Time-series classification has gained wide attention within the Machine Learning community, due to its large range of applicability varying from medical diagnosis, financial markets, up to shape and trajectory classification. The current state-of-art methods applied in timeseries classification rely on detecting similar instances through neighboring algorithms. Dynamic Time Warping (DTW) is a s...

Poor handwriting is a diagnostic criterion for developmental coordination disorder. Typical of poor handwriting is its low overall quality and the high variability of the spatial characteristics of the letters, usually assessed with a subjective handwriting scale. Recently, Dynamic Time Warping (DTW), a technique originally developed for speech recognition, was introduced for pattern recognitio...

Spoken term detection is important for retrieval of multimedia and spoken content over the Internet. Because it is difficult to have acoustic/language models well matched to the huge quantities of spoken documents produced under various conditions, unsupervised approaches using frame-based dynamic time warping (DTW) has been proposed to compare the spoken query with spoken documents frame by fr...

0957-4174/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2012.05.012 ⇑ Corresponding author. Tel.: +36 88 624209. E-mail address: [email protected] (J. Ab In recent years, dynamic time warping (DTW) has begun to become the most widely used technique for comparison of time series data where extensive a priori knowledge is not available. However, it is often expe...

Deterministic tourist walk (DTW) has attracted increasing interest in computer vision. In the last years, different methods for analysis of dynamic and static textures were proposed. So far, all works based on the DTW for texture analysis use all image pixels as initial point of a walk. However, this requires much runtime. In this paper, we conducted a study to verify the performance of the DTW...

Arabic printed cursive characters Recognition using the Dynamic Time Warping (DTW) algorithm provides very interesting results. Unfortunately, the big amount of computing to be achieved by this algorithm during the recognition process makes its execution time very slow. Grid computing presents a very interesting infrastructure that allow to support distributed applications in one hand and to ta...

In speech recognition, the training process plays an important role. When a good training model for a speech pattern is obtained, this not only enhances the speed of recognition tremendously .but also improves the quality of the overall performance in recognizing the speech utterance. In general, there are two classic approaches for this development, namely Dynamic Time Warping (DTW) and Hidden...

Dynamic Time Warping (DTW) can be used to minimize distance between two sequences which display the same trends but are not perfectly aligned with each other. This feature makes DTW an effective pattern classification method for sequence matching. In Ref. [1], a fault diagnosis method using pattern classification based on adaptive rank-order morphological transform has been proposed. It uses Eu...

Emotion recognition helps to recognize the internal expressions of the individuals from the speech database. In this paper, Dynamic time warping (DTW) technique is utilized to recognize speaker independent Emotion recognition based on 39 MFCC features. A large audio of around 960 samples of isolated words of five different emotions are collected and recorded at 20 to 300 KHz sampling frequency....