Wyszukiwarka
Wyniki wyszukiwania dla: MUSICAL INSTRUMENT SIGNALS STIMULI
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Loudness Scaling Test Based on Categorical Perception
PublikacjaThe main goal of this research study is focused on creating a method for loudness scaling based on categorical perception. Its main features, such as: way of testing, calibration procedure for securing reliable results, employing natural test stimuli, etc., are described in the paper and assessed against a procedure that uses 1/2-octave bands of noise (LGOB) for the loudness growth estimation. The Mann-Whitney U-test is employed...
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Nonlinear Modeling in Time Domain Numerical Analysis of Stringed Instrument Dynamics
PublikacjaMusical instruments are very various in terms of sound quality with their timbre shaped by materials and geometry. Materials' impact is commonly treated as dominant one by musicians, while it is unclear whether it is true or not. The research proposed in the study focuses on determining influence of both these factors on sound quality based on their impact on harmonic composition. Numerical approach has been chosen to allowed independent...
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Real and Virtual Instruments in Machine Learning – Training and Comparison of Classification Results
PublikacjaThe 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...
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Identyfikacja instrumentu muzycznego z nagrania fonicznego za pomocą sztucznych sieci neuronowych
PublikacjaCelem 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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Exploring Neural Networks for Musical Instrument Identification in Polyphonic Audio
PublikacjaThe 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 Instrument Identification Using Deep Learning Approach
PublikacjaThe 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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Musical Instrument Separation Applied to Music Genre Classification . Separacja instrumentów muzycznych w zastosowaniu do rozpoznawania gatunków muzycznych
PublikacjaThis 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...
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Role of various parametres in automatic classification of musical instrument sound.
PublikacjaArtkuł dotyczy problemu automatycznej klasyfikacji dźwięków instrumentów muzycznych, w tym głównie wpływu indywidualnych parametrów na proces automatycznego rozpoznawania instrumentów. Parametryzacja wykorzystuje wdirmo Fourierowskie i analizę czasową dźwięków do formowania 14 i 62-parametrowych wektorów cech dystynktywnych. Autorzy porównują jakość rozpoznawania i rozróźnialność instrumentów. Przy ocenach tego typu stosowano drzewa...
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Rough set based automatic classification of musical instrument sound
PublikacjaReferat dotyczy problemu automatycznego rozpoznawania instrumentów muzycznych rozwiązywanego z zastosowaniem, inteligentnych algorytmów decyzyjnych. Wnioski zawarte w referacie dotyczą reprezentacji sygnałów muzycznych, która jest przydatna w procesie automatycznej klasyfikacji instrumentów.
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Soft computing based automatic recognition of musical instrument classes.
PublikacjaW 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.
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Journal of the American Musical Instrument Society
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Musical Instrument Classification and Duet Analysis Employing Music Information Retrieval Techniques.
PublikacjaArtykuł przedstawia w sposób przeglądowy prace Katedry Systemów Multimedialnych Politechniki Gdańskiej związane z wyszukiwaniem informacji muzycznej, a w szczególności z klasyfikacją dźwięków instrumentów muzycznych. W opisywanych eksperymentach wykorzystano sztuczne sieci neuronowe.
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Musical Instrument Tagging Using Data Augmentation and Effective Noisy Data Processing
PublikacjaDeveloping 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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Musical instrument sound separation methods supported by artificial nueural network decision system
PublikacjaRozprawa doktorska (27 czerwica 2006).Celem prowadzonych prac badawczych było opracowanie algorytmów separacji dźwięków instrumentów muzycznych. Dodatkowo dobrano zestaw parametrów tak aby możliwe było wytrenowanie sztucznej sieci neuronowej w celu automatycznego rozpoznawania odseparowanych sygnałów. Zaproponowano również aby algorytm decyzyjny odpowiedzialny za klasyfikacje dźwięków pełnił funkcję automatycznej metody oceny algorytmów...
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Цифровой анализ сигналов речи как инструмент сравнительного языкознания [A digital analysis of speech signals as an instrument in comparative linguistics]
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Automatic music genre classification based on musical instrument track separation / Automatyczna klasyfikacja gatunku muzycznego wykorzystująca algorytm separacji dźwięku instrumentó muzycznych
PublikacjaThe 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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''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.
PublikacjaW 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.
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SYNAT_MUSIC_GENRE_FV_173
Dane BadawczeThis 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...
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Decomposition of duet instrument sounds. W: [CD-ROM] International Sympo-sium of Musical Acoustics. ISMA MEXICO CITY. Mexico City, 9-13 December 2002. Mexico City: Escuela Nacional de Musica UNAM**2002, 10 s. 4 rys. 2 tab. bibliogr. 15 poz. Dekompozycja duetów muzycznych.
PublikacjaW referacie zaprezentowany został algorytm separacji nagrań duetów muzycz-nych. Metoda separacji oparta została na algorytmie FED, przy pomocy któregomożliwa jest ekstrakcja części harmonicznych sygnałów. Ponadto wykorzystanyzostał algorytm estymacji częstotliwości podstawowej oparty na korelacjiskrośnej, w celu estymacji częstotliwości dekomponowanych harmonicznych.
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SYNAT_PCA_48
Dane BadawczeThere 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...
