Obiekt
Tytuł: Note onset detection in musical signals via neural-network-based multi-ODF fusion
Współtwórca:
Korbicz, Józef - red. ; Uciński, Dariusz - red.
Tytuł publikacji grupowej:
Abstract:
The problem of note onset detection in musical signals is considered. The proposed solution is based on known approaches in which an "onset detection function" is defined on the basis of spectral characteristics of audio data. In our approach, several onset detection functions are used simultaneously to form an input vector for a multi-layer non-linear perceptron, which learns to detect onsets in the training data. This is in contrast to standard methods based on thresholding the onset detection functions with a moving average or a moving median. ; Our approach is also different from most of the current machine-learning-based solutions in that we explicitly use the onset detection functions as an intermediate representation, which may therefore be easily replaced with a different one, e.g., to match the characteristics of a particular audio data source. The results obtained for a database containing annotated onsets for 17 different instruments and ensembles are compared with state-of-the-art solutions.
Wydawca:
Zielona Góra: Uniwersytet Zielonogórski
Identyfikator zasobu:
DOI:
Strony:
Źródło:
AMCS, volume 26, number 1 (2016) ; kliknij tutaj, żeby przejść
Jezyk:
Prawa do dysponowania publikacją:
Biblioteka Uniwersytetu Zielonogórskiego
Kolekcje, do których przypisany jest obiekt:
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Jednostki organizacyjne > Wydział Informatyki, Elektrotechniki i Automatyki
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Typy utworów > Artykuły
- Zielonogórska Biblioteka Cyfrowa > Repozytorium > Czasopisma naukowe i serie wydawnicze UZ > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2016)
Data ostatniej modyfikacji:
2024-05-09
Data dodania obiektu:
2024-05-09
Liczba wyświetleń treści obiektu:
2
Wszystkie dostępne wersje tego obiektu:
https://zbc.uz.zgora.pl/publication/88951
Wyświetl opis w formacie RDF:
Wyświetl opis w formacie OAI-PMH:
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International Journal of Applied Mathematics and Computer Science (AMCS)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26, number 1 (2016)
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- Note onset detection in musical signals via neural-network-based multi-ODF fusion
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26, number 4 (2016)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26, number 1 (2016)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
| Nazwa wydania | Data |
|---|---|
| Note onset detection in musical signals via neural-network-based multi-ODF fusion | 2024-05-09 |
