Search results for: musical genre recognition - Bridge of Knowledge

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Search results for: musical genre recognition

Search results for: musical genre recognition

  • Guido: a musical score recognition system

    Publication

    - Year 2007

    This paper presents an optical music recognition system Guido that can automatically recognize the main musical symbols of music scores that were scanned or taken by a digital camera. The application is based on object model of musical notation and uses linguistic approach for symbol interpretation and error correction. The system offers musical editor with a partially automatic error correction.

  • 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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  • Soft computing based automatic recognition of musical instrument classes.

    W artykule przedstawiono wyniki eksperymentów dotyczących automatycznego rozpoznawania klas instrumentów muzycznych. Proces klasyfikacji zrealizowano w oparciu o sztuczne sieci neuronowe, zaś wektor cch został oparty o parametry obliczane w wyniku analizy falkowej dźwięków instrumentów muzycznych.

  • Musical phrase representation and recognition by means of neural networks and rough sets.

    Publication

    - Year 2004

    W artykule przedstawiono podstawowe definicje dotyczące frazy muzycznej. W eksperymentach posłużono się zapisem parametrycznym. W celu wzmocnienia procesu rozpoznawania wykorzystano kodowanie entropijne muzyki. W eksperymentach klasyfikacji oparto się o sztuczne sieci neuronowe i metodę zbiorów przybliżonych. Słowa kluczowe: fraza muzyczna, klasyfikacja, sztuczne sieci neuronowe, metoda zbiorów przybliżonych

  • 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...

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

    Publication

    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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  • 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.

  • ''Computing with words'' concept applied to musical instrument recognition. W: [CD-ROM] International Symposium of Musical Acoustics. ISMA MEXICO CITY. Mexico City, 9-13 December 2002. Mexico City: Escuela Nacional de Musica UNAM**2002, 8 s. 3 rys. 3 tab. bibliogr. 25 poz. Automatyczne rozpoznawanie klas instrumentów muzycznych w oparciu o wyraże- nia opisujące barwę dźwięku.

    Publication

    - Year 2002

    W referacie przedstawiono nowy sposób automatycznego przetwarzania danychmuzycznych w oparciu o paradygmat zaproponowany przez L. Zadeha. Pozwala tona automatyczne rozpoznawanie klas instrumentów muzycznych wykorzystując o-pis słowny barwy dźwięku. Przedstawiono system realizujący automatyczną kla-syfikację instrumentów muzycznych oparty o metodę zbiorów przybliżonych ilogikę rozmytą.

  • 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...

  • 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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  • Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation

    In this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic model,...

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  • Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation

    Publication

    - Year 2014

    In this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic...

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  • 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...

  • Observing uncertainty in music tagging by automatic gaze tracking

    Publication

    - Year 2011

    In this paper, a new approach to observe music file tagging process by employing a gaze tracking system is proposed. The study was conducted with the participation of twenty subjects having different musical experience. For the purpose of the experiments a website survey based on a musical database was prepared. It allowed to gather information about music experience of subjects along with music characteristics such as genre, tempo,...

  • 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...

  • Testing a Variety of Features for Music Mood Recognition. Testowanie zestawu parametrów w celu rozpoznawania nastroju w muzyce

    Music collections are organized in a very different way depending on a target, number of songs or a distribution method, etc. One of the high-level feature, which can be useful and intuitive for listeners, is “mood”. Even if it seems to be the easiest way to describe music for people who are non-experts, it is very difficult to find the exact correlation between physical features and perceived impressions. The paper presents experiments...

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  • Evaluation of a Novel Approach to Virtual Bass Synthesis Strategy

    Publication

    - Year 2015

    The aim of this paper is to present a novel approach to the Virtual Bass Synthesis (VBS) strategy applied to portable computers. The developed algorithms involve intelligent, rule-based settings of bass synthesis parameters with regard to music genre of an audio excerpt and the type of a portable device in use. The Smart VBS algorithm performs the synthesis based on a nonlinear device (NLD) with artificial controlling synthesis...

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  • Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing

    Developing signal processing methods to extract information automatically has potential in several applications, for example searching for multimedia based on its audio content, making context-aware mobile applications (e.g., tuning apps), or pre-processing for an automatic mixing system. However, the last-mentioned application needs a significant amount of research to reliably recognize real musical instruments in recordings....

