Showing papers on "Codebook published in 2001"

A speech communication system and method for handling lost frames

Abstract: A speech communication system and method that has an improved way of handling information lost during transmission from the encoder to the decoder. More specifically, the improved speech communication system more accurately recovers from losing information about a frame of speech such as line spectral frequencies (LSF's), pitch lag (or adaptive codebook excitation), fixed codebook excitation and/or gain information. After estimating lost parameters in a lost frame and synthesizing the speech, the improved system matches the energy of the synthesized speech to the energy of the previously received frame.

Excitation vector generator, speech coder and speech decoder

Abstract: A random code vector reading section and a random codebook of a conventional CELP type speech coder/decoder are respectively replaced with an oscillator for outputting different vector streams in accordance with values of input seeds, and a seed storage section for storing a plurality of seeds. This makes it unnecessary to store fixed vectors as they are in a fixed codebook (ROM), thereby considerably reducing the memory capacity.

Methods and apparatus for encoding a video signal

Abstract: The present invention relates to systems and methods for compressing, decompressing, and transmitting video data. The systems and methods include pixel by pixel motion estimation and compensation and efficient quantization of residual errors. The present invention applies block estimation of the residual error produced by motion compensation. The block estimation is applied by a local decoder to generate synthesized blocks of video data. The block estimation approximated uses a set of predetermined motion estimation errors that are stored as error vectors in a codebook. The codebook is included in an encoder of the present invention and converts an error vector for each block to an error vector index. The error vector index, which introduces minimal transmission burden, is then sent from the encoder to a target decoder. A receiving decoder also includes a copy of the codebook and converts the error vector index to its associated error vector for reconstruction of video data.

Hierarchical SOM applied to image compression

Abstract: The increase of the need for image storage and transmission in computer systems has increased the importance of signal and image compression algorithms. The approach involving vector quantization (VQ) relies on the design of a finite set of codes which will substitute the original signal during transmission with a minimal of distortion, taking advantage of the spatial redundancy of image to compress them. Algorithms such as LBG and SOM work in an unsupervised way toward finding a good codebook for a given training data. However, the number of code vectors (N) needed for VQ increases with the vector dimension, and full-search algorithms such as LBG and SOM can lead to large training and coding times. An alternative for reducing the computational complexity is the use of a tree-structured vector quantization algorithm. This paper presents an application of a hierarchical SOM for image compression which reduces the search complexity from O(N) to O(log N), enabling a faster training and image coding. Results are given for conventional SOM, LBG and HSOM, showing the advantage of the proposed method.

Robust Speech Recognition using Missing Feature Theory and Vector Quantization

Abstract: This paper addresses the problem of speech recognition in noisy conditions when low complexity is required like in embedded systems. In such systems, vector quantization is generally used to reduce the complexity of the recognition systems (e.g. HMMs). A novel approach for vector quantization based on the missing data theory is proposed. This approach allows to increase the robustness of the system against the noise perturbations with only a small increase of the computational requirements. The proposed algorithm is composed of two parts. The first part consists in dividing the spectral temporal features of the noisy signal into two subspaces: the unreliable (or missing) features and the reliable (or present) features. The second part of the proposed approach consists in defining a robust distance measure for vector quantization that compensates for the unreliable features. The proposed approach obtains similar results in noisy conditions than a more classical approach that consists in adapting the codebook of the vector quantization to the noisy conditions using model compensation. However the computation requirements are lower in the proposed approach and it is more suitable for a low complexity speech recognition system.

Algebraic codebook system and method

Abstract: Code-excited linear prediction speech encoders/decoders with excitation including an algebraic codebook contribution encoded with a single sign bit for each track of pulses by inferring pulse amplitude signs from the pulse position code ordering within a codeword.

System for coding speech information using an adaptive codebook with enhanced variable resolution scheme

Abstract: A speech coding system includes an adaptive codebook containing excitation vector data associated with corresponding adaptive codebook indices (e.g., pitch lags). Different excitation vectors in the adaptive codebook have distinct corresponding resolution levels. The resolution levels include a first resolution range of continuously variable or finely variable resolution levels. A gain adjuster scales a selected excitation vector data or preferential excitation vector data from the adaptive codebook. A synthesis filter synthesizes a synthesized speech signal in response to an input of the scaled excitation vector data. The speech coding system may be applied to an encoder, a decoder, or both.

