Coding algorithms for high fidelity audio signals

140 p.This report presents the research work done in the area of perceptual audio coding by using the ISO/MPEG 1 audio coding algorithm as the reference. It discusses the psychoacoustic model used in the conventional audio coding algorithms. It further focuses on the efficient implementation of the bit allocation procedure which forms the main part of the ISO/MPEG audio coding algorithm. The discussion on the development of the encoder employing a simple bit allocation technique is also presented. The performance of this encoder is compared with that of the ISO/MPEG audio encoder in terms of hardware complexity, objective measures as well as subjective quality.RP 58/9

Real time speech enhancement

Investigation on the speech enhancement algorithms in the transform domain and ways to implement them in real time. The strengths and weaknesses of various transforms such as Discrete Fourier Transform, Discrete Cosine Transform, Karhunen Loeve Transform and Wavelet Transform are also discussed

Single channel speech enhancement

In this report, we present our research work on single channel speech enhancement. First, current major speech enhancement algorithms are reviewed and we conclude that the S-MMSE-LSAE algorithm is the best in overall performance among the well known algorithms reported in the existing literature and examined by the authors under most signal-to-noise ratios conditions. Secondly, an enhanced Itakura speech distortion measure is examined in our study. The proposed measure incorporates masking properties of the human auditory system into the original Itakura measure and substantially improves the correlation degree of objective measure with subjective evaluation. Next, an F-norm constrained SVD enhancement algorithm based on the conventional SVD-based algorithms is proposed. The traditional SVD algorithms are usually limited by the use of the fixed order of retained singular values, which are difficult to match diverse corrupted speech signals embedded in various noise environments

Development of a speech analyser/synthesizer for special applications in linguistics

This project on the development of a speech analyzer/synthesiser for special applications in linguistics was proposed for the purpose of developing computer software for the alteration of the prosodic characteristics of speech signals in the English Language.RP 12/8

Partial separation method for solving permutation problem in frequency domain blind source separation of speech signals

This paper addresses the well known permutation problem in frequency domain blind source separation. The proposed method uses correlation between two signals in each DFT bin to solve the permutation problem. One of the signals is partially separated by a time domain blind source separation method and the other is obtained by the frequency domain blind source separation method. Two different ways of configuring the time and frequency domain blocks, i.e., in parallel or cascade, have been studied. The cascaded configuration not only achieves a better separation performance but also reduces the computational cost as compared to the parallel configuration.Accepted versio

Convolution using discrete sine and cosine transforms

In this paper, we derive a relation for the circular convolution operation in the discrete sine and cosine transform domains. The transform coefficients are either symmetric or asymmetric and hence we need to calculate only half of the total coefficients. Since fast algorithms are available for the computation of discrete sine and cosine transforms, the proposed method is an alternative to the discrete Fourier transform method for filtering applications.Accepted versio

An algorithm for mixing matrix estimation in instantaneous blind source separation

Sparsity of signals in the frequency domain is widely used for blind source separation (BSS) when the number of sources is more than the number of mixtures (underdetermined BSS). In this paper we propose a simple algorithm for detection of points in the Time-Frequency (TF) plane of the instantaneous mixtures where only single source contributions occur. Samples at these points in the TF plane can be used for the mixing matrix estimation. The proposed algorithm identifies the single-source points (SSPs) by comparing the absolute directions of the real and imaginary parts of the Fourier transform coefficient vectors of the mixed signals. Finally, the SSPs so obtained are clustered using the hierarchical clustering algorithm for the estimation of the mixing matrix. The proposed idea for the SSP identification is simpler than the previously reported algorithms.Accepted versio