Iskanje po katalogu digitalne knjižnice

Opis: The advanced smart home environment presents an important trend for the future of human wellbeing. One of the prerequisites for applying its rich functionality is the ability to differentiate between various user categories, such as gender, age, speakers, etc. We propose a model for an efficient acoustic gender and age classification system for human–computer interaction in a smart home. The objective was to improve acoustic classification without using high-complexity feature extraction. This was realized with pitch as an additional feature, combined with additional acoustic modeling approaches. In the first step, the classification is based on Gaussian mixture models. In thesecond step, two new procedures are introduced for gender and age classification. The first is based on the count of the frames with the speaker’s pitch values, and the second is based on the sum of the frames with pitch values belonging to a certain speaker. Since both procedures are based on pitch values, we have proposed a new, effective algorithm for pitch value calculation. In order to improve gender and age classification, we also incorporated speech segmentation with the proposed voice activity detection algorithm. We also propose a procedure that enables the quick adaptation of the classification algorithm to frequent smart home users. The proposed classification model with pitch values has improved the results in comparison with the baseline system.
Ključne besede: acoustic classification, acoustic signal processing, Gaussian mixture model, pitch analysis, smart home
Objavljeno v DKUM: 11.12.2023; Ogledov: 471; Prenosov: 23
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Opis: Background and purpose: We explore the problem of License Plate Recognition (LPR) to highlight a number of algorithms that can be used in image analysis problems. In management support systems using image object recognition, the intelligence resides in the statistical algorithms that can be used in various LPR steps. We describe a number of solutions, from the initial thresholding step to localization and recognition of image elements. The objective of this paper is to present a number of probabilistic approaches in LPR steps, then combine these approaches together in one system. Most LPR approaches used deterministic models that are sensitive to many uncontrolled issues like illumination, distance of vehicles from camera, processing noise etc. The essence of our approaches resides in the statistical algorithms that can accurately localize and recognize license plate. Design/Methodology/Approach: We introduce simple and inexpensive methods to solve relatively important problems, using probabilistic approaches. In these approaches, we describe a number of statistical solutions, from the initial thresholding step to localization and recognition of image elements. In the localization step, we use frequency plate signals from the images which we analyze through the Discrete Fourier Transform. Also, a probabilistic model is adopted in the recognition of plate characters. Finally, we show how to combine results from bilingual license plates like Saudi Arabia plates. Results: The algorithms provide the effectiveness for an ever-prevalent form of vehicles, building and properties management. The result shows the advantage of using the probabilistic approached in all LPR steps. The averaged classification rates when using local dataset reached 79.13%. Conclusion: An improvement of recognition rate can be achieved when there are two source of information especially of license plates that have two independent texts.
Ključne besede: image analysis, probabilistic modeling, signal processing, license plate recognition
Objavljeno v DKUM: 28.11.2017; Ogledov: 1501; Prenosov: 367
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Opis: Noise source vizualization represents an important tool in the field of technical acoustics. There are many different techniques of noise source visualization. Most of them, however, are intended for a specific noise source in a specific type of acoustic environment. Consequently, a certain visualization method can be used only for certain types of noise sources in a specific acoustic environment and in a restricted frequency area. This paper presents a new visualization method of complex noise sources on the basis of the use of an acoustic camera. A new algorithm has been used, which makes it possible to visualize all types of different complex noise sources. Monopole, dipole or quadropole noise sources can be observed simultaneously. It is possible to track a moving noise source by means of an acoustic camera. In addition to that it is possible to observe various transient acoustical phenomena. Through the use in diagnostics, it is possible to define, by means of noise, the condition of mechanical systems at an advance level.
Ključne besede: gears, failure, noise sources, visualization of noise sources, sound, acoustic analysis, acoustic camera, signal analysis, acoustic image, measurements
Objavljeno v DKUM: 31.05.2012; Ogledov: 2209; Prenosov: 43
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