System and method for reduced codebook vector quantization

Abstract: The present invention extends the generalized Lloyd algorithm (GLA) for vector quantizer (VQ) codebook improvement and codebook design to a new linearly-constrained generalized Lloyd algorithm (LCGLA). The LCGLA improves the quality of VQ codebooks, by forming the codebooks from linear combinations of a reduced set of base codevectors. The present invention enables a principled approach for compressing texture images in formats compatible with various industry standards. New, more flexible compressed texture image formats are also made possible with the present invention. The present invention enhances signal compression by improving traditional VQ approaches through the integrated application of linear constraints on the multiple pattern and signal prototypes that represent a single pattern or block of signal samples.

Short-term enhancement in celp speech coding

Abstract: A speech-coding device includes a fixed codebook, an adaptive codebook, a short-term enhancement circuit, and a summing circuit. The short-term enhancement circuit connects an output of the fixed codebook to a summing circuit. The summing circuit adds an adaptive codebook contribution to a fixed codebook contribution. The short-term enhancement circuit can also be connected to a synthesis filter to emphasize the spectral formants in an encoder and a decoder.

Parameter interpolation to enhance the frame erasure robustness of CELP coders in packet networks

Abstract: Frame erasure (FE) robustness is an important quality measure for voice over IP networks (VoIP). The recovery of the erased frames from the received information is crucial to realize this robustness. We allow the lost frames to be recovered from both the "previous" and "next" good frames. We first give quantitative distortion comparisons between predictive and interpolative frame recovery. Then we add FE-robust LSF coding modes to the popular ITU G.723.1 and G.729 CELP coders. These FE-robust modes utilize intraframe LSF VQ and invoke no bit-rate increase for the G.723.1 coder and a small increase (0.4 kb/s) for G.729. Simulations show that FE robust coding with interpolation achieves average spectral distortions 0.7-1.8 dB smaller than that of the original coders. Significant quality improvement was achieved by combined implementation of FE robust coding, LSF and pitch interpolation, and a proposed fixed codebook excitation recovery method.

Multichannel ECG compression using multichannel adaptive vector quantization

Abstract: Adaptive vector quantization (AVQ) is a recently proposed approach for electrocardiogram (ECG) compression. The adaptability of the approach can be used to control the quality of reconstructed signals. However, like most of other ECG compression methods, AVQ only deals with the single-channel ECG, and for the multichannel (MC) ECG, coding ECG signals on a channel by channel basis is not efficient, because the correlation across channels is not exploited. To exploit this correlation, an MC version of AVQ is proposed. In the proposed approach, the AVQ index from each channel is collected to form a new input vector. The vector is then vector quantized adaptively using one additional codebook called index codebook. Both the MIT/BIH database and a clinical Holter database are tested. The experimental results show that, for exactly the same quality of reconstructed signals, the MC-AVQ performs better than single-channel AVQ in terms of bit rate. A theoretical analysis supporting this result is also demonstrated in this paper. For the same and relatively good visual quality, the average compressed data rate/channel is reduced from 293.5 b/s using the single-channel AVQ to 238.2 b/s using the MC-AVQ in the MIT/BIH case.

Blur identification from vector quantizer encoder distortion

Abstract: Blur identification is a crucial first step in many image restoration techniques. An approach for identifying image blur using vector quantizer encoder distortion is proposed. The blur in an image is identified by choosing from a finite set of candidate blur functions. The method requires a set of training images produced by each of the blur candidates. Each of these sets is used to train a vector quantizer codebook. Given an image degraded by unknown blur, it is first encoded with each of these codebooks. The blur in the image is then estimated by choosing from among the candidates, the one corresponding to the codebook that provides the lowest encoder distortion. Simulations are performed at various bit rates and with different levels of noise. Results show that the method performs well even at a signal-to-noise ratio (SNR) as low as 10 dB.

