IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING

MARCH 2010

Lan-Ying Yeh99.04.12

Introduction

Music Information Retrieval (MIR) Singer identification & Vocal-Timbre-

Similarity Feature extraction Influence from other instruments

Related Studies Using a statistically based speaker-

identification method for speech signals in noisy environmentsFirst estimated an accompaniment-only

model from interlude sectionsa vocal-only model by subtract the

accompaniment-only model from the vocal-plus-accompaniment model

Assume singing voice and accompaniment sounds statistically independent Not always satisfied

Estimation have problem

Related Studies

Using vocal separation methodSimilar to their accompaniment sound

reduction method

Did not dealt with interlude sectionsConducted experiments, using only vocal sections

Method Overview

Accompaniment Sound Reduction F0 estimation

PreFEst (Predominant-F0 estimation method)Observed power spectrum in units of centsA band pass filter designed for most melodyObserved pdf of frequency componentsEach observed pdf is generated from weighted-

mixture model of possible tone model Estimate the weighting by EM algorithm (MAP),

regard as F0’s pdfTrack dominant F0

11 cent=

100semi tone

Accompaniment Sound Reduction Harmonic Structure Extraction

Extract the frequency and amplitude of the

l-th overtoneAllow r cent errorSearch local maximum amplitude in an area

Accompaniment Sound Reduction Re-synthesis

Model by sinusoidalQuadratic function approximate changes

in phaseLinear function approximate changes in

amplitude

Accompaniment Sound Reduction Evaluation

To be continued…