Wyniki wyszukiwania dla: SINGING EXPRESSION CLASSIFICATION - MOST Wiedzy

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Wyniki wyszukiwania dla: SINGING EXPRESSION CLASSIFICATION

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Wyniki wyszukiwania dla: SINGING EXPRESSION CLASSIFICATION

  • Automatic classification of singing voice quality

    Publikacja

    - Rok 2005

    W artykule przedstawiono zagadnienia związane z automatyczną klasyfikacją jakości i rodzajów głosów śpiewaczych. Na potrzebę takiej klasyfikacji stworzono bazę głosów śpiewaczych, w której dokonano parametryzacji nagrań samogłosech śpiewanych przez różnych wokalistów (zarówno profesjonalistów jak i amatorów) na różnych wysokościach i z różną głośnością. W celu ograniczenia wymiaru wektora opisu zastosowano statystykę Behrensa Fishera...

  • Ranking Speech Features for Their Usage in Singing Emotion Classification

    Publikacja

    This paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...

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  • Expert system for automatic classification and quality assessment of singing voices

    Publikacja

    - Rok 2006

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  • Expert system for automatic classification and quality assessment of singing voices

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  • Automatic Singing Voice Recognition EmployingNeural Networks and Rough Sets

    Publikacja

    Celem badań jest automatyczne rozpoznawanie głosów śpiewaczych w kategorii rodzaju i jakości technicznej śpiewu. W artykule opisano stworzoną bazę danych głosów, która zawiera próbki głosu śpiewaków profesjonalnych i amatorskich. W dalszej części opisano parametry zdefiniowane w oparciu o zjawiska biomechaniczne w narządzie głosu podczas śpiewania. W oparciu o stworzone macierze parametrów wytrenowano i porównano automatyczne klasyfikatory...

  • Introduction to the special issue on machine learning in acoustics

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

    - Journal of the Acoustical Society of America - Rok 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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  • A system for singing training

    Publikacja

    - Rok 2007

    The system proposed is aimed at the vocal students and persons who want to improve emission of their voices. The goal is not to substituite a singing teacher but to provide a tool for automatic teaching of voice emission basics. In this way singers can develop their vocal skills and improve them. By a visual feedback a student can control and modify vocal tract maximas (resonances) of a chosen vowel to match the resonances of the...

  • System for automatic singing voice recognition

    W artykule przedstawiono system automatycznego rozpoznawania jakości i typu głosu śpiewaczego. Przedstawiono bazę danych oraz zaimplementowane parametry. Algorytmem decyzyjnym jest algorytm sztucznych sieci neuronowych. Wytrenowany system decyzyjny osiąga skuteczność ok. 90% w obydwu kategoriach rozpoznawania. Dodatkowo wykazano przy pomocy metod statystycznych, że wyniki działania systemu automatycznej oceny jakości technicznej...

  • Automatic singing quality recognition employing artificial neural networks

    Publikacja

    Celem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...

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  • Automatic detection and correction of detuned singing system for use with query-by-humming applications

    Publikacja

    - Rok 2008

    The aim of the paper is to present an idea of using the automatic detection and correction of detuned singing as a subsystem in query-by-humming (QBH) applications. The common approach to searching for a requested song basing on the melody retrieved from hummed pattern usually employs the so-called Parsons code or melody contour. In such a case information about sound pitch is discarded. It was thought out that an additional module...

  • Automatic detection and correction of detuned singing system for use with query-by-humming applications

    Publikacja

    The aim of the paper is to present an idea of using the automatic detection and correction of detuned singing as a subsystem in query-by-humming (QBH) applications. The common approach to searching for a requested song basing on the melody retrieved from hummed pattern usually employs the so-called Parsons code or melody contour. In such a case information about sound pitch is discarded. It was thought out that an additional module...

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  • Transcriptomic landscape of blood platelets in healthy donors

    Publikacja
    • A. Supernat
    • M. Popęda
    • K. Pastuszak
    • M. G. Best
    • P. Grešner
    • S. I. ’. Veld
    • B. Siek
    • N. Bednarz-Knoll
    • M. T. Rondina
    • T. Stokowy... i 3 innych

    - Scientific Reports - Rok 2021

    Blood platelet RNA-sequencing is increasingly used among the scientific community. Aberrant platelet transcriptome is common in cancer or cardiovascular disease, but reference data on platelet RNA content in healthy individuals are scarce and merit complex investigation. We sought to explore the dynamics of platelet transcriptome. Datasets from 204 healthy donors were used for the analysis of splice variants, particularly with...

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  • Novel Tools for Comprehensive Functional Analysis of LDLR (Low-Density Lipoprotein Receptor) Variants

    Publikacja
    • J. Jasiecki
    • M. Targońska
    • A. Janaszak-Jasiecka
    • M. Chmara
    • M. Żuk
    • L. Kalinowski
    • K. Waleron
    • B. Wasąg

    - INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES - Rok 2023

    Familial hypercholesterolemia (FH) is an autosomal-dominant disorder caused mainly by substitutions in the low-density lipoprotein receptor (LDLR) gene, leading to an increased risk of premature cardiovascular diseases. Tremendous advances in sequencing techniques have resulted in the discovery of more than 3000 variants of the LDLR gene, but not all of them are clinically relevant. Therefore, functional studies of selected variants...

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  • Physics augmented classification of fNIRS signals

    Publikacja
    • F. Orihuela-Espina
    • M. Rojas-Cisneros
    • S. A. Montero-Hernández
    • J. S. Garcia Salinas
    • B. Cuervo-Soto
    • J. Herrera-Vega

    - Rok 2022

    Background. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...

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  • Seabed classification using multibeam echosounder

    Publikacja

    The method of seabed identification and classification from multibeam sonar echoes is presented. The proposed approach is based on calculation of a set of parameters of an echo envelope, similarly as in seafloor classification using single beam echosounder. These parameters are extracted for each consecutive beam allowing the estimation of their dependence on the seafloor incident angle. The relation between seabed type and calculated...

  • Comparison of selected electroencephalographic signal classification methods

    A variety of methods exists for electroencephalographic (EEG) signals classification. In this paper, we briefly review selected methods developed for such a purpose. First, a short description of the EEG signal characteristics is shown. Then, a comparison between the selected EEG signal classification methods, based on the overview of research studies on this topic, is presented. Examples of methods included in the study are: Artificial...

  • Impact of optimization of ALS point cloud on classification

    Airborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...

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  • A System for Heart Sounds Classification

    The future of quick and efficient disease diagnosis lays in the development of reliable non-invasive methods. As for the cardiac diseases – one of the major causes of death around the globe – a concept of an electronic stethoscope equipped with an automatic heart tone identification system appears to be the best solution. Thanks to the advancement in technology, the quality of phonocardiography signals is no longer an issue. However,...

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  • The Hough transform in the classification process of inland ships

    Publikacja

    This article presents an analysis of the possibilities of using image processing methods for feature extraction that allows kNN classification based on a ship’s image delivered from an on-water video surveillance system. The subject of the analysis is the Hough transform which enables the detection of straight lines in an image. The recognized straight lines and the information about them serve as features in the classification...

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  • Using similar classification tasks in feature extractor learning

    Publikacja

    - Rok 2009

    The article presents and experimentally verify the idea of automatic construction of feature extractors in classification problems. The extractors are created by genetic programming techniques using classification examples taken from other problems then the problem under consideration.