Search results for: GENRE RECOGNITION - Bridge of Knowledge

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Search results for: GENRE RECOGNITION

Search results for: GENRE RECOGNITION

  • Music Genre Recognition in the Rough Set-Based Environment

    Publication

    - Year 2015

    The aim of this paper is to investigate music genre recognition in the rough set-based environment. Experiments involve a parameterized music data-base containing 1100 music excerpts. The database is divided into 11 classes cor-responding to music genres. Tests are conducted using the Rough Set Exploration System (RSES), a toolset for analyzing data with the use of methods based on the rough set theory. Classification effectiveness...

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  • Bass Enhancement Settings in Portable Devices Based on Music Genre Recognition

    The paper presents a novel approach to the Virtual Bass Synthesis (VBS) applied to mobile devices, called Smart VBS (SVBS). The proposed algorithm uses an intelligent, rule-based setting of bass synthesis parameters adjusted to the particular music genre. Harmonic generation is based on a nonlinear device (NLD) method with the intelligent controlling system adapting to the recognized music genre. To automatically classify music...

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  • Elgold: gold standard, multi-genre dataset for named entity recognition and linking

    Open Research Data
    version 1.0 open access

    The dataset contains 276 multi-genre texts with marked named entities, which are linked to corresponding Wikipedia articles if available. Each entity was manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.

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

    Publication

    - Year 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...

  • Smart Virtual Bass Synthesis Algorithm Based on Music Genre Classification

    Publication

    The aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The proposed algorithm employed automatic music genre recognition to determine the optimum parameters for the synthesis of additional frequencies. The synthesis was carried out using the non-linear device (NLD) and phase vocoder (PV) methods depending on the music excerpt genre. Classification of musical...

  • In uence of Low-Level Features Extracted from Rhythmic and Harmonic Sections on Music Genre Classi cation

    Publication

    - Year 2013

    We present a comprehensive evaluation of the infuence of 'harmonic' and rhythmic sections contained in an audio file on automatic music genre classi cation. The study is performed using the ISMIS database composed of music files, which are represented by vectors of acoustic parameters describing low-level music features. Non-negative Matrix Factorization serves for blind separation of instrument components. Rhythmic components...

  • Music genre classification applied to bass enhancement for mobile technology

    The aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) algorithms applied to portable computers. The proposed algorithm is related to intelligent, rule-based setting of synthesis parameters according to music genre of an audio excerpt. The classification of music genres is automatically executed employing MPEG 7 parameters and the Principal Component Analysis method applied to reduce information...

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  • Discovering Rule-Based Learning Systems for the Purpose of Music Analysis

    Publication

    Music analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...

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  • Creating a Realible Music Discovery and Recomendation System

    The aim of this paper is to show problems related to creating a reliable music dis-covery system. The SYNAT database that contains audio files is used for the purpose of experiments. The files are divided into 22 classes corresponding to music genres with different cardinality. Of utmost importance for a reliable music recommendation system are the assignment of audio files to their appropriate gen-res and optimum parameterization...

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  • SYNAT Music Genre Parameters PCA 19

    Open Research Data

    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...

  • EEG data recorded in three mental states

    Open Research Data

    Electroencephalographic (EEG) signals were acquired from 17 (14 males, 3 females) participants aged between 20 and 30 years. 

  • SYNAT_MUSIC_GENRE_FV_173

    Open Research Data

    This is the original dataset containing 51582 music tracks (22 music genres) and 173 element-feature vector [1-6,9]. A collection of more than 50000 music excerpts described with a set of descriptors obtained through the analysis of 30-second mp3 recordings was gathered in a database called SYNAT. The SYNAT database was realized by the Gdansk University...

  • SYNAT_PCA_48

    Open Research Data

    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_PCA_11

    Open Research Data

    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...

  • Porównanie wyników klasyfikacji gatunków muzycznych uzyskanych za pomocą testów subiektywnych i algorytmów uczących się

    Celem pracy jest przeprowadzenie testów subiektywnych rozróżniania gatunku muzycznego przez słuchaczy oraz dokonanie automatycznej klasyfikacji gatunków muzycznych przy pomocy wybranych algorytmów uczących się. W pierwszej kolejności przywołano genezę podziału na gatunki muzyczne. W ramach pracy zrealizowana została ankieta internetowa w celu umożliwienia odsłuchu i przypisania próbek dźwiękowych do wybranych gatunków muzycznych...