Struktura obiektu

Autor:

Stasiak, Bartłomiej ; Mońko, Jędrzej ; Niewiadomski, Adam

Współtwórca:

Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.

Tytuł:

Note onset detection in musical signals via neural-network-based multi-ODF fusion

Tytuł publikacji grupowej:

AMCS, Volume 26 (2016)

Temat i słowa kluczowe:

note onset detection ; onset detection function ; multi-layer perceptron ; multi-ODF fusion ; NN-based fusion

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

Typ zasobu:

artykuł

DOI:

10.1515/amcs-2016-0014

Strony:

203-213

Źródło:

AMCS, volume 26, number 1 (2016) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego