24 research outputs found
Adaptive Variable Degree-k Zero-Trees for Re-Encoding of Perceptually Quantized Wavelet-Packet Transformed Audio and High Quality Speech
A fast, efficient and scalable algorithm is proposed, in this paper, for
re-encoding of perceptually quantized wavelet-packet transform (WPT)
coefficients of audio and high quality speech and is called "adaptive variable
degree-k zero-trees" (AVDZ). The quantization process is carried out by taking
into account some basic perceptual considerations, and achieves good subjective
quality with low complexity. The performance of the proposed AVDZ algorithm is
compared with two other zero-tree-based schemes comprising: 1- Embedded
Zero-tree Wavelet (EZW) and 2- The set partitioning in hierarchical trees
(SPIHT). Since EZW and SPIHT are designed for image compression, some
modifications are incorporated in these schemes for their better matching to
audio signals. It is shown that the proposed modifications can improve their
performance by about 15-25%. Furthermore, it is concluded that the proposed
AVDZ algorithm outperforms these modified versions in terms of both output
average bit-rates and computation times.Comment: 30 pages (Double space), 15 figures, 5 tables, ISRN Signal Processing
(in Press
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 equations whose solutions lead to the first estimates of speech and noise power spectra. The noise source is also identified and the input SNR estimated in this first step. These first estimates are then refined using approximate but explicit MMSE and MAP estimation formulations. The refined estimates are then used in a Wiener filter to reduce noise and enhance the noisy speech. The proposed schemes show good results. Nevertheless, it is shown that the MAP explicit solution, introduced here for the first time, reduces the computation time to less than one third with a slight higher improvement in SNR and PESQ score and also less distortion in comparison to the MMSE solution