Reducing memory requirements of a codebook vector search

Abstract: Methods and apparatus for quickly selecting an optimal excitation waveform from a codebook are presented herein. To reduce the number of computations required to choose the optimal codebook vector, a subset of codevectors are selected based upon optimal pulse locations, wherein the subset of codevectors form a subcodebook. Rather than searching the entire codebook, only the entries of the subcodebook are searched.

Fast code-vector searching

Abstract: Methods and apparatus for quickly selecting an optimal excitation waveform from a codebook are presented herein. In encoding schemes that use forward and backward pitch enhancement, storage and processor load is reduced by approximating a two-dimensional autocorrelation matrix with a one-dimensional autocorrelation vector. The approximation is possible when a cross-correlation element is configured to determine the autocorrelation matrix of an impulse response and a pulse energy determination element is configured to determine the energy of a pulse code vector that incorporates secondary pulse positions.

Error correctible channel coding method

Abstract: A coding scheme encodes a series of M-bit message words into a series of N-bit codewords having a bounded unbalance. A part of the M-bit message words are used to index bits and others source words. The message words are grouped to a plurality of subsets using the index bits thereof. The unbalanced codewords are classified to a plurality of sets based on a state transition in a trellis. Each of the classified unbalanced codewords is stored at a codebook for each codeword set, respectively. The codebook has the source words, a codeword ID for each of the source words and the classified unbalanced codewords. The message words are encoded into the respective codeword in the codebook, respectively, by using the index bits of the message words and the state transition in the trellis having states and levels. The codewords are selected by transition for each state at each level stage of the trellis based on correlations.

Optimization of Classifiers Using Genetic Algorithms

Abstract: This chapter contains sections titled: Introduction, State of the Art, Method, Unsupervised Codebook Design and Optimization Using GAs, Genetic Optimization of LVQ Algorithm, Discussion and Future Work, Acknowledgments, References

Smooth side-match classified vector quantizer with variable block size

Abstract: Although the side-match vector quantizer (SMVQ) reduces the bit rate, the image coding quality by SMVQ generally degenerates as the gray level transition across the boundaries of the neighboring blocks is increasing or decreasing. This study presents a smooth side-match method to select a state codebook according to the smoothness of the gray levels between neighboring blocks. This method achieves a higher PSNR and better visual perception than SMVQ does for the same bit rate. Moreover, to design codebooks, a genetic clustering algorithm that automatically finds the appropriate number of clusters is proposed. The proposed smooth side-match classified vector quantizer (SSM-CVQ) is thus a combination of three techniques: the classified vector quantization, the variable block size segmentation and the smooth side-match method. Experimental results indicate that SSM-CVQ has a higher PSNR and a lower bit rate than other methods. Furthermore, the Lena image can be coded by SSM-CVQ with 0.172 bpp and 32.49 dB in PSNR.

System and methods for concealing errors in data transmission

Abstract: The present invention provides a frame erasure concealment device and method that is based on reestimating gain parameters for a code excited linear prediction (CELP) coder. During operation, when a frame in a stream of received data is detected as being erased, the coding parameters, especially an adaptive codebook gain gp and a fixed codebook gain gc, of the erased and subsequent frames can be reestimated by a gain matching procedure. By using this technique with the IS-641 speech coder, it has been found that the present invention improves the speech quality under various channel conditions, compared with a conventional extrapolation-based concealment algorithm.

Vector quantizing for lpc parameters

Abstract: The present invention carries out pre-selection on many LPC codevectors stored in an LSF codebook 101 using a weighted Euclidean distortion as a measure and carries out a full-code selection on the LPC codevectors left after the pre-selection using an amount of distortion in a spectral space as a measure. This makes it possible to improve the quantization performance of the LPC parameter vector quantizer and improve the quality of synthesized speech of the speech coder/decoder.

