Stressed Speech Recognition Method Based on Difference Subspace Combined with Dynamic Time Warping

2012 ◽  
Vol 241-244 ◽  
pp. 1640-1646
Author(s):  
Cheng Guo Lv ◽  
Ru Bo Zhang ◽  
Pei Hua Li
Keyword(s):  
Dynamic Time Warping ◽  
Recognition Rate ◽  
Decision Criterion ◽  
Time Warping ◽  
Training Set ◽  
Recognition Method ◽  
Average Recognition Rate ◽  
Normal Environment ◽  
Acceleration Of Gravity ◽  
Dynamic Time

Speech under G-force which produced when speaker was under different acceleration of gravity was analyzed and researched, considered as principal part and stressed part to research. An isolated word recognition approach was proposed which combined difference subspace means with dynamic time warping technique. The method recognized speech under G-force by constructing a difference subspace to remove the stressed part. Dynamic time warping technique was adopted to make all feature vectors of one word in the training set have equal length, and a corresponding decision criterion was suggested. For a small vocabulary including 15 words, the method obtained the average recognition rate of 98.3%, which almost equal to the rate in normal environment. The method not only worked well in normal conditions but also had good performance for speech under G-force.

RELATIVE POSITIONING OF STROKE-BASED CLUSTERING: A NEW APPROACH TO ONLINE HANDWRITTEN DEVANAGARI CHARACTER RECOGNITION

2012 ◽  
Vol 12 (02) ◽  
pp. 1250016 ◽  
Author(s):  
K. C. SANTOSH ◽  
CHOLWICH NATTEE ◽  
BART LAMIROY
Keyword(s):  
Character Recognition ◽  
Dynamic Time Warping ◽  
Large Range ◽  
Recognition Rate ◽  
Relative Positioning ◽  
Writing Style ◽  
Time Warping ◽  
New Approach ◽  
Tip Position ◽  
Dynamic Time

In this paper, we propose a new scheme for Devanagari natural handwritten character recognition. It is primarily based on spatial similarity-based stroke clustering. A feature of a stroke consists of a string of pen-tip positions and directions at every pen-tip position along the trajectory. It uses the dynamic time warping algorithm to align handwritten strokes with stored stroke templates and determine their similarity. Experiments are carried out with the help of 25 native writers and a recognition rate of approximately 95% is achieved. Our recognizer is robust to a large range of writing style and handles variation in the number of strokes, their order, shapes and sizes and similarities among classes.

Follow That Tune-Adaptive Approach to DTW-based Query-by-Humming System

2015 ◽  
Vol 39 (4) ◽  
pp. 467-476 ◽  
Author(s):  
Bartłomiej Stasiak
Keyword(s):  
Dynamic Time Warping ◽  
Experimental Validation ◽  
Recognition Rate ◽  
Multimedia Databases ◽  
Time Warping ◽  
Query By Humming ◽  
Human Ability ◽  
Alignment Problem ◽  
Computationally Expensive ◽  
Dynamic Time

Abstract Dynamic Time Warping is a standard algorithm used for matching time series irrespective of local tempo variations. Its application in the context of Query-by-Humming interface to multimedia databases requires providing the transposition independence, which involves some additional, sometimes computationally expensive processing and may not guarantee the success, e.g., in the presence of a pitch trend or accidental key changes. The method of tune following, proposed in this paper, enables solving the pitch alignment problem in an adaptive way inspired by the human ability of ignoring typical errors occurring in sung melodies. The experimental validation performed on the database containing 4431 queries and over 5000 templates confirmed the enhancement introduced by the proposed algorithm in terms of the global recognition rate.

scholarly journals DTW–RADON-BASED SHAPE DESCRIPTOR FOR PATTERN RECOGNITION

2013 ◽  
Vol 27 (03) ◽  
pp. 1350008 ◽  
Author(s):  
K. C. SANTOSH ◽  
BART LAMIROY ◽  
LAURENT WENDLING
Keyword(s):  
Pattern Recognition ◽  
Dynamic Time Warping ◽  
Recognition Performance ◽  
Shape Descriptor ◽  
Shape Descriptors ◽  
Time Warping ◽  
Recognition Method ◽  
Dynamic Time ◽  
Public Datasets ◽  
Comprehensive Study

In this paper, we present a pattern recognition method that uses dynamic programming for the alignment of Radon features. The key characteristic of the method is to use dynamic time warping (DTW) to match corresponding pairs of the Radon features for all possible projections. Thanks to DTW, we avoid compressing the feature matrix into a single vector which would otherwise miss information. To reduce the possible number of matchings, we rely on a initial normalization based on the pattern orientation. A comprehensive study is made using major state-of-the-art shape descriptors over several public datasets of shapes such as graphical symbols (both printed and hand-drawn), handwritten characters and footwear prints. In all tests, the method proves its generic behavior by providing better recognition performance. Overall, we validate that our method is robust to deformed shape due to distortion, degradation and occlusion.

Speech Recognition for Endoscopic Automatic Positioning System

2012 ◽  
Vol 588-589 ◽  
pp. 1296-1299
Author(s):  
Ning Ma ◽  
Xiao Dong Chen ◽  
Ya Nan Li ◽  
Qing Yun Yin ◽  
Yi Wang ◽  
...  
Keyword(s):  
Speech Recognition ◽  
Embedded System ◽  
Dynamic Time Warping ◽  
Recognition Rate ◽  
Positioning System ◽  
Time Warping ◽  
Embedded Platform ◽  
Speech Recognition Engine ◽  
Dynamic Time ◽  
Automatic Positioning

A novel system for minimally invasive surgery is presented in this paper. The system utilized an Endoscopic Automatic Positioner (EAP) controlled by Speech Recognition Engine to implement the clamping and dynamically positioning of the laparoscope. The motion instructions of the EAP are transformed from voice commands of specific doctor recognized by an improved algorithm named Normalized Average- Dynamic Time Warping (NA-DTW). An embedded platform based on ARM is designed to run the NA-DTW on Windows CE operating system. 1250 groups of experiments from 10 individual speakers demonstrate the performance of DTW. Compared with traditional algorithms, the enhanced algorithm improves the recognition rate from 96.6% to 99.76% and shortens the time of calculation by 51%. The results demonstrate the enhanced algorithm being effective and can satisfy the real time requirement in embedded system.

Chinese Connected Word Speech Recognition Based on Derivative Dynamic Time Warping

2012 ◽  
Vol 542-543 ◽  
pp. 1324-1329
Author(s):  
Zhi Guo He ◽  
Ze Min Liu
Keyword(s):  
Speech Recognition ◽  
Computational Complexity ◽  
Dynamic Time Warping ◽  
Recognition Rate ◽  
Experimental Results ◽  
Time Warping ◽  
Test String ◽  
Cumulative Distance ◽  
Isolated Word ◽  
Dynamic Time

The algorithm of derivative dynamic time warping (DDTW) can overcome the shortcoming of dynamic time warping (DTW) and the computational complexity has not increased. In this paper, the algorithm of DDTW was applied to Chinese connected word speech recognition. For each isolated word, as an independent reference template and as basic recognition unit, there was an independent reference template to correspond; the matching between some word of the test string and a reference template was done by the DDTW, and the reference string which had the minimum cumulative distance was as output. The experimental results show that our method is obviously superior to all the methods based on DTW, and the recognition rate has reached 90%.

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