Real time implementation of an adaptive filter for speech enhancement

Author

Creighton, John ; Doraiswami, R.

Author_Institution

Dept. of Electr. & Comput. Eng., New Brunswick Univ., Fredericton, NB, Canada

Volume

4

fYear

2004

Firstpage

2201

Abstract

An adaptive linear prediction filter for speech enhancement is implemented in real time on a PC interfaced to an A/D and D/A converter board. A least means squares (LMS) algorithm is employed to update the filter weights where the learning factor is adaptively adjusted to provide faster convergence. The prediction horizon is chosen to be larger than the correlation length of the noise, thereby not restricting the noise to be white. The voice activity and noise segment of the speech waveform are detected by using the energy of the adaptive filter output. This is used to attenuate the noise-only portion. The proposed scheme is evaluated on number of speech samples.

Keywords

adaptive filters; adaptive signal processing; convergence; correlation methods; least mean squares methods; linear predictive coding; noise; speech enhancement; A/D and D/A converter board interfaced PC; LMS algorithm; adaptive filter output energy; adaptive linear prediction filter; adaptively adjusted learning factor; convergence; filter weights; least means squares algorithm; noise correlation length; noise-only portion attenuation; prediction horizon; real time PC implementation; real time implementation; speech enhancement; speech samples; speech waveform noise segment; voice activity; Adaptive filters; Algorithm design and analysis; Computer interfaces; Finite impulse response filter; Iterative algorithms; Least squares approximation; Niobium; Nonlinear filters; Robustness; Speech enhancement;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2004. Canadian Conference on

ISSN

0840-7789

Print_ISBN

0-7803-8253-6

Type

conf

DOI

10.1109/CCECE.2004.1347681

Filename

1347681