Wyniki wyszukiwania dla: MUSIC INFORMATION RETRIEVAL (MIR) AUTOMATIC MUSIC GENRE CLASSIFICATION AUTOMATIC SEPARATION OF MUSIC TRACKS SUPPORT VECTOR MACHINE (SVM) - MOST Wiedzy

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Wyniki wyszukiwania dla: MUSIC INFORMATION RETRIEVAL (MIR) AUTOMATIC MUSIC GENRE CLASSIFICATION AUTOMATIC SEPARATION OF MUSIC TRACKS SUPPORT VECTOR MACHINE (SVM)

Wyniki wyszukiwania dla: MUSIC INFORMATION RETRIEVAL (MIR) AUTOMATIC MUSIC GENRE CLASSIFICATION AUTOMATIC SEPARATION OF MUSIC TRACKS SUPPORT VECTOR MACHINE (SVM)

  • Smart Virtual Bass Synthesis Algorithm Based on Music Genre Classification

    Publikacja

    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...

  • 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_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_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...

  • Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres

    The purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....

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  • Speech Analytics Based on Machine Learning

    In this chapter, the process of speech data preparation for machine learning is discussed in detail. Examples of speech analytics methods applied to phonemes and allophones are shown. Further, an approach to automatic phoneme recognition involving optimized parametrization and a classifier belonging to machine learning algorithms is discussed. Feature vectors are built on the basis of descriptors coming from the music information...

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  • Separability Assessment of Selected Types of Vehicle-Associated Noise

    Music Information Retrieval (MIR) area as well as development of speech and environmental information recognition techniques brought various tools in-tended for recognizing low-level features of acoustic signals based on a set of calculated parameters. In this study, the MIRtoolbox MATLAB tool, designed for music parameter extraction, is used to obtain a vector of parameters to check whether they are suitable for separation of...

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  • Sound engineering as our commitment to its creators in Poland

    Sound engineering is an interdisciplinary and rapidly expanding domain. It covers many aspects, such as sound perception, studio and sound mastering technology, music information retrieval including content-based search systems and automatic music transcription frameworks, sound synthesis, sound restoration, electroacoustics, and other ones constituting multimedia technology. Moreover, machine learning methods applied to the topics...

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  • 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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  • Comparison of Lithuanian and Polish Consonant Phonemes Based on Acoustic Analysis – Preliminary Results

    Publikacja

    - Archives of Acoustics - Rok 2019

    The goal of this research is to find a set of acoustic parameters that are related to differences between Polish and Lithuanian language consonants. In order to identify these differences, an acoustic analysis is performed, and the phoneme sounds are described as the vectors of acoustic parameters. Parameters known from the speech domain as well as those from the music information retrieval area are employed. These parameters are...

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