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...

The study proposes an algorithm for noise cancellation by using recursive least square (RLS) and pattern recognition by using fusion method of Dynamic Time Warping (DTW) and Hidden Markov Model (HMM). Speech signals are often corrupted with background noise and the changes in signal characteristics could be fast. These issues are especially important for robust speech recognition. Robustness is...

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...

Nowadays, the alignment of multidimensional sequences is required in many applications especially for multimedia data. The ordinary DTW is not well satisfied this condition because it can only align a pair of 1D sequences at once. Applying traditional DTW to these tasks not only makes each pairwise alignments are independent but also causes each dimensions are compared separately. In this paper...

The dynamic time warping (DTW) algorithm is able to find the optimal alignment between two time series. It is often used to determine time series similarity, classification, and to find corresponding regions between two time series. DTW has a quadratic time and space complexity that limits its use to only small time series data sets. In this paper we introduce FastDTW, an approximation of DTW t...

Temporal alignment of human motion performing similar activities has been a topic of recent interest due to its many applications in animation, tele-rehabilitation or activity recognition. This paper presents generalized time warping (GTW), an extension of dynamic time warping (DTW) for temporally aligning multi-modal sequences from multiple subjects performing similar activities. GTW solves th...

Dynamic time warping (DTW) is a successful algorithm in many matching and searching tasks. For the text-dependent speaker verification, it is still an appropriate choice when enrollment data are very limited. Yet DTW is very sensitive to the endpoint variations between the reference template and test examples. Most research reported on this issue is mainly in two directions: robust endpoint det...

Common approaches to automatic speech recognition (ASR) are based on training statistical models for the acoustics of speech. In our work, a retrieval-based ASR system is developed that does not rely on training and thus provides more flexible application. It is based on a set of known reference word utterances for each possibly occurring word in a test string. A test word string is identified ...

This paper introduces a method for human action recognition based on optical flow motion features extraction. Automatic spatial and temporal alignments are combined together in order to encourage the temporal consistence on each action by an enhanced dynamic time warping (DTW) algorithm. At the same time, a fast method based on coarse-to-fine DTW constraint to improve computational performance ...