Multi-pitch estimation
Periodic signals can be decomposed into sets of sinusoids having frequencies that are integer multiples of a fundamental frequency. The problem of finding such fundamental frequencies from noisy observations is important in many speech and audio applications, where it is commonly referred to as pitc...
| Main Author: | |
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| Other Authors: | |
| Format: | Electronic |
| Language: | English |
| Published: |
San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) :
Morgan & Claypool Publishers,
c2009.
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| Series: | Synthesis lectures on speech and audio processing (Online) ;
# 5. |
| Subjects: | |
| Online Access: | Abstract with links to full text |
Table of Contents:
- Fundamentals
- Introduction
- Related work
- Some applications
- Signal models
- Covariance matrix model
- Speech and audio signals
- Other signal models
- Parameter estimation bounds
- Evaluation of pitch estimators
- Statistical methods
- Introduction
- Maximum likelihood estimation
- Noise covariance matrix estimation
- White noise case
- Some maximum a posteriori estimators
- MAP model and order selection
- Fast multi-pitch estimation
- Expectation maximization
- Another related method
- Harmonic fitting
- Some results
- Discussion
- Filtering methods
- Introduction
- Comb filtering
- Filterbank interpretation of NLS
- Optimal filterbank design
- Optimal filter design
- Asymptotic analysis
- Inverse covariance matrix
- Variance and order estimation
- Fast implementation
- Some results
- Discussion
- Subspace methods
- Introduction
- Signal and noise subspace identification
- Subspace properties
- Pre-whitening
- Rank estimation using Eigenvalues
- Angles between subspaces
- Estimation using orthogonality
- Robust estimation
- Estimation using shift-invariance
- Some results
- Discussion
- Amplitude estimation
- Introduction
- Least squares estimation
- Capon- and APES-like amplitude estimates
- Some results and discussion
- The analytic signal
- Bibliography
- About the authors.