Joint High-Resolution Fundamental Frequency and Order Estimation

Mads G. Christensen; Andreas Jakobsson; Sören Holdt Jensen

doi:10.1109/TASL.2007.899267

Joint High-Resolution Fundamental Frequency and Order Estimation

Mads G. Christensen, Andreas Jakobsson, Sören Holdt Jensen

Karlstad University

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, we present a novel method for joint estimation of the fundamental frequency and order of a set of harmonically related sinusoids based on the MUltiple SIgnal Classification (MUSIC) estimation criterion. The presented method, termed HMUSIC, is shown to have an efficient implementation using fast Fourier transforms (FFTs). Furthermore, refined estimates can be obtained using a gradient-based method. Illustrative examples of the application of the algorithm to real-life speech and audio signals are given, and the statistical performance of the estimator is evaluated using synthetic signals, demonstrating its good statistical properties.

Original language	English
Pages (from-to)	1635-1644
Journal	IEEE Transactions on Audio, Speech, and Language Processing
Volume	15
Issue number	5
DOIs	https://doi.org/10.1109/TASL.2007.899267
Publication status	Published - 2007
Externally published	Yes

Subject classification (UKÄ)

Probability Theory and Statistics

Free keywords

estimation
frequency estimation
fundamental frequency estimation
MUltiple SIgnal Classification (MUSIC)
pitch estimation
subspace methods
PARAMETER-ESTIMATION
SINUSOIDAL SIGNALS
AUDIO SIGNALS
MUSIC
MODEL
DECOMPOSITION
SELECTION

Access to Document

10.1109/TASL.2007.899267

http://ieeexplore.ieee.org/iel5/10376/4244504/04244509.pdf?tp=&arnumber=4244509&isnumber=4244504

Cite this

@article{b4661ce4a33444c78805f5f46c7fe5d7,

title = "Joint High-Resolution Fundamental Frequency and Order Estimation",

abstract = "In this paper, we present a novel method for joint estimation of the fundamental frequency and order of a set of harmonically related sinusoids based on the MUltiple SIgnal Classification (MUSIC) estimation criterion. The presented method, termed HMUSIC, is shown to have an efficient implementation using fast Fourier transforms (FFTs). Furthermore, refined estimates can be obtained using a gradient-based method. Illustrative examples of the application of the algorithm to real-life speech and audio signals are given, and the statistical performance of the estimator is evaluated using synthetic signals, demonstrating its good statistical properties.",

keywords = "estimation, frequency estimation, fundamental frequency estimation, MUltiple SIgnal Classification (MUSIC), pitch estimation, subspace methods, PARAMETER-ESTIMATION, SINUSOIDAL SIGNALS, AUDIO SIGNALS, MUSIC, MODEL, DECOMPOSITION, SELECTION",

author = "Christensen, {Mads G.} and Andreas Jakobsson and Jensen, {S{\"o}ren Holdt}",

year = "2007",

doi = "10.1109/TASL.2007.899267",

language = "English",

volume = "15",

pages = "1635--1644",

journal = "IEEE Transactions on Audio, Speech, and Language Processing",

issn = "1558-7924",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

number = "5",

}

TY - JOUR

T1 - Joint High-Resolution Fundamental Frequency and Order Estimation

AU - Christensen, Mads G.

AU - Jakobsson, Andreas

AU - Jensen, Sören Holdt

PY - 2007

Y1 - 2007

N2 - In this paper, we present a novel method for joint estimation of the fundamental frequency and order of a set of harmonically related sinusoids based on the MUltiple SIgnal Classification (MUSIC) estimation criterion. The presented method, termed HMUSIC, is shown to have an efficient implementation using fast Fourier transforms (FFTs). Furthermore, refined estimates can be obtained using a gradient-based method. Illustrative examples of the application of the algorithm to real-life speech and audio signals are given, and the statistical performance of the estimator is evaluated using synthetic signals, demonstrating its good statistical properties.

AB - In this paper, we present a novel method for joint estimation of the fundamental frequency and order of a set of harmonically related sinusoids based on the MUltiple SIgnal Classification (MUSIC) estimation criterion. The presented method, termed HMUSIC, is shown to have an efficient implementation using fast Fourier transforms (FFTs). Furthermore, refined estimates can be obtained using a gradient-based method. Illustrative examples of the application of the algorithm to real-life speech and audio signals are given, and the statistical performance of the estimator is evaluated using synthetic signals, demonstrating its good statistical properties.

KW - estimation

KW - frequency estimation

KW - fundamental frequency estimation

KW - MUltiple SIgnal Classification (MUSIC)

KW - pitch estimation

KW - subspace methods

KW - PARAMETER-ESTIMATION

KW - SINUSOIDAL SIGNALS

KW - AUDIO SIGNALS

KW - MUSIC

KW - MODEL

KW - DECOMPOSITION

KW - SELECTION

U2 - 10.1109/TASL.2007.899267

DO - 10.1109/TASL.2007.899267

M3 - Article

SN - 1558-7924

VL - 15

SP - 1635

EP - 1644

JO - IEEE Transactions on Audio, Speech, and Language Processing

JF - IEEE Transactions on Audio, Speech, and Language Processing

IS - 5

ER -

Joint High-Resolution Fundamental Frequency and Order Estimation

Abstract

Subject classification (UKÄ)

Free keywords

Access to Document

Fingerprint

Cite this