of these alternative approaches is missing. In this study, an extensive comparison is firstly performed for three alternative neighbourhood definitions...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
A. Mansur, F. T. Yarman Vural, and N. Yalabık, “Modified condensed nearest neighbor rule as applied to speaker independent word recognition,”
Speech Communication
, pp. 411–415, 1988, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51781.