Abstract
Fundamental frequency estimation is an important task in speech and audio analysis. Harmonic model-based methods typically have superior estimation accuracy. However, such methods usually as- sume that the fundamental frequency and amplitudes are station- ary over a short time frame. In this paper, we propose a Kalman filter-based fundamental frequency estimation algorithm using the harmonic model, where the fundamental frequency and amplitudes can be truly nonstationary by modeling their time variations as first- order Markov chains. The Kalman observation equation is derived from the harmonic model and formulated as a compact nonlinear matrix form, which is further used to derive an extended Kalman filter. Detailed and continuous fundamental frequency and ampli- tude estimates for speech, the sustained vowel /a/ and solo musical tones with vibrato are demonstrated.
Originalsprog | Engelsk |
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Titel | 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA 2017) |
Antal sider | 5 |
Udgivelsessted | New Paltz, NY, USA, USA |
Forlag | IEEE Press |
Publikationsdato | 15 okt. 2017 |
Sider | 314-318 |
ISBN (Trykt) | 978-1-5386-1633-8 |
ISBN (Elektronisk) | 978-1-5386-1632-1 |
DOI | |
Status | Udgivet - 15 okt. 2017 |
Begivenhed | 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics - Mohonk Mountain House, New Paltz, USA Varighed: 15 okt. 2017 → 18 okt. 2017 http://www.waspaa.com/ |
Workshop
Workshop | 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics |
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Lokation | Mohonk Mountain House |
Land/Område | USA |
By | New Paltz |
Periode | 15/10/2017 → 18/10/2017 |
Internetadresse |
Navn | IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) |
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ISSN | 1947-1629 |