Time and frequency domain algorithms for speech coding

The promise of digital hardware economies (due to recent advances in VLSI technology), has focussed much attention on more complex and sophisticated speech coding algorithms which offer improved quality at relatively low bit rates. This thesis describes the results (obtained from computer simulations) of research into various efficient (time and frequency domain) speech encoders operating at a transmission bit rate of 16 Kbps. In the time domain, Adaptive Differential Pulse Code Modulation (ADPCM) systems employing both forward and backward adaptive prediction were examined. A number of algorithms were proposed and evaluated, including several variants of the Stochastic Approximation Predictor (SAP). A Backward Block Adaptive (BBA) predictor was also developed and found to outperform the conventional stochastic methods, even though its complexity in terms of signal processing requirements is lower. A simplified Adaptive Predictive Coder (APC) employing a single tap pitch predictor considered next provided a slight improvement in performance over ADPCM, but with rather greater complexity. The ultimate test of any speech coding system is the perceptual performance of the received speech. Recent research has indicated that this may be enhanced by suitable control of the noise spectrum according to the theory of auditory masking. Various noise shaping ADPCM configurations were examined, and it was demonstrated that a proposed pre-/post-filtering arrangement which exploits advantageously the predictor-quantizer interaction, leads to the best subjective performance in both forward and backward prediction systems. Adaptive quantization is instrumental to the performance of ADPCM systems. Both the forward adaptive quantizer (AQF) and the backward oneword memory adaptation (AQJ) were examined. In addition, a novel method of decreasing quantization noise in ADPCM-AQJ coders, which involves the application of correction to the decoded speech samples, provided reduced output noise across the spectrum, with considerable high frequency noise suppression. More powerful (and inevitably more complex) frequency domain speech coders such as the Adaptive Transform Coder (ATC) and the Sub-band Coder (SBC) offer good quality speech at 16 Kbps. To reduce complexity and coding delay, whilst retaining the advantage of sub-band coding, a novel transform based split-band coder (TSBC) was developed and found to compare closely in performance with the SBC. To prevent the heavy side information requirement associated with a large number of bands in split-band coding schemes from impairing coding accuracy, without forgoing the efficiency provided by adaptive bit allocation, a method employing AQJs to code the sub-band signals together with vector quantization of the bit allocation patterns was also proposed. Finally, 'pipeline' methods of bit allocation and step size estimation (using the Fast Fourier Transform (FFT) on the input signal) were examined. Such methods, although less accurate, are nevertheless useful in limiting coding delay associated with SRC schemes employing Quadrature Mirror Filters (QMF)

Improvements on stochastic vector quantization of images

A novel nonadaptive fixed-rate vector quantizer encoding scheme is presented, and preliminary results are shown. The design of the codebook has been based on a stochastic approach in order to match a previously defined model for the image to be encoded. Following this approach, the generation of the codebook is made extremely simple in terms of computational load. Good visual results are shown in the range of 0.5-0.8 bit/pixel. Much better performance is expected for adaptive schemes.Peer ReviewedPostprint (published version

Weighted universal image compression

We describe a general coding strategy leading to a family of universal image compression systems designed to give good performance in applications where the statistics of the source to be compressed are not available at design time or vary over time or space. The basic approach considered uses a two-stage structure in which the single source code of traditional image compression systems is replaced with a family of codes designed to cover a large class of possible sources. To illustrate this approach, we consider the optimal design and use of two-stage codes containing collections of vector quantizers (weighted universal vector quantization), bit allocations for JPEG-style coding (weighted universal bit allocation), and transform codes (weighted universal transform coding). Further, we demonstrate the benefits to be gained from the inclusion of perceptual distortion measures and optimal parsing. The strategy yields two-stage codes that significantly outperform their single-stage predecessors. On a sequence of medical images, weighted universal vector quantization outperforms entropy coded vector quantization by over 9 dB. On the same data sequence, weighted universal bit allocation outperforms a JPEG-style code by over 2.5 dB. On a collection of mixed test and image data, weighted universal transform coding outperforms a single, data-optimized transform code (which gives performance almost identical to that of JPEG) by over 6 dB

Optimal modeling for complex system design

The article begins with a brief introduction to the theory describing optimal data compression systems and their performance. A brief outline is then given of a representative algorithm that employs these lessons for optimal data compression system design. The implications of rate-distortion theory for practical data compression system design is then described, followed by a description of the tensions between theoretical optimality and system practicality and a discussion of common tools used in current algorithms to resolve these tensions. Next, the generalization of rate-distortion principles to the design of optimal collections of models is presented. The discussion focuses initially on data compression systems, but later widens to describe how rate-distortion theory principles generalize to model design for a wide variety of modeling applications. The article ends with a discussion of the performance benefits to be achieved using the multiple-model design algorithms

Masking of errors in transmission of VAPC-coded speech

A subjective evaluation is provided of the bit error sensitivity of the message elements of a Vector Adaptive Predictive (VAPC) speech coder, along with an indication of the amenability of these elements to a popular error masking strategy (cross frame hold over). As expected, a wide range of bit error sensitivity was observed. The most sensitive message components were the short term spectral information and the most significant bits of the pitch and gain indices. The cross frame hold over strategy was found to be useful for pitch and gain information, but it was not beneficial for the spectral information unless severe corruption had occurred

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Performance of a low data rate speech codec for land-mobile satellite communications

In an effort to foster the development of new technologies for the emerging land mobile satellite communications services, JPL funded two development contracts in 1984: one to the Univ. of Calif., Santa Barbara and the other to the Georgia Inst. of Technology, to develop algorithms and real time hardware for near toll quality speech compression at 4800 bits per second. Both universities have developed and delivered speech codecs to JPL, and the UCSB codec was extensively tested by JPL in a variety of experimental setups. The basic UCSB speech codec algorithms and the test results of the various experiments performed with this codec are presented