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3DTV Conference

作者： Nikolce Stefanoski Xiaoliang Liu Patrick Klie Jorn Ostermann Leibniz Universität Hannover Hanover Germany

We present a linear predictive compression approach for time-consistent 3D mesh sequences supporting and exploiting scalability. The algorithm decomposes each frame of a mesh sequence in layers employing patch-based mesh simplification techniques. This layered decomposition is consistent in time. Following the predictive coding paradigm, local temporal and spatial dependencies between layers and frames are exploited for compression. Prediction is performed vertex-wise from coarse to fine layers exploiting the motion of already encoded 1-ring neighbor vertices for prediction of the current vertex location. It is shown that a predictive exploitation of the proposed layered configuration of vertices can improve the compression performance upon other state-of-the-art approaches by up to 16% in domains relevant for applications.

关键词： linear predictive coding Scalability Application software Decoding Principal component analysis Wavelet transforms Coherence Entropy predictive coding Animation

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Malayalam Vowel Recognition Based on linear predictive coding Parameters and k-NN Algorithm

Malayalam Vowel Recognition Based on Linear Predictive Codin...

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International Conference on Computational Intelligence and Multimedia Applications

作者： T.M. Thasleema V. Kabeer N.K. Narayanan School of Information Science & Technology Kannur University Kerala India

ISBN: (纸本)9780769530505

Accurate vowel recognition forms the backbone of most successful speech recognition systems. A collection of techniques exists to extract the relevant features from the steady-state regions of the vowels both in time as well as in frequency domains. In this paper we present a novel and accurate feature extraction technique for recognizing Malayalam spoken vowels based on linear predictive coding method and compared the result with wavelet packet decomposition method. Recognition is performed using k-NN pattern classifier. The classification is conducted for 5 Malayalam vowel sounds using training and test set consisting of 50 ( 10 from each class) samples each. The overall recognition accuracy obtained for the vowel using LPC feature extraction method is 94%. The proposed method is efficient and computationally less expensive. The experimental results demonstrate the efficiency of the proposed algorithm

关键词： Speech recognition linear predictive coding Speech analysis Feature extraction Tongue Information science Speech processing Wavelet packets Lips Shape

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Unified pulse-replacement search algorithms for algebra codebooks of speech coders

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IET SIGNAL PROCESSING 2010年第6期4卷 658-665页

作者： Chen, F-K Chen, G-M Su, B-K Tsai, Y-R So Taiwan Univ Dept Comp Sci & Informat Engn Tainan Taiwan

The algebraic code excited linear prediction (ACELP) algorithm, because of low complexity and high quality in its analysis-by-synthesis optimisation, has been adopted by many speech coding standards. This study proposes the unified generalised pulse replacement (UPR) search algorithm for the stochastic codebook of ACELP speech coders. The proposed UPR algorithm discusses the search breadth, the order of the search direction and the update frequency based on the pulse replacement method. In addition, there are many derivative types of UPR algorithms discussed. The proposed approaches can achieve the lowest computational complexity with imperceptible degradation of the speech quality. Furthermore, the normalised degradation ratio based on the standard subjective quality measurement is proposed to fairly compare the performance. The experimental results will verify the claims.

关键词： algebraic code excited linear prediction algorithm linear predictive coding speech coders vocoders Codecs, coders and decoders unified pulse-replacement search algorithms algebra codebooks stochastic codebook algebraic codes Codes

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Joint quantisation strategies for low bit-rate sinusoidal coding

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IET SIGNAL PROCESSING 2010年第5期4卷 548-559页

作者： Unver, E. Villette, S. Kondoz, A. Univ Surrey Ctr Commun Syst Res Guildford GU2 7XH Surrey England

Although there are speech coding standards producing high-quality speech above 4 kbps, below that transparent quality has not been achieved yet. There is still room for improvement at lower bit rates, especially at 2.4 kbps and below, which is an area of interest for military and security applications. Strategies for achieving high-quality speech using sinusoidal coding at very low bit rates are discussed. Previous work in the literature on combining several frames in a metaframe and performing variable bit allocation within the metaframe is extended. Experiments have been carried out to find an optimum metaframe size compromise between delay and quantisation gains. Metaframe classification and quantisation according to the metaframe class are used for better efficiency. A method for voicing determination from the linear prediction coefficient (LPC) shape is also presented. The proposed techniques have been applied to the SB-LPC vocoder to produce speech at 1.2 and 0.8 kbps, and compared to the original SB-LPC vocoder at 2.4/1.2 kbps as well as an established standard (Mixed Excitation linear predictive - MELP - vocoder) at 2.4/1.2/0.6 kbps in a listening test. It has been found that the proposed techniques have been effective in reducing the bit rate while not compromising the speech quality.

关键词： low bit-rate sinusoidal coding metaframe classification speech coding Speech processing techniques speech quality linear prediction coefficient linear predictive coding Speech and audio coding mixed excitation linear predictive vocoder SB-LPC vocoder metaframe quantisation strategies Codecs, coders and decoders vocoders

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Introduction to the Special Issue on Model Order Selection in Signal Processing Systems

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2010年第3期4卷 465-467页

作者： Wu, Hsiao-Chun Hjorungnes, Are Wang, Chin-Liang Wicks, Michael C. Louisiana State Univ Dept Elect & Comp Engn Baton Rouge LA 70803 USA Univ Oslo Fac Math & Nat Sci N-0317 Oslo Norway Natl Tsing Hua Univ Dept Elect Engn Hsinchu 30013 Taiwan USAF Sensors Directorate Res Lab Rome NY 13411 USA

The 18 papers in this special issue focus on model order selection in signal processing systems.

