TY - GEN
T1 - Source separation, dereverberation and noise reduction using LCMV beamformer and postfilter
AU - Schwartz, Ofer
AU - Braun, Sebastian
AU - Gannot, Sharon
AU - Habets, Emanuël A.P.
N1 - Publisher Copyright: © Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - The problem of source separation, dereverberation and noise reduction using a microphone array is addressed in this paper. The observed speech is modeled by two components, namely the early speech (including the direct path and some early reflections) and the late reverberation. The minimum mean square error (MMSE) estimator of the early speech components of the various speakers is derived, which jointly suppresses the noise and the overall reverberation from all speakers. The overall time-varying level of the reverberation is estimated using two different estimators, an estimator based on a temporal model and an estimator based on a spatial model. The experimental study consists of measured acoustic transfer functions (ATFs) and directional noise with various signal-to-noise ratio levels. The separation, dereverberation and noise reduction performance is examined in terms of perceptual evaluation of speech quality (PESQ) and signal-to-interference plus noise ratio improvement.
AB - The problem of source separation, dereverberation and noise reduction using a microphone array is addressed in this paper. The observed speech is modeled by two components, namely the early speech (including the direct path and some early reflections) and the late reverberation. The minimum mean square error (MMSE) estimator of the early speech components of the various speakers is derived, which jointly suppresses the noise and the overall reverberation from all speakers. The overall time-varying level of the reverberation is estimated using two different estimators, an estimator based on a temporal model and an estimator based on a spatial model. The experimental study consists of measured acoustic transfer functions (ATFs) and directional noise with various signal-to-noise ratio levels. The separation, dereverberation and noise reduction performance is examined in terms of perceptual evaluation of speech quality (PESQ) and signal-to-interference plus noise ratio improvement.
UR - http://www.scopus.com/inward/record.url?scp=85013407941&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-319-53547-0_18
DO - https://doi.org/10.1007/978-3-319-53547-0_18
M3 - منشور من مؤتمر
SN - 9783319535463
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 182
EP - 191
BT - Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Proceedings
A2 - Tichavsky, Petr
A2 - Babaie-Zadeh, Massoud
A2 - Michel, Olivier J.J.
A2 - Thirion-Moreau, Nadege
PB - Springer Verlag
T2 - 13th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2017
Y2 - 21 February 2017 through 23 February 2017
ER -