Particle methods for Bayesian modeling and enhancement of speech signals

IEEE Transactions on Speech and Audio Processing

Volumn 10, Issue 3, 2002, Pages 173-185

  Vermaak, Jaco ^a   Andrieu, Christophe ^b   Doucet, Arnaud ^c   Godsill, Simon John ^d  

^a MICROSOFT RESEARCH   (United Kingdom)

^b UNIVERSITY OF BRISTOL   (United Kingdom)

^c UNIVERSITY OF MELBOURNE   (Australia)

^d UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

Particle filters; Speech enhancement; Time varying autoregressive models

Indexed keywords

COMPUTER SIMULATION; GAUSSIAN NOISE (ELECTRONIC); KALMAN FILTERING; MARKOV PROCESSES; MONTE CARLO METHODS; PROBLEM SOLVING; STATISTICAL METHODS; WHITE NOISE;

SPEECH SIGNALS;

SPEECH PROCESSING;

EID: 0036508204     PISSN: 10636676     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSA.2002.1001982     Document Type: Article

References (30)

1. Nonlinear Bayesian estimation using Gaussian sum approximation
2. Bayesian estimation of an autoregressive model using Markov chain Monte Carlo
3. 2
4. Digital synthesis of nonlinear filters
5. Discrete filtering using branching and interacting particle systems
6. Maximum a posteriori estimation of time-varying ARMA processes from noisy observations
7. On sequential Monte Carlo sampling methods for Bayesian filtering
8. Iterative and sequential Kalman filter-based speech enhancement algorithms
9. Diagnostics for time series analysis
10. Novel approach to nonlinear/non-Gaussian Bayesian state estimation
11. Time-dependent ARMA modeling of nonstationary signals
12. Time-varying parametric modeling of speech
13. Monte Carlo techniques to estimate the conditional expectation in multi-stage nonlinear filtering
14. Stochastic volatility: Likelihood inference and comparison with ARCH models
15. Monte Carlo filter and smoother for non-Gaussian nonlinear state space models
16. Sequential imputations and Bayesian missing data problems
17. Enhancement and bandwidth compression of noisy speech
18. Linear estimation of nonstationary signals
19. Blind deconvolution via sequential imputation
20. Sequential Monte Carlo methods for dynamic systems
21. On a measure of lack of fit in time series models
22. Linear prediction: A tutorial review
23. Remarks on a multivariate transformation