New Directions in Subband Coding

Two very different subband coders are described. The first is a modified dynamic bit-allocation-subband coder (D-SBC) designed for variable rate coding situations and easily adaptable to noisy channel environments. It can operate at rates as low as 12 kb/s and still give good quality speech. The second coder is a 16-kb/s waveform coder, based on a combination of subband coding and vector quantization (VQ-SBC). The key feature of this coder is its short coding delay, which makes it suitable for real-time communication networks. The speech quality of both coders has been enhanced by adaptive postfiltering. The coders have been implemented on a single AT&T DSP32 signal processo

A Parametric Approach for Efficient Speech Storage, Flexible Synthesis and Voice Conversion

During the past decades, many areas of speech processing have benefited from the vast increases in the available memory sizes and processing power. For example, speech recognizers can be trained with enormous speech databases and high-quality speech synthesizers can generate new speech sentences by concatenating speech units retrieved from a large inventory of speech data. However, even in today's world of ever-increasing memory sizes and computational resources, there are still lots of embedded application scenarios for speech processing techniques where the memory capacities and the processor speeds are very limited. Thus, there is still a clear demand for solutions that can operate with limited resources, e.g., on low-end mobile devices. This thesis introduces a new segmental parametric speech codec referred to as the VLBR codec. The novel proprietary sinusoidal speech codec designed for efficient speech storage is capable of achieving relatively good speech quality at compression ratios beyond the ones offered by the standardized speech coding solutions, i.e., at bitrates of approximately 1 kbps and below. The efficiency of the proposed coding approach is based on model simplifications, mode-based segmental processing, and the method of adaptive downsampling and quantization. The coding efficiency is also further improved using a novel flexible multi-mode matrix quantizer structure and enhanced dynamic codebook reordering. The compression is also facilitated using a new perceptual irrelevancy removal method. The VLBR codec is also applied to text-to-speech synthesis. In particular, the codec is utilized for the compression of unit selection databases and for the parametric concatenation of speech units. It is also shown that the efficiency of the database compression can be further enhanced using speaker-specific retraining of the codec. Moreover, the computational load is significantly decreased using a new compression-motivated scheme for very fast and memory-efficient calculation of concatenation costs, based on techniques and implementations used in the VLBR codec. Finally, the VLBR codec and the related speech synthesis techniques are complemented with voice conversion methods that allow modifying the perceived speaker identity which in turn enables, e.g., cost-efficient creation of new text-to-speech voices. The VLBR-based voice conversion system combines compression with the popular Gaussian mixture model based conversion approach. Furthermore, a novel method is proposed for converting the prosodic aspects of speech. The performance of the VLBR-based voice conversion system is also enhanced using a new approach for mode selection and through explicit control of the degree of voicing. The solutions proposed in the thesis together form a complete system that can be utilized in different ways and configurations. The VLBR codec itself can be utilized, e.g., for efficient compression of audio books, and the speech synthesis related methods can be used for reducing the footprint and the computational load of concatenative text-to-speech synthesizers to levels required in some embedded applications. The VLBR-based voice conversion techniques can be used to complement the codec both in storage applications and in connection with speech synthesis. It is also possible to only utilize the voice conversion functionality, e.g., in games or other entertainment applications

Scalable and perceptual audio compression

This thesis deals with scalable perceptual audio compression. Two scalable perceptual solutions as well as a scalable to lossless solution are proposed and investigated. One of the scalable perceptual solutions is built around sinusoidal modelling of the audio signal whilst the other is built on a transform coding paradigm. The scalable coders are shown to scale both in a waveform matching manner as well as a psychoacoustic manner. In order to measure the psychoacoustic scalability of the systems investigated in this thesis, the similarity between the original signal\u27s psychoacoustic parameters and that of the synthesized signal are compared. The psychoacoustic parameters used are loudness, sharpness, tonahty and roughness. This analysis technique is a novel method used in this thesis and it allows an insight into the perceptual distortion that has been introduced by any coder analyzed in this manner

Speech coding at medium bit rates using analysis by synthesis techniques

Speech coding at medium bit rates using analysis by synthesis technique

The 1993 Space and Earth Science Data Compression Workshop

The Earth Observing System Data and Information System (EOSDIS) is described in terms of its data volume, data rate, and data distribution requirements. Opportunities for data compression in EOSDIS are discussed

Étude de transformées temps-fréquence pour le codage audio faible retard en haute qualité

In recent years there has been a phenomenal increase in the number of products and applications which make use of audio coding formats. Amongthe most successful audio coding schemes, the MPEG-1 Layer III (mp3), the MPEG-2 Advanced Audio Coding (AAC) or its evolution MPEG-4High Efficiency-Advanced Audio Coding (HE-AAC) can be cited. More recently, perceptual audio coding has been adapted to achieve codingat low-delay such to become suitable for conversational applications. Traditionally, the use of filter bank such as the Modified Discrete CosineTransform (MDCT) is a central component of perceptual audio coding and its adaptation to low delay audio coding has become an important researchtopic. Low delay transforms have been developed in order to retain the performance of standard audio coding while reducing dramatically the associated algorithmic delay.This work presents some elements allowing to better accommodate the delay reduction constraint. Among the contributions, a low delay blockswitching tool which allows the direct transition between long transform and short transform without the insertion of transition window. The sameprinciple has been extended to define new perfect reconstruction conditions for the MDCT with relaxed constraints compared to the original definition.As a consequence, a seamless reconstruction method has been derived to increase the flexibility of transform coding schemes with the possibility toselect a transform for a frame independently from its neighbouring frames. Finally, based on this new approach, a new low delay window design procedure has been derived to obtain an analytic definition for a new family of transforms, permitting high quality with a substantial coding delay reduction. The performance of the proposed transforms has been thoroughly evaluated, an evaluation framework involving an objective measurement of the optimal transform sequence is proposed. It confirms the relevance of the proposed transforms used for audio coding. In addition, the new approaches have been successfully applied to the recent standardisation work items, such as the low delay audio coding developed at MPEG (LD-AAC and ELD-AAC) and they have been evaluated with numerous subjective testing, showing a significant improvement of the quality for transient signals. The new low delay window design has been adopted in G.718, a scalable speech and audio codec standardized in ITU-T and has demonstrated its benefit in terms of delay reduction while maintaining the audio quality of a traditional MDCT.Codage audio à faible retard à l'aide de la définition de nouvelles fenêtres pour la transformée MDCT et l'introduction d'un nouveau schéma de commutation de fenêtre

