Incorporation of phase information for improved time-dependent instrument recognition

Time-dependent estimation of playing instruments in music recordings is an important preprocessing for several music signal processing algorithms. In this approach, instrument recognition is realized by neural networks with a two-dimensional input of short-time Fourier transform (STFT) magnitudes an...

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Bibliographic Details
Published inTechnisches Messen Vol. 87; no. 1; pp. 62 - 67
Main Authors Schwabe, Markus, Elaiashy, Omar, León, Fernando Puente
Format Journal Article
LanguageEnglish
Published De Gruyter 25.09.2020
Subjects
Instrument recognition
Instrumentenerkennung
modified group delay function
modifizierte Gruppenlaufzeit
neural networks
neuronale Netze
polyphone Musiksignale
polyphonic music signals
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Summary:Time-dependent estimation of playing instruments in music recordings is an important preprocessing for several music signal processing algorithms. In this approach, instrument recognition is realized by neural networks with a two-dimensional input of short-time Fourier transform (STFT) magnitudes and a time-frequency representation based on phase information. The modified group delay (MODGD) function and the product spectrum (PS), which is based on MODGD, are analysed as phase representations. Training and evaluation processes are executed based on the MusicNet dataset. By the incorporation of PS in the input, instrument recognition can be improved about 2% in F1-score.
ISSN:0171-8096
2196-7113
DOI:10.1515/teme-2020-0031