Complex Network: A Potential Tool for Uncloaking Tone Quality of Musical Instruments

The paper unwraps the potential application of graph features through complex network analysis in assessing the tone quality of a musical note by analysing the two notes, C and G, at different octaves played by the wind instruments, flute and trumpet, as examples. The musical note sound signals are subjected to fast Fourier transform and wavelet analyses to understand harmonic content and its sustainability. The complex network generated from the temporal data helps in understanding the airflow dynamics through the graph features—edge count, graph density and transitivity. The study reveals that the greater the value of network features, the lesser the overtones present in the musical note, suggesting its application in assessing the musical tone quality or timbre.