### Resumé

Originalsprog | Engelsk |
---|---|

Titel | 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |

Antal sider | 4 |

Forlag | IEEE Press |

Publikationsdato | mar. 2012 |

Sider | 4617-4620 |

ISBN (Trykt) | 978-1-4673-0045-2 |

ISBN (Elektronisk) | 978-1-4673-0044-5 |

DOI | |

Status | Udgivet - mar. 2012 |

Begivenhed | IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP - Kyoto, Japan Varighed: 25 mar. 2012 → 30 mar. 2012 |

### Konference

Konference | IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP |
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Land | Japan |

By | Kyoto |

Periode | 25/03/2012 → 30/03/2012 |

Navn | I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings |
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ISSN | 1520-6149 |

### Fingerprint

### Citer dette

*2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)*(s. 4617-4620). IEEE Press. I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings https://doi.org/10.1109/ICASSP.2012.6288947

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*2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).*IEEE Press, I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, s. 4617-4620, IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP, Kyoto, Japan, 25/03/2012. https://doi.org/10.1109/ICASSP.2012.6288947

**An Approximate Bayesian Fundamental Frequency Estimator.** / Nielsen, Jesper Kjær; Christensen, Mads Græsbøll; Jensen, Søren Holdt.

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - An Approximate Bayesian Fundamental Frequency Estimator

AU - Nielsen, Jesper Kjær

AU - Christensen, Mads Græsbøll

AU - Jensen, Søren Holdt

PY - 2012/3

Y1 - 2012/3

N2 - Joint fundamental frequency and model order estimation is an important problem in several applications such as speech and music processing. In this paper, we develop an approximate estimation algorithm of these quantities using Bayesian inference. The inference about the fundamental frequency and the model order is based on a probability model which corresponds to a minimum of prior information. From this probability model, we give the exact posterior distributions on the fundamental frequency and the model order, and we also present analytical approximations of these distributions which lower the computational load of the algorithm. By use of simulations on both a synthetic signal and a speech signal, the algorithm is demonstrated to be more accurate than a state-of-the-art maximum likelihood-based method.

AB - Joint fundamental frequency and model order estimation is an important problem in several applications such as speech and music processing. In this paper, we develop an approximate estimation algorithm of these quantities using Bayesian inference. The inference about the fundamental frequency and the model order is based on a probability model which corresponds to a minimum of prior information. From this probability model, we give the exact posterior distributions on the fundamental frequency and the model order, and we also present analytical approximations of these distributions which lower the computational load of the algorithm. By use of simulations on both a synthetic signal and a speech signal, the algorithm is demonstrated to be more accurate than a state-of-the-art maximum likelihood-based method.

UR - http://www.scopus.com/inward/record.url?scp=84867619223&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2012.6288947

DO - 10.1109/ICASSP.2012.6288947

M3 - Article in proceeding

SN - 978-1-4673-0045-2

T3 - I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings

SP - 4617

EP - 4620

BT - 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

PB - IEEE Press

ER -