Dynamic Time Warping (DTW) is commonly used in gesture recognition tasks in order to tackle the temporal length variability of gestures. In the DTW framework, a set of gesture patterns are compared one by one to a maybe infinite test sequence, and a query gesture category is recognized if a warping cost inferior to a given value is found within the test sequence. Nevertheless, either taking one...

In the paper recently proposed Human Factor Cepstral Coefficients (HFCC) are used to automatic recognition of pathological phoneme pronunciation in speech of impaired children and efficiency of this approach is compared to application of the standard Mel-Frequency Cepstral Coefficients (MFCC) as a feature vector. Both dynamic time warping (DTW), working on whole words or embedded phoneme patter...

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...

When modeling coexpression networks from high-throughput time course data, Pearson Correlation Coefficient (PCC) is one of the most effective and popular similarity functions. However, its reliability is limited since it cannot capture non-linear interactions and time shifts. Here we propose to overcome these two issues by employing a novel similarity function, Dynamic Time Warping Maximal Info...

We present a new space-efficient approach, (SparseDTW ), to compute the Dynamic Time Warping (DTW ) distance between two time series that always yields the optimal result. This is in contrast to other known approaches which typically sacrifice optimality to attain space efficiency. The main idea behind our approach is to dynamically exploit the existence of similarity and/or correlation between...

In this contribution we describe a novel classification approach for on-line handwriting recognition. The technique combines dynamic time warping (DTW) and support vector machines (SVMs) by establishing a new SVM kernel. We call this kernel Gaussian DTW (GDTW) kernel. This kernel approach has a main advantage over common HMM techniques. It does not assume a model for the generative class condit...

A DTW-based directed acyclic graph (DAG) optimization method is proposed to exploit the interaction information of speech and speaker in feature component. We introduce the DAG representation of intra-class samples based on dynamic time warping (DTW) measure and propose two criteria based on in-degree of DAG. Combined with (l − r) optimization algorithm, the DTW-based DAG model is applied to di...

In this work, we present an alignment-based method to perform sign segmentation and to extract isolated signs from continuous sign language videos. Sign videos contain many modalities, the most prominent of which are hand gestures, manifested as hand motion and shape, which are represented by a variety of extracted features in this work. We compare two different alignment approaches, Dynamic Ti...

Vector quantization (VQ) is a widely used matching algorithm for text-independent speaker recognition. In this paper we study the use of text-dependent speaker recognition in practical access control application. We compared dynamic time warping (DTW) to VQ-based matching using textdependent pass phrases. Our goal was to find out, how fixed phrase affects speaker recognition performance. We col...

This paper describes the experiments and observations for Query-by-Example Search on Speech Task (QUESST) at MediaEval 2014. In this paper, we describe two different representations of speech that were explored for the task. We also show the capabilities and limitations of non-segmental dynamic time warping (NS-DTW) technique for searching various types of queries. This paper mainly focuses on ...