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  • Introduction to the special issue on machine learning in acoustics

    Publication
    • Z. Michalopoulou
    • P. Gerstoft
    • B. Kostek
    • M. A. Roch

    - Journal of the Acoustical Society of America - Year 2021

    When we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...

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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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  • Music Information Retrieval – Soft Computing versus Statistics . Wyszukiwanie informacji muzycznej - algorytmy uczące versus metody statystyczne

    Publication

    - Year 2015

    Music Information Retrieval (MIR) is an interdisciplinary research area that covers automated extraction of information from audio signals, music databases and services enabling the indexed information searching. In the early stages the primary focus of MIR was on music information through Query-by-Humming (QBH) applications, i.e. on identifying a piece of music by singing (singing/whistling), while more advanced implementations...

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  • 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...

  • Audio Content and Crowdsourcing: A Subjective Quality Evaluation of Radio Programs Streamed Online

    Publication

    - Year 2023

    Radio broadcasting has been present in our lives for over 100 years. The transmission of speech and music signals accompanies us from an early age. Broadcasts provide the latest information from home and abroad. They also shape musical tastes and allow many artists to share their creativity. Modern distribution involves transmission over a number of terrestrial systems. The most popular are analog FM (Frequency Modulation) and...

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  • Automatic Rhythm Retrieval from Musical Files

    Publication

    - Year 2008

    This paper presents a comparison of the effectiveness of two computational intelligence approaches applied to the task of retrieving rhythmic structure from musical files. The method proposed by the authors of this paper generates rhythmic levels first, and then uses these levels to compose rhythmic hypotheses. Three phases: creating periods, creating simplified hypotheses and creating full hypotheses are examined within this study....

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  • Intelligent equalizer solution employing music genre and the room characteristics analysis

    The paper presents an intelligent equalizer solution based on room acoustic conditions and music genre analysis. A series of acoustic characteristic measurements are performed for checking the concept proposed. White noise (reference signal) and audio excerpts belonging to six music genres are utilized as excitation signals in measurements. This results in registration of frequency responses of rooms and reverberation times. Signals...

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  • Genre

    Journals

    ISSN: 0016-6928

  • A Study on Influence of Normalization Methods on Music Genre Classification Results Employing kNN Algorithms

    This paper presents a comparison of different normalization methods applied to the set of feature vectors of music pieces. Test results show the influence of min-nlax and Zero-Mean normalization methods, employing different distance functions (Euclidean, Manhattan, Chebyshev, Minkowski) as a pre-processing for genre classification, on k-Nearest Neighbor (kNN) algorithm classification results.

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  • Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio

    Publication

    - IEEE INTELLIGENT SYSTEMS - Year 2024

    The purpose of this paper is to introduce neural network-based methods that surpass state-of-the-art (SOTA) models, either by training faster or having simpler architecture, while maintaining comparable effectiveness in musical instrument identification in polyphonic music. Several approaches are presented, including two authors’ proposals, i.e., spiking neural networks (SNN) and a modular deep learning model named FMCNN (Fully...

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  • Musical inspiration in contemporary architecture - to build a music and to hear an architecture

    Publication

    - Year 2009

    The goal of this research is chosen from a wide range of subjects within two fields of knowledge on the crossroads between music and architecture There are many designs in modern contemporary architecture that would illustrate the relationship between music and architecture, mainly through musical inspiration. The article shows contemporary musical and architectural discussion that cross over from the theoretical to the practical...

  • A concept of Signal Equalization Method Based on Music Genre and the Listener's Room Characteristics

    Publication

    - Year 2016

    A research study that investigates the influence of the room acoustics environment on the frequency characteristic of the audio signal playback is presented. First, a novel spectral equalization method of the room acoustic conditions is introduced. On the basis of the frequency response of the room, a system for room acoustics compensation based on eight-band equalizer is proposed. The system settings depend on music genre. In...

  • Genre & Histoire

    Journals

    eISSN: 2102-5886

  • Musical Instrument Identification Using Deep Learning Approach

    Publication

    - SENSORS - Year 2022

    The work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...

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  • Uncertainty in emotion recognition

    Purpose–The purpose of this paper is to explore uncertainty inherent in emotion recognition technologiesand the consequences resulting from that phenomenon.Design/methodology/approach–The paper is a general overview of the concept; however, it is basedon a meta-analysis of multiple experimental and observational studies performed over the past couple of years.Findings–The mainfinding of the paper might be summarized as follows:...

