In this paper we introduce a novel dynamic programming algorithm called Information Retrieval-based Dynamic Time Warping (IR-DTW) used to find non-linearly matching subsequences between two time series where matching start and end points are not known a priori. In this paper our algorithm is applied for audio matching within the query by example (QbE) spoken term detection (STD) task, although ...

In this paper we introduce a novel dynamic programming algorithm called Information Retrieval-based Dynamic Time Warping (IR-DTW) used to find non-linearly matching subsequences between two time series where matching start and end points are not known a priori. In this paper our algorithm is applied for audio matching within the query by example (QbE) spoken term detection (STD) task, although ...

Arabic cursive optical character recognition (OCR) based on the dynamic time warping (DTW) algorithm provides simultaneously very interesting segmentation and recognition rates. However, the computing complexity of the DTW algorithm restricts its widespread utilization and its consideration at a commercial scale. Accelerating the DTW execution time has attracted many researchers and several sol...

The Dynamic Time Warping (DTW) algorithm is a software technique to quantify the diversity between two time varying sequences. In spite of its computational complexity, it is often used in speech recognition systems. In this work, hardware implementation of DTW modeled in VERILOG Hardware Description Language (HDL) has been done, with an aim to use it as an independent unit or as a co-processor...

We investigate usage of dynamic time warping (DTW) algorithm for aligning raw signal data from MinION sequencer. DTW is mostly using for fast alignment for selective sequencing to quickly determine whether a read comes from sequence of interest. We show that standard usage of DTW has low discriminative power mainly due to problem with accurate estimation of scaling parameters. We propose a simp...

Dynamic time warping (DTW) is well known as an effective method for model-based symbol recognition. Unfortunately, its complexity is quadratic in the number of points present in the symbols to be matched. In this paper, we propose a greedy approximate solution to Tappert’s dynamic program formulation of DTW, and show empirically that it performs as well as the exact solution while requiring onl...

Introduction. When dealing with time series, the application of a smoothing filter (to get rid of random fluctuations and better recognise the relevant structure) is usually one of the first steps. In the literature on time series similarity measures, however, the impact of smoothing is not explicitly or systematically considered – despite extensive experiments in, e.g., [2]. Instead, complex s...

In this paper, we propose a signature verification system based on Dynamic Time Warping (DTW). The method works by extracting the vertical projection feature from signature images and by comparing reference and probe feature templates using elastic matching. Modifications are made to the basic DTW algorithm to account for the stability of the various components of a signature. The basic DTW and...

Nearest neighbor (NN) classifier with dynamic time warping (DTW) is considered to be an effective method for time series classification. The performance of NN-DTW is dependent on the DTW constraints because the NN classifier is sensitive to the used distance function. For time series classification, the global path constraint of DTW is learned for optimization of the alignment of time series by...

It has long been known that Dynamic Time Warping (DTW) is superior to Euclidean distance for classification and clustering of time series. However, until lately, most research has utilized Euclidean distance because it is more efficiently calculated. A recently introduced technique that greatly mitigates DTWs demanding CPU time has sparked a flurry of research activity. However, the technique a...