Julia is a high-level dynamic programming language for technical computing characterized by its concise syntax and high performance. This paper reviews Julia's features that are useful for audio signal processing, and introduces JuliaAudio and MusicProcessing.jl, which provide a set of Julia packages for basic I/O and transformations of audio data as well as various feature extraction methods for music information retrieval tasks. We quantitatively evaluate the package in terms of its performance relative to existing audio feature extraction libraries. We argue that using Julia for music and audio processing brings a number of benefits, including its high performance in numerical computations, the ease of development coming from Julia's conciseness and versatility, and its scalability for distributed computing.

Authors: Kim, Jong Wook; Russell, Spencer; Bello, Juan
Affiliations: New York University, New York, NY, USA; Massachusetts Institute of Technology, Cambridge, MA, USA(See document for exact affiliation information.)
AES Conference: 2017 AES International Conference on Semantic Audio (June 2017)
Paper Number: P1-6
Publication Date: June 13, 2017 Import into BibTeX
Subject: Semantic Audio
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=18769

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:   /conf/2017/semantic/semantic_audio_2017_paper_36.pdf

Start a discussion about this paper!