Self Designing Pattern Recognition System Employing Multistage Classification

Recently, pattern recognition/classification has received a considerable attention in diverse engineering fields such as biomedical imaging, speaker identification, fingerprint recognition, etc. In most of these applications, it is desirable to maintain the classification accuracy in the presence of corrupted and/or incomplete data. The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distortion. Some classification techniques that are introduced in the literature are described in Chapter one. In this dissertation, a pattern recognition approach that can be designed to have evolutionary learning by developing the features and selecting the criteria that are best suited for the recognition problem under consideration is proposed. Chapter two presents some of the features used in developing the set of criteria employed by the system to recognize different types of signals. It also presents some of the preprocessing techniques used by the system. The system operates in two modes, namely, the learning (training) mode, and the running mode. In the learning mode, the original and preprocessed signals are projected into different transform domains. The technique automatically tests many criteria over the range of parameters for each criterion. A large number of criteria are developed from the features extracted from these domains. The optimum set of criteria, satisfying specific conditions, is selected. This set of criteria is employed by the system to recognize the original or noisy signals in the running mode. The modes of operation and the classification structures employed by the system are described in details in Chapter three. The proposed pattern recognition system is capable of recognizing an enormously large number of patterns by virtue of the fact that it analyzes the signal in different domains and explores the distinguishing characteristics in each of these domains. In other words, this approach uses available information and extracts more characteristics from the signals, for classification purposes, by projecting the signal in different domains. Some experimental results are given in Chapter four showing the effect of using mathematical transforms in conjunction with preprocessing techniques on the classification accuracy. A comparison between some of the classification approaches, in terms of classification rate in case of distortion, is also given. A sample of experimental implementations is presented in chapter 5 and chapter 6 to illustrate the performance of the proposed pattern recognition system. Preliminary results given confirm the superior performance of the proposed technique relative to the single transform neural network and multi-input neural network approaches for image classification in the presence of additive noise

Low Power Digital Filter Implementation in FPGA

Digital filters suitable for hearing aid application on low power perspective have been developed and implemented in FPGA in this dissertation. Hearing aids are primarily meant for improving hearing and speech comprehensions. Digital hearing aids score over their analog counterparts. This happens as digital hearing aids provide flexible gain besides facilitating feedback reduction and noise elimination. Recent advances in DSP and Microelectronics have led to the development of superior digital hearing aids. Many researchers have investigated several algorithms suitable for hearing aid application that demands low noise, feedback cancellation, echo cancellation, etc., however the toughest challenge is the implementation. Furthermore, the additional constraints are power and area. The device must consume as minimum power as possible to support extended battery life and should be as small as possible for increased portability. In this thesis we have made an attempt to investigate possible digital filter algorithms those are hardware configurable on low power view point. Suitability of decimation filter for hearing aid application is investigated. In this dissertation decimation filter is implemented using ‘Distributed Arithmetic’ approach.While designing this filter, it is observed that, comb-half band FIR-FIR filter design uses less hardware compared to the comb-FIR-FIR filter design. The power consumption is also less in case of comb-half band FIR-FIR filter design compared to the comb-FIR-FIR filter. This filter is implemented in Virtex-II pro board from Xilinx and the resource estimator from the system generator is used to estimate the resources. However ‘Distributed Arithmetic’ is highly serial in nature and its latency is high; power consumption found is not very low in this type of filter implementation. So we have proceeded for ‘Adaptive Hearing Aid’ using Booth-Wallace tree multiplier. This algorithm is also implemented in FPGA and power calculation of the whole system is done using Xilinx Xpower analyser. It is observed that power consumed by the hearing aid with Booth-Wallace tree multiplier is less than the hearing aid using Booth multiplier (about 25%). So we can conclude that the hearing aid using Booth-Wallace tree multiplier consumes less power comparatively. The above two approached are purely algorithmic approach. Next we proceed to combine circuit level VLSI design and with algorithmic approach for further possible reduction in power. A MAC based FDF-FIR filter (algorithm) that uses dual edge triggered latch (DET) (circuit) is used for hearing aid device. It is observed that DET based MAC FIR filter consumes less power than the traditional (single edge triggered, SET) one (about 41%). The proposed low power latch provides a power saving upto 65% in the FIR filter. This technique consumes less power compared to previous approaches that uses low power technique only at algorithmic abstraction level. The DET based MAC FIR filter is tested for real-time validation and it is observed that it works perfectly for various signals (speech, music, voice with music). The gain of the filter is tested and is found to be 27 dB (maximum) that matches with most of the hearing aid (manufacturer’s) specifications. Hence it can be concluded that FDF FIR digital filter in conjunction with low power latch is a strong candidate for hearing aid application

Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks