A new approach to speech enhancement by a microphone array using EM and mixture models
نویسندگان
چکیده
Speech enhancement and recognition in noisy, reverberant conditions is a challenging open problem. We present a new approach to this problem, which is developed in the framework of probabilistic modeling. Our approach incorporates information about the statistical structure of speech signals using a speech model, which is pre-trained on a large dataset of clean speech. The speech model is a component in a larger model describing the observed sensor signals. That model is parametrized by the coefficients of the reverberation filters and the spectra of the sensor noise. We develop an EM algorithm that estimates those parameters from data and constructs a Bayes optimal estimator of the original speech signal.
منابع مشابه
Speech Enhancement Using Gaussian Mixture Models, Explicit Bayesian Estimation and Wiener Filtering
Gaussian Mixture Models (GMMs) of power spectral densities of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy speech. No assumption is made on the nature or stationarity of the noise. No voice activity detection (VAD) or any other means is employed to estimate the input SNR. The GMM mean vectors are used to form sets of over-determined system of equatio...
متن کاملشکلدهی وفقی و هوشمند پرتو در آرایههای میکروفونی Ad-hoc با استفاده از خوشهبندی و رتبهبندی میکروفونها
Considering the existence of a many speech degradation factors, speech enhancement has become an important topic in the field of speech processing. Beamforming is one of the well-known methods for improving the speech quality that is conventionally applied using regular (classical) microphone arrays. Due to the restrictions in the regular arrangement of microphones, in recent years there has be...
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 کاملMethods for Noise Cancellation based on the EM Algorithm
Single microphone speech enhancement systems have typically shown limited performance, while multiple microphone systems based on a least-squares error criterion have shown encouraging results in some contexts. In this paper we formulate a new approach to multiple microphone speech enhancement. Specifically, we formulate a maximum likelihood (ML) problem for estimating the parameters needed for...
متن کاملSpeech Enhancement Using a Multidimensional Mixture-Maximum Model
We present a single-microphone speech enhancement algorithm that models the log-spectrum of the noise-free speech signal by a multidimensional Gaussian mixture. The proposed estimator is based on an earlier study which uses the single-dimensional mixture-maximum (MIXMAX) model for the speech signal. The experimental study shows that there is only a marginal difference between the proposed exten...
متن کامل