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This paper introduces a novel approach to exemplar-based connected digit recognition. The approach is tested for different sizes of the exemplar collection (from 250 to 16,000), different length of the exemplars (from 1 to 50 time frames) and state-labeled versus word-labeled decoding. In addition, we compare the novel method for selecting exemplars, based on Sparse Classification, with a conventional...
In comparison with standard HMM (Hidden Markov Model) with forced alignment, this paper discusses two automatic segmentation algorithms from different points of view: the probabilities of insertion and omission, and the accuracy. The first algorithm, hereafter named the refined HMM algorithm, aims at refining the segmentation performed by standard HMM via a GMM (Gaussian Mixture Model) of each boundary...
This paper presents a framework to recognize the symbols drawn in air using bare hand motion. The work marks a step towards development of non-tactile interfaces requiring no physical means for writing or drawing. To overcome the limitations of traditional two dimensional camera based acquisition, a preliminary step in gesture recognition, depth based sensor is used to acquire trajectory signals....
In the languages, the occur of words are indicated about meaning of contents in text. Generative models for text, such as the topic model, have the potential to make important contributions to the statistical analysis of large document collections, and the development of a deeper understanding of human language learning and processing. In this paper, we proposed a novel method for building Vietnamese...
Aiming at the problem of Chinese thesaurus construction, we propose a method of using HMM to extract new terms from academic literature to expand automatically entry-words for Chinese thesaurus. This method converts the new terms extraction problem to a sequence labelling problem. It uses HMM fully integrated lexical information and syntactic information of new terms, as well as local context information,...
Prognostic is nowadays recognized as a key feature in maintenance strategies as it should allow avoiding inopportune maintenance spending. Real prognostic systems are however scarce in industry. That can be explained from different aspects, on of them being the difficulty of choosing an efficient technology: many approaches to support the prognostic process exist, whose applicability is highly dependent...
Video content classification and retrieval is a necessary tool in the current merging of entertainment and information media. With the advent of broadband networking, every consumer will have video programs available on-line as well as in the traditional distribution channels. Systems that help in content management have to discern between different categories of video in order to provide for fast...
Weighting the stream outputs according to their reliability levels is one of the most common stream fusion methods in the multi-stream automatic speech recognition (MS ASR). However, when a MS ASR system works in noisy environments, there are distortion level differences among not only the data streams, but also the feature components inside a stream. In this paper, we first propose a feature component...
Part Of Speech tagging (POS) is the basic process for almost all natural language processing (NLP) applications. The typical methods for combining different taggers, the program doing POS tagging, are voting or stacking techniques. We propose here a Master-Slaves Technique, which can combine Hidden Markov Model (HMM) tagger as master and any number of other taggers of any type as slaves. We describe...
In this paper we assess about the recognition of User Interaction events when handling electrical devices. This work is placed in the context of Intrusive Load Monitoring used for appliance recognition. ILM implies several Smart Metering Sensors to be placed inside the environment under analysis (in our case we have one Smart Metering Sensor per device). Our existing system is able to recognise the...
The actual field survey data from the Rice Department of Thailand's Ministry of Agriculture over a large area wastes a huge amount of resources. To solve this problem, this paper proposes a new approach to estimate rice phenology using SAR images derived from the RADARSAT-2 data. In this work, we divided the rice phenology into five stages, consisting of seedling, tillering, reproductive, ripening,...
The growing affordability of smart phones and mobile devices has only added to this trend by encouraging prolonged durations of inactivity. In this paper, we present a middleware, called the Pervasive Middleware for Activity Recognition (PEMAR) that aims to increase the level of physical activity by creating a middleware for active games on mobile devices. For the PEMAR application, we present a human...
Pattern recognition and classification algorithms are widely studied in natural gesture interfaces for upper limb prostheses. Robustness and accuracy of control systems are key challenge in such applications. To improve the classification performance, the conventional approach builds on classifier parameters tuning and/or feature extraction techniques. In this paper, we propose a complementary approach...
The automatic identification of appliances through the analysis of their electricity consumption has several purposes in Smart Buildings including better understanding of the energy consumption, appliance maintenance and indirect observation of human activities. Electric signatures are typically acquired with IoT smart plugs integrated or added to wall sockets. We observe an increasing number of research...
Intrusion detection system is widely used to protect and reduce damage to information system. It protects virtual and physical computer networks against threats and vulnerabilities. Presently, machine learning techniques are widely extended to implement effective intrusion detection system. Neural network, statistical models, rule learning, and ensemble methods are some of the kinds of machine learning...
Pedestrian navigation via dead reckoning (PDR) is considered a promising domain for search and rescue personnel tracking, particularly for fire-fighters. The technique is considered particularly useful when other conventional means such as the GPS and RF-based location estimation are not present or not accurate. However, PDR approaches in real-world operating environments fail due to a wide range...
Hidden Markov Models (HMM) are used in handwritten strokes recognition task. The two design parameters of HMM are the number of states and number of mixtures in each state. There are two approaches for finding the number of states, namely, equal number of states and variable number of states. Since the shape of strokes will be different, variable number of states approach should be beneficial. This...
Percussion instruments play a significant role in Carnatic music concerts. The percussion artist enjoys a great degree of freedom in improvising within the defined tāla structure of a composition. The objective of this paper is to transcribe the improvisations, treating the percussion strokes as syllables or aksharas.
In the storyteller speech, pauses plays a significant role in introducing suspense and climax. Pauses are used to emphasize keywords, emotion-salient words and separate the phrases in the utterance. The objective of this work is to predict the position and duration of the pauses in the synthesized speech from the text-to-speech system. We analyzed the pause patterns in storyteller speech and classified...
Hidden Markov Models (HMM) are the widely used modeling techniques for online handwriting recognition. This paper describes both stroke based and character based methods for Assamese handwritten character recognition using HMM classifier. In stroke based method, unique strokes that are used to write the characters are grouped and then HMM modeling is done for each of these selected class of strokes...
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