This paper compares Dynamic Time Warping (DTW) and Waveform Matching (WFM), the two gesture recognition techniques, applied on a specific Squash game application we have developed. Our application gets accelerometer readings by moving the NintendoTM Wiimote in a 3D space. This application manipulates the Wiimote gestures in the form of signals. These signals are the effect of the movements, the...

Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each te...

We propose a dynamic time-warping (DTW) based distortion measure for measuring the dissimilarity between pairs of left-to-right continuous density hidden Markov models with state observation densities being mixture of Gaussians. The local distortion score required in DTW is defined as an approximate Kullback-Leibler divergence (KLD) between two Gaussian mixture models (GMMs). Several approximat...

Distributed computing is the method of splitting a large problem into smaller pieces and allocating the workload among many computers. These individual computers process their portions of the problem, and the results are combined together to form a solution for the original problem. At present, Distributed computing systems can be broadly classified into two methods, namely Grid computing and V...

There has been much recent interest in adapting data mining algorithms to time series databases. Many of these algorithms need to compare time series. Typically some variation or extension of Euclidean distance is used. However, as we demonstrate in this paper, Euclidean distance can be an extremely brittle distance measure. Dynamic time warping (DTW) has been suggested as a technique to allow ...

There has been much recent interest in adapting data mining algorithms to time series databases. Many of these algorithms need to compare time series. Typically some variation or extension of Euclidean distance is used. However, as we demonstrate in this paper, Euclidean distance can be an extremely brittle distance measure. Dynamic time warping (DTW) has been suggested as a technique to allow ...

Time series averaging in dynamic time warping (DTW) spaces has been successfully applied to improve pattern recognition systems. This article proposes and analyzes subgradient methods for the problem of finding a sample mean in DTW spaces. The class of subgradient methods generalizes existing sample mean algorithms such as DTW Barycenter Averaging (DBA). We show that DBA is a majorize-minimize ...

In this paper, we investigate the task of translating spontaneous speech transcriptions by employing aligned movie subtitles in training a statistical machine translator (SMT). In contrast to the lexical-based dynamic time warping (DTW) approaches to bilingual subtitle alignment, we align subtitle documents using time-stamps. We show that subtitle time-stamps in two languages are often approxim...

Dynamic time warping (DTW) is a popular distance measure for series analysis and has been applied in many research domains. This paper proposes the R package IncDTW incremental calculation of DTW, based on this principle also helps to classify or cluster series, perform subsequence matching k-nearest neighbor search. DTW can dissimilarity between two temporal sequences which may vary speed, wit...