Maximum likelihood estimation of the late reverberant power spectral density in noisy environments

2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2015

Volumn , Issue , 2015, Pages

  Schwartz, Ofer ^a   Braun, Sebastian ^b   Gannot, Sharon ^a   Habets, Emanuel A P ^b  

^a BAR ILAN UNIVERSITY   (Israel)

^b UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

Author keywords

Closed form solutions; Maximum likelihood estimation; Microphones; Noise measurement; Reverberation; Speech

Indexed keywords

ACOUSTIC NOISE; AUDIO ACOUSTICS; AUDIO SIGNAL PROCESSING; ESTIMATION; MAXIMUM LIKELIHOOD; MICROPHONES; NEWTON-RAPHSON METHOD; POWER SPECTRAL DENSITY; REVERBERATION; SIGNAL PROCESSING; SPECTRAL DENSITY; SPEECH;

CLOSED FORM SOLUTIONS; MAXIMUM LIKELIHOOD ESTIMATOR; MAXIMUM LIKELIHOOD ESTIMATORS (MLE); MULTI-MICROPHONE NOISE REDUCTION; NOISE MEASUREMENTS; NOISY ENVIRONMENT; PERFORMANCE MEASURE; POWER SPECTRAL DENSITIES (PSD);

MAXIMUM LIKELIHOOD ESTIMATION;

EID: 84960903353     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WASPAA.2015.7336919     Document Type: Conference Paper

References (11)

1. P. A. Naylor and N. D. Gaubitch, Speech dereverberation. Springer Science &Business Media, 2010.
2. O. Schwartz, S. Gannot, and E. A. P. Habets, "Multimicrophone speech dereverberation and noise reduction using relative early transfer functions," IEEE/ACM Transactions on Audio, Speech, and Language Processing, pp. 240-251, Feb. 2015.
3. S. Braun and E. A. P. Habets, "Dereverberation in noisy environments using reference signals and a maximum likelihood estimator," in Proceedings of the 21st European Signal Processing Conference (EUSIPCO), 2013, pp. 1-5.
4. U. Kjems and J. Jensen, "Maximum likelihood based noise covariance matrix estimation for multi-microphone speech enhancement," in Proceedings of the 20th European Signal Processing Conference (EUSIPCO), 2012, pp. 295-299.
5. A. Schwarz, K. Reindl, and W. Kellermann, "A two-channel reverberation suppression scheme based on blind signal separation and Wiener filtering," in Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on. IEEE, 2012, pp. 113-116.
6. A. Kuklasinski, S. Doclo, S. H. Jensen, and J. Jensen, "Maximum likelihood based multi-channel isotropic reverberation reduction for hearing aids," in Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), 2014, pp. 61-65.
7. K. Lebart, J. Boucher, and P. Denbigh, "A new method based on spectral subtraction for speech dereverberation," Acta Acustica united with Acustica, vol. 87, pp. 359-366, 2001.
8. E. A. P. Habets, S. Gannot, and I. Cohen, "Late reverberant spectral variance estimation based on a statistical model," IEEE Signal Processing Letters, vol. 16, no. 9, pp. 770-773, Sep. 2009.
9. S. Boyd and L. Vandenberghe, Convex optimization. Cambridge university press, 2004.
10. O. Thiergart, G. Del Galdo, and E. A. P. Habets, "On the spatial coherence in mixed sound fields and its application to signal-to-diffuse ratio estimation," J. Acoust. Soc. Am., vol. 132, no. 4, pp. 2337-2346, 2012.
11. ITU-T, "Perceptual evaluation of speech quality (PESQ), an objective method for end-to-end speech quality assessment of narrowband telephone networks and speech codecs," Feb. 2001.