关键词： Special issues and sections Signal processing Biomedical signal processing predictive models Speech processing Parameter estimation Array signal processing USA Councils linear predictive coding Speech coding

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Autoregressive modeling of near-IR spectra and MLR to predict RON values of gasolines

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FUEL 2010年第1期89卷 158-161页

作者： Kardamakis, Andreas A. Pasadakis, Nikos Tech Univ Crete Mineral Resources Engn Dept Khania 73100 Greece

A new calibration method that accurately predicts the Research Octane Number (RON) values of gasoline fractions, based on their infrared spectra, is presented. This model combines linear predictive coding (LPC) and multiple linear regression (MLR) as an integrated estimation technique. Spectral information from the 4800-3520 cm (1) range was initially encoded into linear predictive (LP) coefficients, which were used as predictor variables in the MLR model against RON values. The model was trained and tested on an extensive data set (384 gasoline samples) and found to ensure prediction accuracy of 0.3 RON Root Mean Squared Error (RMSE). The LPC technique was found to be efficient in capturing spectral features of the entire range, related to the RON characteristics of the gasoline samples, without the need of any pretreatment on the experimental raw data. The small number of input variables in the regression model ensures a robust, easy-to-use and high accuracy prediction model. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Gasoline RON linear predictive coding Infrared spectroscopy

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An application of linear predictive coding and computational geometry to iris recognition

An application of linear predictive coding and computational...

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Working Conference on Computer Vision

作者： Alipour, Masoud Farhadi, Ali Razavi, Nima Inst Studies Theoret Phys & Math Tehran Iran

The aim of this work is to present a method in computer vision for person identification via iris recognition. The method makes essential use of computational geometry and LPC. (C) 2007 Wiley Periodicals, Inc.

关键词： computer vision texture classification biometrics linear predictive coding computational geometry

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Fixed-Lag Smoothing for Low-Delay predictive coding with Noise Shaping for Lossy Networks

Fixed-Lag Smoothing for Low-Delay Predictive Coding with Noi...

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Data Compression Conference (DCC)

作者： Thomas Arildsen Jan Ostergaard Manohar N. Murthi Soren Vang Andersen Soren Holdt Jensen Department of Electronic Systems University of Aalborg Denmark Electrical and Computer Engineering University of Miami FL USA

ISBN: (纸本)9781424464258;9780769539942

We consider linear predictive coding and noise shaping for coding and transmission of auto-regressive (AR) sources over lossy networks. We generalize an existing framework to arbitrary filter orders and propose use of fixed-lag smoothing at the decoder, in order to further reduce the impact of transmission failures. We show that fixed-lag smoothing up to a certain delay can be obtained without additional computational complexity by exploiting the state-space structure. We prove that the proposed smoothing strategy strictly improves performance under quite general conditions. Finally, we provide simulations on AR sources, and channels with correlated losses, and show that substantial improvements are possible.

关键词： Smoothing methods predictive coding Noise shaping linear predictive coding Propagation losses Filters Decoding Delay Computational complexity Computational modeling

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Speaker-Independent Malay Vowel Recognition of Children using Neural Networks

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11th International Congress of the IUPESM/World Congress on Medical Physics and Biomedical Engineering

作者： Ting, H. N. Lam, Y. M. Univ Malaya Fac Engn Dept Biomed Engn Kuala Lumpur 50603 Malaysia

ISBN: (纸本)9783642038815

This paper investigates the use of Neural Networks in recognizing Malay vowels of children in speaker-independent manner. Malay vowels are comprised of /a/, /e/, /./, /i/, /o/and /u/. Speech database is collected from 300 Malay children between seven and twelve years old. Each speaker contributes two samples per vowel sound. The speech database is organized equally into training set and test set. The speech sounds are sampled at 20 kHz with 16 bit resolution. A single frame of cepstral coefficients is extracted around the vowel onset point using linear predictive coding. Multi-Layer Perceptron (MLP) with one hidden-layer is used to train and recognize the vowel sounds. The output of the MLP consists of 6 neurons, which correspond to the 6 vowel sounds. Experiments are conducted to determine the optimal signal length of vowels, and hidden neuron number of MLP. A maximum recognition rate of 75.00% is achieved at signal length of 30ms and 35ms.

关键词： linear predictive coding Malay Vowels Multi-Layer Perceptron Neural Networks Speaker Independent

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ESTIMATION OF FRAME INDEPENDENT AND ENHANCEMENT COMPONENTS FOR SPEECH COMMUNICATION OVER PACKET NETWORKS

ESTIMATION OF FRAME INDEPENDENT AND ENHANCEMENT COMPONENTS F...

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2010 IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Giacobello, Daniele Murthi, Manohar N. Christensen, Mads Graesboll Jensen, Soren Holdt Moonen, Marc Aalborg Univ Dept Elect Syst Aalborg Denmark Miami Univ Dept Elect & Comp Engn Oxford OH 45056 USA Katholieke Univ Leuven Dept Elect Engn Leuven Belgium

ISBN: (纸本)9781424442966

In this paper, we describe a new approach to cope with packet loss in speech coders. The idea is to split the information present in each speech packet into two components, one to independently decode the given speech frame and one to enhance it by exploiting interframe dependencies. The scheme is based on sparse linear prediction and a redefinition of the analysis-by-synthesis process. We present Mean Opinion Scores for the presented coder with different degrees of packet loss and show that it performs similarly to frame dependent coders for low packet loss probability and similarly to frame independent coders for high packet loss probability. We also present ideas on how to make the coder work synergistically with the channel loss estimate.

关键词： Speech coding Voice over IP (VoIP) linear predictive coding analysis-by-synthesis

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