TY - GEN
T1 - MMSE-based speech enhancement using the harmonic model
AU - Stark, Yair
AU - Tabrikian, Joseph
N1 - Funding Information:
The authors are grateful to Dr. D. Pamu, IIT-Guwahati for providing PXRD and FESEM and Dr. V. Sudarsan, BARC, Mumbai for acquiring PL studies.
PY - 2008/12/1
Y1 - 2008/12/1
N2 - Modern speech and audio signal processing applications deal with signals contaminated with high noise level. Thus, the problem of speech and audio enhancement is of great importance in speech and audio signal processing. In this paper, a new method for speech enhancement using the harmonic model for voiced frames is proposed. In this method, the fundamental frequency is estimated via the maximum a-posteriori probability (MAP) tracking, while the harmonic amplitudes are estimated via the minimum-mean-square error (MMSE) estimator, which utilizes prior statistical information of the speech phonemes. The MMSE estimator is implemented using the Monte Carlo method. The performance of the proposed method is evaluated by the perceptual evaluation of speech quality (PESQ) algorithm. It is shown that the method outperforms other speech enhancement methods in low signal-to-noise ratios (SNRs).
AB - Modern speech and audio signal processing applications deal with signals contaminated with high noise level. Thus, the problem of speech and audio enhancement is of great importance in speech and audio signal processing. In this paper, a new method for speech enhancement using the harmonic model for voiced frames is proposed. In this method, the fundamental frequency is estimated via the maximum a-posteriori probability (MAP) tracking, while the harmonic amplitudes are estimated via the minimum-mean-square error (MMSE) estimator, which utilizes prior statistical information of the speech phonemes. The MMSE estimator is implemented using the Monte Carlo method. The performance of the proposed method is evaluated by the perceptual evaluation of speech quality (PESQ) algorithm. It is shown that the method outperforms other speech enhancement methods in low signal-to-noise ratios (SNRs).
KW - Harmonic model
KW - MMSE
KW - Monte Carlo methods
KW - Pitch estimation
KW - Speech enhancement
UR - http://www.scopus.com/inward/record.url?scp=62749155354&partnerID=8YFLogxK
U2 - 10.1109/EEEI.2008.4736608
DO - 10.1109/EEEI.2008.4736608
M3 - Conference contribution
AN - SCOPUS:62749155354
SN - 9781424424825
T3 - IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings
SP - 626
EP - 630
BT - 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008
T2 - 2008 IEEE 25th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2008
Y2 - 3 December 2008 through 5 December 2008
ER -