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SYNAT_PCA_11
Dane BadawczeThe 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...
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SYNAT Music Genre Parameters PCA 19
Dane BadawczeThe 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...
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Emotion Recognition Using Physiological Signals
PublikacjaIn this paper the problem of emotion recognition using physiological signals is presented. Firstly the problems with acquisition of physiological signals related to specific human emotions are described. It is not a trivial problem to elicit real emotions and to choose stimuli that always, and for all people, elicit the same emotion. Also different kinds of physiological signals for emotion recognition are considered. A set of...
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Intracranial electrophysiological recordings from the human brain during memory tasks with pupillometry
PublikacjaData comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N=10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task...
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A Comparison of STI Measured by Direct and Indirect Methods for Interiors Coupled with Sound Reinforcement Systems
PublikacjaThis paper presents a comparison of STI (Speech Transmission Index) coefficient measurement results carried out by direct and indirect methods. First, acoustic parameters important in the context of public address and sound reinforcement systems are recalled. A measurement methodology is presented that employs various test signals to determine impulse responses. The process of evaluating sound system performance, signals enabling...
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Selected results of measurements carried out in a ship power station with two generators working in parallel with the use of the NI PXIe-1062Q based measurement system
Dane BadawczeThe presented dataset is part of research focusing on the assessment of metrological properties of the instrument, Estimator/Analyzer (A/E v.2), developed and made at the Faculty of Electrical Engineering, Department of Marine Electrical Power Engineering, of Gdynia Maritime University. The attached data set contains the results of measurements made...
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Using concentrated spectrogram for analysis of audio acoustic signals
PublikacjaThe paper presents results of time-frequency analysis of audio acoustic signals using the method of Concentrated Spectrograph also known as ''Cross-spectral method'' or ''Reassignment method''. Presented algorithm involves signal's local group delay and channelized instantaneous frequency to relevantly redistribute all Short-time Fourier transform lines in time-frequency plain. The main intention of the paper is to compare various...
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Using A Particular Sampling Method for Impedance Measurement
PublikacjaThe paper presents an impedance measurement method using a particular sampling method which is an alternative to DFT calculation. The method uses a sine excitation signal and sampling response signals proportional to current flowing through and voltage across the measured impedance. The object impedance is calculated without using Fourier transform. The method was first evaluated in MATLAB by means of simulation. The method was...
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Dynamic Bayesian Networks for Symbolic Polyphonic Pitch Modeling
PublikacjaSymbolic pitch modeling is a way of incorporating knowledge about relations between pitches into the process of an- alyzing musical information or signals. In this paper, we propose a family of probabilistic symbolic polyphonic pitch models, which account for both the “horizontal” and the “vertical” pitch struc- ture. These models are formulated as linear or log-linear interpo- lations of up to fi ve sub-models, each of which is...
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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublikacjaMusic 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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Audio Content and Crowdsourcing: A Subjective Quality Evaluation of Radio Programs Streamed Online
PublikacjaRadio 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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In uence of Low-Level Features Extracted from Rhythmic and Harmonic Sections on Music Genre Classi cation
PublikacjaWe 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...
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Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review
PublikacjaThe automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities...
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Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
PublikacjaBackground A lack of communication with people suffering from acquired brain injuries may lead to drawing erroneous conclusions regarding the diagnosis or therapy of patients. Information technology and neuroscience make it possible to enhance the diagnostic and rehabilitation process of patients with traumatic brain injury or post-hypoxia. In this paper, we present a new method for evaluation possibility of communication and the...
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Music Information Retrieval – Soft Computing versus Statistics . Wyszukiwanie informacji muzycznej - algorytmy uczące versus metody statystyczne
PublikacjaMusic 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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Wavelet transform analysis to assess oscillations in pial artery pulsation at the human cardiac frequency
PublikacjaPial artery adjustments to changes in blood pressure (BP)may last only seconds in humans. Using a novelmethod called near-infrared transillumination backscattering sounding (NIR-T/BSS) that allows for the non-invasive measurement of pial artery pulsation (cc-TQ) in humans, we aimed to assess the relationship between spontaneous oscillations in BP and cc-TQ at frequencies between 0.5 Hz and 5 Hz. We hypothesized that analysis of...
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Monitoring of Caged Bluefin Tuna Reactions to Ship and Offshore Wind Farm Operational Noises
PublikacjaUnderwater noise has been identified as a relevant pollution affecting marine ecosystems in different ways. Despite the numerous studies performed over the last few decades regarding the adverse effect of underwater noise on marine life, a lack of knowledge and methodological procedures still exists, and results are often tentative or qualitative. A monitoring methodology for the behavioral response of bluefin tuna (Thunnus thynnus)...
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In vivo imaging of the human eye using a two-photon excited fluorescence scanning laser ophthalmoscope
PublikacjaBACKGROUND. Noninvasive assessment of metabolic processes that sustain regeneration of human retinal visual pigments (visual cycle) is essential to improve ophthalmic diagnostics and to accelerate development of new treatments to counter retinal diseases. Fluorescent vitamin A derivatives, which are the chemical intermediates of these processes, are highly sensitive to UV light; thus, safe analyses of these processes in humans...