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In this paper, we investigate methods to improve the recognition performance of low-resource languages with limited training data by borrowing subspace parameters from a high-resource language in subspace Gaussian mixture model (SGMM) framework. As a first step, only the state-specific vectors are updated using low-resource language, while retaining all the globally shared parameters from the high-resource...
Aligning two representations of the same domain with different expressiveness is a crucial topic in nowadays semantic web and big data research. OWL ontologies and Entity Relation Diagrams are the most widespread representations whose alignment allows for semantic data access via ontology interface, and ontology storing techniques. The term ""alignment" encompasses three different processes:...
We propose a language based on relational algebra extended by intervals for detecting high-level surveillance events from a video stream. The operators we introduce for describing temporal constraints are based on the well-known Allen's interval relationships. The semantics of our language are clearly defined and we illustrate its usefulness by expressing typical events in it and showing the promising...
This work proposes a system that percepts handsigns and gestures via computer vision system and extractsufficient amount of images from it. After applying imageprocessing and extracting the features of the images, the systemuses an algorithm to recognize the hand signs and gestures. Inthe process of recognizing the hand signs, the Artificial NeuralNetwork (ANN) is being trained with some specific...
Heterogeneous image conversion is a critical issue in many computer vision tasks, among which example-based face sketch style synthesis provides a convenient way to make artistic effects for photos. However, existing face sketch style synthesis methods generate stylistic sketches depending on many photo-sketch pairs. This requirement limits the generalization ability of these methods to produce arbitrarily...
One of the major challenge in human emotion recognition is extraction of features containing maximum prosodic information. The accuracy of entire emotion detection system eventually relies upon the efficiency of the selected feature. When it comes to identifying emotions from voice, ambiguity in detection can never be completely avoided due to several reasons. Exclusion of redundant information to...
The aim of this work is to automatically detect and analyse the emotions from the digital videos and images. Initially the images are extracted from pre-recorded videos, from which the faces are cropped automatically. The training dataset is formed with minimal number of images per subject for each emotion. Bi-dimensional Empirical Mode Decomposition (BEMD) is used to decompose the images in its Intrinsic...
Building natural scene statistic models is a potentially transformative development for a wide variety of visual applications, ranging from the design of faithful image and video quality models to the development of perceptually optimized image enhancing techniques. Most predominant statistical models of natural images only characterize the univariate distributions of divisively normalized bandpass...
Design a software system on smart phone platform. The purpose of this system is providing a reasonable method to evaluate the English accent of non-native speakers, based on the phoneme recognition and fluency assessment, taking advantage of Hidden Markov Model (HMM). Meanwhile, this paper would use the neural net algorithm to combine the objective scoring and experts' scoring to increase the accuracy...
The safety of miners is of interest to all countries. In the event of a coal mine disaster, how to locate the miners remains the biggest and most urgent issue. The aim of this study is to propose a precise positioning method for underground mine environments. In this paper, a layered two-step Hidden Markov Model is proposed to simulate human walking in underground mine environments and an improved...
In this paper, a novel sparse representation over learned and exemplar dictionaries is explored to estimate the speech information of stressed speech. Stressed speech contains speech and stress informations. The acoustic variabilities are induced due to presence of stress information, which results in degradation of the performance of speech recognition system. In this work, the acoustic variabilities...
There has been a considerable use of acoustic features for speaker identification and recognition. Few of these features have also been used by researchers to recognize emotions in speech effectively. Here an attempt is made to characterize human speech emotions with acoustic features as speech rate, formant frequencies, amplitude and energy initially. Further, a reduced acoustic feature set based...
There has been confusion about the American Midland dialect for a long time. Since 1968, researchers have been looking for an answer to the question of whether it exists or not. Starting with Bailey, who was unsuccessful in identifying the Midland dialect based on vocabulary only, as vocabulary varies within the same community, and ending with Johnson, who proved that the Midland region is a separate...
Smile is not only a visual expression. When it occurs together with speech, it also alters its acoustic realization. Being able to synthesize speech altered by the expression of smile can hence be an important contributor for adding naturalness and expressiveness in interactive systems. In this work, we present a first attempt to develop a Hidden Markov Model (HMM)-based synthesis system allowing...
In speech recognition, it is preferable not to hypothesize the details, e.g., specific age and gender, of a target user. However, speaker independence is one of the things that degrades ASR performance. In this work, we propose a speaker adaptation method to recognize a short time utterance. There have been several studies on speaker-independent DNN-HMM in which i-vector is computed, and the additional...
Nowadays, hand gesture is one of main considerations for hearing impaired people because they use sign language to communicate with each other and to normal people. In general, the normal people have difficulties with sign language therefore they need an interpreter supporting communication. Then the automatic hand gesture recognition system is needed to help hearing impaired people integrating into...
This paper proposes a system that allows recognizing a person's emotional state with the help of recording audio signals. This system is able to recognize four emotions (anger, happiness, sadness and neutral) This emotion recognition technique is mainly composed of two subsystems as - 1) gender recognition (GR) and 2) emotion recognition (ER). It has been proved experimentally that the performance...
Automatic personal identification from their physical and behavioral traits, called biometrics technologies, is now needed in many fields such as: surveillance systems, access control systems, physical buildings and many more applications. In this paper, we propose an efficient online personal identification system based on Multi-Spectral Palmprint images (MSP) using Hidden Markov Model (HMM) and...
Application specific intrusion detection methods are used to detect network intrusions targeted at applications. Normally such detection methods require payload or packet content analysis. One of the prominent method of payload modeling and analysis is sequence or ngram modeling. Normally ngrams generated from a packet are compared with a database of ngrams seen during training phase. Depending on...
This paper presents a robust and anticipative realtime gesture recognition and its motion quality analysis module. By utilizing a motion capture device, the system recognizes gestures performed by a human, where the recognition process is based on skeleton analysis and motion features computation. Gestures are collected from a single person. Skeleton joints are used to compute features which are stored...
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