Combined Kohonen neural networks and discrete cosine transform method for iterated transformation theory

Abstract: Iterated transformation theory (ITT) coding, also known as fractal coding, in its original form, allows fast decoding but suffers from long encoding times. During the encoding step, a large number of block best-matching searches have to be performed which leads to a computationally expensive process. Because of that, most of the research efforts carried on this held are focused on speeding up the encoding algorithm. Many different methods and algorithms have been proposed, from simple classifying methods to multi-dimensional nearest key search. We present in this paper a new method that significantly reduces the computational load of ITT-based image coding. Both domain and range blocks of the image are transformed into the frequency domain (which has proven to be more appropriate for ITT coding). Domain blocks are then used to train a two-dimensional Kohonen neural network (KNN) forming a codebook similar to vector quantization coding. The property of KNN land self-organizing feature maps in general) which maintains the input space (transformed domain blocks) topology allows to perform a neighboring search to find the piecewise transformation between domain and range blocks. (C) 2001 Elsevier Science B.V. All rights reserved.

Coding of digital video with high motion content

Abstract: Methods for coding the current frame of a video data bit stream are provided. Methods include, for example, creating and maintaining a global codebook of historic values for the macroblocks of previous frames; searching entries in the global codebook to find the best estimation of the current frame and calculate a measure of the difference between values for the two macroblocks; comparing the effectiveness of the estimation macroblock provided by the global codebook entry to the estimation provided by a motion compensation scheme; choosing the best estimation method and coding the current frame; and updating the global codebook based on the new coded macroblock.

Lpc vector quantization apparatus

Abstract: The present invention carries out pre-selection on many LPC codevectors stored in an LSF codebook 101 using a weighted Euclidean distortion as a measure and carries out a full-code selection on the LPC codevectors left after the pre-selection using an amount of distortion in a spectral space as a measure. This makes it possible to improve the quantization performance of the LPC parameter vector quantizer and improve the quality of synthesized speech of the speech coder/decoder.

Gains quantization for a clep speech coder

Abstract: A speech encoder that analyzes and classifies each frame of speech as being periodic-like speech or non-periodic like speech where the speech encoder performs a different gain quantization process depending if the speech is periodic or not. If the speech is periodic, the improved speech encoder obtains the pitch gains from the unquantized weighted speech signal and performs a pre-vector quantization of the adaptive codebook gain GP for each subframe of the frame before subframe processing begins and a closed-loop delayed decision vector quantization of the fixed codebook gain GC. If the frame of speech is non-periodic, the speech encoder may use any known method of gain quantization. The result of quantizing gains of periodic speech in this manner results in a reduction of the number of bits required to represent the quantized gain information and for periodic speech, the ability to use the quantized pitch gain for the current subframe to search the fixed codebook for the fixed codebook excitation vector for the current subframe. Alternatively, the new gain quantization process which was used only for periodic signals may be extended to non-periodic signals as well. This second strategy results in a slightly higher bit rate than that for periodic signals that use the new gain quantization strategy, but is still lower than the prior art's bit rate. Yet another alternative is to use the new gain quantization process for all speech signals without distinguishing between periodic and non-periodic signals.

Approximate prefix coding for data compression

Abstract: A method of compressing a dataset of distinct symbols, such as binary instructions, that all have a common length. The instructions are ranked by frequency. The most common symbols are classified according to a successive-powers-of-two class size scheme, and are compressed as concatenations of respective class codes and respective symbol codes. A literal class code is prepended to the remaining symbols. The associated codebook is a list of the classified symbols in rank order. To decompress the compressed symbols, the compressed symbols are parsed into their class codes and symbol codes, and the symbol codes are used as lookup indices for the codebook. The scope of the invention includes a computer with a fixed-instruction-length processor and one or more instruction storage areas where compressed instructions are stored and decompressed for execution.

Joint optimization of VQ codebooks and QAM signal constellations for AWGN channels

Abstract: A joint design scheme has been proposed to optimize the source encoder and the modulation signal constellation based on the minimization of the end-to-end distortion including both the quantization error and channel distortion. The proposed scheme first optimizes the vector quantization (VQ) codebook for a fixed modulation signal set, and then the modulation signals for the fixed VQ codebook. These two steps are iteratively repeated until they reach a local optimum solution. It has been shown that the performance of the proposed system can be enhanced by employing a new efficient mapping scheme between codevectors and modulation signals. Simulation results show that a jointly optimized system based on the proposed algorithms outperforms the conventional system based on a conventional quadrature amplitude modulation signal set and the VQ codebook designed for a noiseless channel.