Wyniki wyszukiwania dla: MUSIC DATABASES - MOST Wiedzy

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Wyniki wyszukiwania dla: MUSIC DATABASES

Wyniki wyszukiwania dla: MUSIC DATABASES

  • Music Data Processing and Mining in Large Databases for Active Media

    Publikacja

    - Rok 2014

    The aim of this paper was to investigate the problem of music data processing and mining in large databases. Tests were performed on a large data-base that included approximately 30000 audio files divided into 11 classes cor-responding to music genres with different cardinalities. Every audio file was de-scribed by a 173-element feature vector. To reduce the dimensionality of data the Principal Component Analysis (PCA) with variable...

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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...

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

    Publikacja

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

    Publikacja

    - Rok 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 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...

  • SYNAT_MUSIC_GENRE_FV_173

    Dane Badawcze

    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

    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_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...

  • Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results

    Publikacja

    The continuous growth of the computing power of processors, as well as the fact that computational clusters can be created from combined machines, allows for increasing the complexity of algorithms that can be trained. The process, however, requires expanding the basis of the training sets. One of the main obstacles in music classification is the lack of high-quality, real-life recording database for every instrument with a variety...

  • Identyfikacja instrumentu muzycznego z nagrania fonicznego za pomocą sztucznych sieci neuronowych

    Publikacja

    - Rok 2024

    Celem rozprawy jest zbadanie algorytmów do identyfikacji instrumentów występujących w sygnale polifonicznym z wykorzystaniem sztucznych sieci neuronowych. W części teoretycznej przywołano podstawy przetwarzania sygnałów fonicznych w kontekście ekstrakcji parametrów sygnałów wykorzystywanych w treningu sieci neuronowych. Dodatkowo dokonano analizy rozwoju metod uczenia maszynowego z uwzględnieniem podziału na sieci neuronowe pierwszej,...

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  • SUBJECTIVE PERCEPTION OF MUSIC GENRES IN THE FIELD OF MUSIC INFORMATION RETRIEVAL SYSTEMS

    Publikacja

    - Rok 2014

    The aim of this paper is to evaluate the relationship between perception of music genres and subjective features of music that can be assigned to them. For this purpose a group of subjective features such as loudness, melody, rhythm, volume, instrumentation was chosen to describe music genres. A group of 30 listeners with normal hearing, ranging from 20 to 40, was created. Each sub-ject participating in listening tests was asked...

  • SUBJECTIVE PERCEPTION OF MUSIC GENRES IN THE FIELD OF MUSIC INFORMATION RETRIEVAL SYSTEMS

    Publikacja

    - Rok 2014

    The aim of this paper is to evaluate the relationship between perception of music genres and subjective features of music that can be assigned to them. For this purpose a group of subjective features such as loudness, melody, rhythm, volume, instrumentation was chosen to describe music genres. A group of 30 listeners with normal hearing, ranging from 20 to 40, was created. Each sub-ject participating in listening tests was asked...

  • 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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