Musical note onset detection based on a spectral sparsity measure

Abstract

If music is the language of the universe, musical note onsets may be the syllables for this language. Not only do note onsets define the temporal pattern of a musical piece, but their time-frequency characteristics also contain rich information about the identity of the musical instrument producing the notes. Note onset detection (NOD) is the basic component for many music information retrieval tasks and has attracted significant interest in audio signal processing research. In this paper, we propose an NOD method based on a novel feature coined as Normalized Identification of Note Onset based on Spectral Sparsity (NINOS2). The NINOS2 feature can be thought of as a spectral sparsity measure, aiming to exploit the difference in spectral sparsity between the different parts of a musical note. This spectral structure is revealed when focusing on low-magnitude spectral components that are traditionally filtered out when computing note onset features. We present an extensive set of NOD simulation results covering a wide range of instruments, playing styles, and mixing options. The proposed algorithm consistently outperforms the baseline Logarithmic Spectral Flux (LSF) feature for the most difficult group of instruments which are the sustained-strings instruments. It also shows better performance for challenging scenarios including polyphonic music and vibrato performances.

Deteksi Onset Gamelan Bebasis DWPT dan BLSTM

“…Onset memiliki peranan penting dalam perspektif warna musik (timbre). Hal tersebut membuat membuat pendeteksian onset secara otomatis berkembang dalam berbagai bidang penelitian seperti pendengaran mesin, pemrosesan music dan music information retrieva [1]. Menurut Stasiak onset detection merupakan atribut penting yang dimiliki oleh sistem intelegensi sebagai tahapan fundamental dasar untuk analisis audio, ekstraksi fitur, deskripsi, sehingga akhirnya memberikan suatu informasi yang komprehensif [2].…”

“…Deteksi musik onset memiliki kegunaan yang luas untuk membangun berbagai macam aplikasi seperti analisi tempo dan beat tracking, transkripsi music otomatis [3], identifikasi instrument, pergantian harmonic, dan generator metadata untuk mebangun system rekomendasi khusus music pada mesin pencarian [1]. Karena kegunaan tersebut, penelitian tentang deteksi onset menarik minak banyak peneliti dari berbagai bidamg.…”