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Wyniki wyszukiwania dla: feature vector

Wyniki wyszukiwania dla: feature vector

  • Examining Feature Vector for Phoneme Recognition

    Publikacja

    - Rok 2018

    The aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...

  • Examining Feature Vector for Phoneme Recognition / Analiza parametrów w kontekście automatycznej klasyfikacji fonemów

    Publikacja

    - Rok 2017

    The aim of this paper is to analyze usability of descriptors coming from music information retrieval to the phoneme analysis. The case study presented consists in several steps. First, a short overview of parameters utilized in speech analysis is given. Then, a set of time and frequency domain-based parameters is selected and discussed in the context of stop consonant acoustical characteristics. A toolbox created for this purpose...

  • Fast Distance Vector Field Extraction for Facial Feature Detection

    Publikacja

    Praca dotyczy metody lokalizowania cech twarzy z wykorzystaniem wektorowych pól odległości (DVF), zaproponowanej przez Asteriadisa. Zawiera skrótowy opis tej koncepcji oraz prezentuje ulepszenia wprowadzone przez autorów do oryginalnego rozwiązania. Główną zaletą wprowadzonych zmian jest znacznie zredukowana złożoność obliczeniowa algorytmu, jak również zwiększona precyzja wektorowego pola odległości wyznaczanego w wyniku jego...

  • Low-Level Music Feature Vectors Embedded as Watermarks

    In this paper a method consisting in embedding low-level music feature vectors as watermarks into a musical signal is proposed. First, a review of some recent watermarking techniques and the main goals of development of digital watermarking research are provided. Then, a short overview of parameterization employed in the area of Music Information Retrieval is given. A methodology of non-blind watermarking applied to music-content...

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  • Support Vector Machine Applied to Road Traffic Event Classification

    Publikacja

    - MATEC Web of Conferences - Rok 2018

    The aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application...

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  • Audio Feature Analysis for Precise Vocalic Segments Classification in English

    Publikacja

    An approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...

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  • Automatic music genre classification based on musical instrument track separation / Automatyczna klasyfikacja gatunku muzycznego wykorzystująca algorytm separacji dźwięku instrumentó muzycznych

    Publikacja

    The aim of this article is to investigate whether separating music tracks at the pre-processing phase and extending feature vector by parameters related to the specific musical instruments that are characteristic for the given musical genre allow for efficient automatic musical genre classification in case of database containing thousands of music excerpts and a dozen of genres. Results of extensive experiments show that the approach...

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  • SYNAT_PCA_48

    Dane Badawcze

    There is a series of datasets containing feature vectors derived from music tracks. The dataset contains 51582 music tracks (22 music genres) and feature vector after  Principal Component Analysis (PCA) performing, so there are 48-element vectors derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier...

  • SYNAT Music Genre Parameters PCA 19

    Dane Badawcze

    The dataset contains feature vector after  Principal Component Analysis (PCA) performing, so there are 11 music genres and 19-element vector derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier research studies carried out by the team of authors [1-6]. A collection of 52532 music excerpts described...

  • Comparative analysis of spectral and cepstral feature extraction techniques for phoneme modelling

    Publikacja

    - Rok 2018

    Phoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support...

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  • Music Recommendation System

    The paper focuses on optimization vector content feature for the music recommendation system. For the purpose of experiments a database is created consisting of excerpts of music les. They are assigned to 22 classes corresponding to dierent music genres. Various feature vectors based on low-level signal descriptors are tested and then optimized using correlation analysis and Principal Component Analysis (PCA). Results of the experiments...

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  • SYNAT_PCA_11

    Dane Badawcze

    The dataset contains 51582 music tracks (22 music genres) and feature vector after  Principal Component Analysis (PCA) performing, so there are 11-element vectors derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier research studies carried out by the team of authors [1-6]. A collection of more than...

  • Classifying type of vehicles on the basis of data extracted from audio signal characteristics

    The aim of this study is to find and optimize a feature vector for an automatic recognition of the type of vehicles, extracted form an audio signal. First, the influence of weather-based conditions of road surface on spectral characteristic of the audio signal recorded from a passing vehicle in close proximity to the road is discussed. Next, parameterization of the recorded audio signal is performed. For that purpose, the MIRtoolbox,...

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  • Selection of Features for Multimodal Vocalic Segments Classification

    Publikacja

    English speech recognition experiments are presented employing both: audio signal and Facial Motion Capture (FMC) recordings. The principal aim of the study was to evaluate the influence of feature vector dimension reduction for the accuracy of vocalic segments classification employing neural networks. Several parameter reduction strategies were adopted, namely: Extremely Randomized Trees, Principal Component Analysis and Recursive...

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  • Analiza stanu nawierzchni i klas pojazdów na podstawie parametrów ekstrahowanych z sygnału fonicznego

    Celem badań jest poszukiwanie parametrów wektora cech ekstrahowanego z sygnału fonicznego w kontekście automatycznego rozpoznawania stanu nawierzchni jezdni oraz typu pojazdów. W pierwszej kolejności przedstawiono wpływ warunków pogodowych na charakterystykę widmową sygnału fonicznego rejestrowanego przy przejeżdżających pojazdach. Następnie, dokonano parametryzacji sygnału fonicznego oraz przeprowadzano analizę korelacyjną w celu...

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  • Musical Instrument Separation Applied to Music Genre Classification . Separacja instrumentów muzycznych w zastosowaniu do rozpoznawania gatunków muzycznych

    Publikacja

    - Rok 2015

    This paper outlines first issues related to music genre classification and a short description of algorithms used for musical instrument separation. Also, the paper presents proposed optimization of the feature vectors used for music genre recognition. Then, the ability of decision algorithms to properly recognize music genres is discussed based on two databases. In addition, results are cited for another database with regard to...

  • A comparative study of English viseme recognition methods and algorithm

    An elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector...

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  • A comparative study of English viseme recognition methods and algorithms

    An elementary visual unit – the viseme is concerned in the paper in the context of preparing the feature vector as a main visual input component of Audio-Visual Speech Recognition systems. The aim of the presented research is a review of various approaches to the problem, the implementation of algorithms proposed in the literature and a comparative research on their effectiveness. In the course of the study an optimal feature vector construction...

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  • Selecting Features with SVM

    Publikacja

    A common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection. Experiments were performed on three text datasets generated from a Wikipedia dump. Amount...

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  • Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning

    Publikacja

    The aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...

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