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Audio Source Separation in a Musical Context

  • Bryan Pardo
  • Zafar Rafii
  • Zhiyao Duan
Part of the Springer Handbooks book series (SHB)

Abstract

When musical instruments are recorded in isolation, modern editing and mixing tools allow correction of small errors without requiring a group to re-record an entire passage. Isolated recording also allows rebalancing of levels between musicians without re-recording and application of audio effects to individual instruments. Many of these techniques require (nearly) isolated instrumental recordings to work. Unfortunately, there are many recording situations (e. g., a stereo recording of a 10-piece ensemble) where there are many more instruments than there are microphones, making many editing or remixing tasks difficult or impossible.

Audio source separation is the process of extracting individual sound sources (e. g., a single flute) from a mixture of sounds (e. g., a recording of a concert band using a single microphone). Effective source separation would allow application of editing and remixing techniques to existing recordings with multiple instruments on a single track.

In this chapter we will focus on a pair of source separation approaches designed to work with music audio. The first seeks the repeated elements in the musical scene and separates the repeating from the nonrepeating. The second looks for melodic elements, pitch tracking and streaming the audio into separate elements. Finally, we consider informing source separation with information from the musical score.

BPM

beats per minute

ICA

independent component analysis

MAP

maximum a posteriori

MFCC

Mel-frequency cepstral coefficient

MIDI

musical instrument digital interface

MIS

University of Iowa musical instrument samples

MMSE

minimum mean square error

MPE

multipitch estimation

NMF

nonnegative matrix factorization

NTF

nonnegative tensor factorization

PLCA

probabilistic latent component analysis

REPET

repeating pattern extraction technique

RPCA

robust principal component analysis

STFT

short-term Fourier transform/short-time Fourier transform

UDC

uniform discrete cepstrum

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Copyright information

© Springer-Verlag Berlin Heidelberg 2018

Authors and Affiliations

  • Bryan Pardo
    • 1
  • Zafar Rafii
    • 2
  • Zhiyao Duan
    • 3
  1. 1.Ford Engineering Design CenterNorthwestern UniversityEvanstonUSA
  2. 2.GracenoteEmeryvilleUSA
  3. 3.Dept. of Electrical and Computer EngineeringUniversity of RochesterRochesterUSA

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