Removal of noise from speech using the dual EKF algorithm
نویسندگان
چکیده
Noise reduction for speech signals has applications ranging from speech enhancement for cellular communications, to front ends for speech recognition systems. A neural network based time-domain method called Dual Extended Kalman Filtering (Dual EKF) is presented for removing nonstationary and colored noise from speech. This paperdescribes the algorithm and provides a set of experimental results.
منابع مشابه
A New Shuffled Sub-swarm Particle Swarm Optimization Algorithm for Speech Enhancement
In this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. The new method is a hybrid optimization algorithm, which employs the combination of the conventional θ-PSO and the shuffled sub-swarms particle optimization (SSPSO) technique. It is known that the θ-PSO algorithm has better optimization performance than standard PSO al...
متن کاملTuning of Extended Kalman Filter using Self-adaptive Differential Evolution Algorithm for Sensorless Permanent Magnet Synchronous Motor Drive
In this paper, a novel method based on a combination of Extended Kalman Filter (EKF) with Self-adaptive Differential Evolution (SaDE) algorithm to estimate rotor position, speed and machine states for a Permanent Magnet Synchronous Motor (PMSM) is proposed. In the proposed method, as a first step SaDE algorithm is used to tune the noise covariance matrices of state noise and measurement noise i...
متن کاملNeural Dual Extended Kalman Filtering: Applications in Speech Enhancement and Monaural Blind Signal Separation
The removal of noise from speech signals has applications ranging from speech enhancement for cellular communications, to front ends for speech recognition systems. A nonlinear time-domain method called dual extended Kalman filtering (DEKF) is presented for removing nonstationary and colored noise from speech. We further generalize the algorithm to perform the blind separation of two speech sig...
متن کاملA New Algorithm for Voice Activity Detection Based on Wavelet Packets (RESEARCH NOTE)
Speech constitutes much of the communicated information; most other perceived audio signals do not carry nearly as much information. Indeed, much of the non-speech signals maybe classified as ‘noise’ in human communication. The process of separating conversational speech and noise is termed voice activity detection (VAD). This paper describes a new approach to VAD which is based on the Wavelet ...
متن کاملSpeech Enhancement using Laplacian Mixture Model under Signal Presence Uncertainty
In this paper an estimator for speech enhancement based on Laplacian Mixture Model has been proposed. The proposed method, estimates the complex DFT coefficients of clean speech from noisy speech using the MMSE estimator, when the clean speech DFT coefficients are supposed mixture of Laplacians and the DFT coefficients of noise are assumed zero-mean Gaussian distribution. Furthermore, the MMS...
متن کامل