Journal ArticleDOI
Quality Estimation Methodology of Speech Recognition Features
R. Lileikyte,Laimutis Telksnys +1 more
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TLDR
The methodology for quality estimation of speech features is presented and the most proper metric was chosen in combination with Dynamic Time Warping (DTW) classifier.Abstract:
The best feature set selection is the key of successful speech recognition system. Quality measure is needed to characterize the chosen feature set. Variety of feature quality metrics are proposed by other authors. However, no guidance is given to choose the appropriate metric. Also no metrics investigations for speech features were made. In the paper the methodology for quality estimation of speech features is presented. Metrics have to be chosen on the ground of their correlation with classification results. Linear Frequency Cepstrum (LFCC), Mel Frequency Cepstrum (MFCC), Perceptual Linear Prediction (PLP) analyses were selected for experiment. The most proper metric was chosen in combination with Dynamic Time Warping (DTW) classifier. Experimental investigation results are presented. Ill. 5, bibl. 18, tabl. 3 (in English; abstracts in English and Lithuanian). http://dx.doi.org/10.5755/j01.eee.110.4.302read more
Citations
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IEEE transactions on pattern analysis and machine intelligence
TL;DR: This special issue aims at gathering the recent advances in learning with shared information methods and their applications in computer vision and multimedia analysis and addressing interesting real-world computer Vision and multimedia applications.
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Evaluation of Features Extraction Algorithms for a Real-Time Isolated Word Recognition System
TL;DR: The robustness of features extraction algorithms was tested recognizing the speech records at different signal to noise rates and the proposed word recognition system satisfy the real-time requirements and is suitable for applications in embedded systems.
Journal ArticleDOI
Quality Measurement of Speech Recognition Features in Context of Nearest Neighbour Classifier
R. Lileikyte,Laimutis Telksnys +1 more
TL;DR: Within the proposed method PLP was established to have the higher quality comparing to LFCC, and the adequateness of the method was validated by Nearest neighbour classification error.
Journal ArticleDOI
Quality Estimation of Speech Recognition Features for Dynamic Time Warping Classifier
Rasa Lileikytė,Laimutis Telksnys +1 more
TL;DR: In this article, the authors proposed a methodology for speech feature quality establishment without running the classification process, which is based on metrics that do not need parameters setting, thus the results can be uniformly interpreted across the different problems.
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Dynamic Outlier Detection in the Calibration by Comparison Method Applied to Strain Gauge Weight Sensors.
TL;DR: The Dynamic Time Warping method appears to be more efficient while comparing the shapes of calibration characteristics done with the use of the Pearson’s method, which makes the method a good tool for eliminating improper data series which might appear in the calibration process due to, e.g., malfunctioning devices installed in the calibrating stand.
References
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IEEE transactions on pattern analysis and machine intelligence
TL;DR: This special issue aims at gathering the recent advances in learning with shared information methods and their applications in computer vision and multimedia analysis and addressing interesting real-world computer Vision and multimedia applications.
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Complexity measures of supervised classification problems
Tin Kam Ho,Mitra Basu +1 more
TL;DR: A set of real-world problems to random labelings of points is compared and it is found that real problems contain structures in this measurement space that are significantly different from the random sets.
Journal ArticleDOI
Performance tradeoffs in dynamic time warping algorithms for isolated word recognition
TL;DR: The results suggest a new approach to dynamic time warping for isolated words in which both the reference and test patterns are linearly warped to a fixed length, and then a simplified dynamic time Warping algorithm is used to handle the nonlinear component of the time alignment.
Journal ArticleDOI
Meta analysis of classification algorithms for pattern recognition
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Journal ArticleDOI
Domain of competence of XCS classifier system in complexity measurement space
TL;DR: This paper investigates the domain of competence of XCS by means of a methodology that characterizes the complexity of a classification problem by a set of geometrical descriptors, and focuses on XCS with hyperrectangle codification, which has been predominantly used for real-attributed domains.