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  • Recognition and sensing of anions

    Publication

    Molecular ion recognition is one of the most intensively studied areas of supramolecular technology. The reason for this is the essential role that ions play in many biological as well as industrial processes. On the other hand, however, it has been proved that ions can have a negative impact on human health and the environment. For these reasons, it is extremly important to develop rapid and simple methods allowing the determination...

  • Language Models in Speech Recognition

    Publication

    - Year 2022

    This chapter describes language models used in speech recognition, It starts by indicating the role and the place of language models in speech recognition. Mesures used to compare language models follow. An overview of n-gram, syntactic, semantic, and neural models is given. It is accompanied by a list of popular software.

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  • Integration in Multichannel Emotion Recognition

    Publication

    - Year 2018

    The paper concerns integration of results provided by automatic emotion recognition algorithms. It presents both the challenges and the approaches to solve them. Paper shows experimental results of integration. The paper might be of interest to researchers and practitioners who deal with automatic emotion recognition and use more than one solution or multichannel observation.

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  • Human emotion recognition with biosignals

    Publication

    - Year 2022

    This chapter presents issues in the field of affective computing. Basic preliminary information for the recognition of emotions is given and models of emotions, various ways of evoking emotions, as well as their theoretical foundations are discussed. The particular attention is given to the use of physiological signals in recognizing emotions. This subject is outlined further below by presenting selected biosignals, their relationship...

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  • Automatic tagging of musical files

    Publication

    - Year 2011

    Celem niniejszej pracy jest zbadanie możliwości automatycznego tagowania utworów muzycznych z wykorzystaniem systemu śledzenia punktu fiksacji wzroku użytkownika. Badania przeprowadzono z udziałem dwudziestu osób o różnym doświadczeniu muzycznym. Zadaniem badanej osoby było wskazanie odpowiedzi na pytania zawarte w ankiecie internetowej, która pozwala na określenie cech utworów muzycznych, takich jak: tempo, dynamika, gatunek....

  • Automatic sound recognition for security purposes

    Publication

    - Year 2008

    In the paper an automatic sound recognition system is presented. It forms a part of a bigger security system developed in order to monitor outdoor places for non-typical audio-visual events. The analyzed audio signal is being recorded from a microphone mounted in an outdoor place thus a non stationary noise of a significant energy is present in it. In the paper an especially designed algorithm for outdoor noise reduction is presented,...

  • Recognition of Hand Drawn Flowcharts

    Publication

    - Year 2013

    In this paper the problem of hand drawn flowcharts recognition is presented. There are described two attitudes to this problem: on-line and off-line. A concept of FCE, a system for recognizing and understanding of freehand drawn on-line flow charts on desktop computer and mobile devices is presented. The first experiments with the FCE system and the planes for future are also described.

  • Semantic Integration of Heterogeneous Recognition Systems

    Publication

    - LECTURE NOTES IN COMPUTER SCIENCE - Year 2011

    Computer perception of real-life situations is performed using a variety of recognition techniques, including video-based computer vision, biometric systems, RFID devices and others. The proliferation of recognition modules enables development of complex systems by integration of existing components, analogously to the Service Oriented Architecture technology. In the paper, we propose a method that enables integration of information...

  • Anuario Musical

    Journals

    ISSN: 0211-3538 , eISSN: 1988-4125

  • Musical Times

    Journals

    ISSN: 0027-4666

  • Musical Quarterly (The)

    Journals

    ISSN: 0027-4631 , eISSN: 1741-8399

  • Using Physiological Signals for Emotion Recognition

    Publication

    - Year 2013

    Recognizing user’s emotions is the promising area of research in a field of human-computer interaction. It is possible to recognize emotions using facial expression, audio signals, body poses, gestures etc. but physiological signals are very useful in this field because they are spontaneous and not controllable. In this paper a problem of using physiological signals for emotion recognition is presented. The kinds of physiological...

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  • Emotion Recognition for Affect Aware Video Games

    In this paper the idea of affect aware video games is presented. A brief review of automatic multimodal affect recognition of facial expressions and emotions is given. The first result of emotions recognition using depth data as well as prototype affect aware video game are presented

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