Automatic detection of phoneme boundaries is an important sub-task in building speech processing applications, especially text-to-speech synthesis (TTS) systems. The main drawback of the Gaussian mixture model hidden Markov model (GMMHMM) based forced-alignment is that the phoneme boundaries are not explicitly modeled. In an earlier work, we had proposed the use of signal processing cues in tan...

5 Domains of research 10 5.1 Mixture models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 5.1.1 Learning and classification techniques . . . . . . . . . . . . . . . . . . 11 5.1.2 Taking into account the curse of dimensionality. . . . . . . . . . . . 12 5.2 Markov models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 5.2.1 Triplet Markov Fields f...

In this work, we address the task of weakly-supervised human action segmentation in long, untrimmed videos. Recent methods have relied on expensive learning models, such as Recurrent Neural Networks (RNN) and Hidden Markov Models (HMM). However, these methods suffer from expensive computational cost, thus are unable to be deployed in large scale. To overcome the limitations, the keys to our des...

This paper presents a decision tree-based algorithm to cluster residual segments assuming an excitation model based on statedependent filtering of pulse train and white noise. The decision tree construction principle is the same as the one applied to speech recognition. Here parent nodes are split using the residual maximum likelihood criterion. Once these excitation decision trees are construc...

background: routinely collected data from tuberculosis surveillance system can be used to investigate and monitor the irregularities and abrupt changes of the disease incidence. we aimed at using a hidden markov model in order to detect the abnormal states of pulmonary tuberculosis in iran. methods: data for this study were the weekly number of newly diagnosed cases with sputum smear-positive p...

Date stream mining techniques can be used in tracking user behaviors as they attempt to achieve their goals. Quality metrics over stream-mined models identify potential changes in user goal attainment. When the quality of some data mined models varies significantly from nearby models—as defined by quality metrics—then the user’s behavior is automatically flagged as a potentially significant beh...

The widespread application of positron emission tomography (PET) in clinical oncology has driven this imaging technology into a number of new research and clinical arenas. Increasing numbers of patient scans have led to an urgent need for efficient data handling and the development of new image analysis techniques to aid clinicians in the diagnosis of disease and planning of treatment. Automati...

In this paper, we propose a novel technique for video shot segmentation and classiication based on the Singular Value Decomposition (SVD). For the input video sequence, we create a feature-frame matrix A, and perform the SVD on it. From this SVD, we are able to not only derive the reened feature space to better segment the video sequence along time axis, but also deene metrics to enable classii...

This paper presents a hidden Markov model (HMM) based approach to on-line handwritten digit recognition using stroke sequences. In this approach, a character instance is represented by a sequence of symbolic strokes, and the representation is obtained by component segmentation and stroke classification. The component segmentation is based on the delta lognormal model of handwriting generation. ...