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Speaker-Independent Malay Vowel Recognition of Children using Neural Networks

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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Adaptive Total Least Squares Based Speech Prediction 6

Adaptive Total Least Squares Based Speech Prediction

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6th International Conference on Information Technology and Multimedia (ICIM)

作者： Javed, Shazia Ahmad, Noor Atinah Univ Sains Malaysia Sch Math Sci George Town 11800 Malaysia

ISBN: (纸本)9781479954230

In this paper, an instantaneous total error based adaptive linear predictor is presented for linear predictive coding (LPC) of speech signals. In LPC, the speech signal is predicted by a linear combination of delayed input signals that are contaminated by noise. For this reason, total least mean squares (T-LMS) algorithm is used to decode the noisy input signals and to predict a speech signal. A compressed speech prediction is done when the mean squares total error is minimized, showing the efficiency of T-LMS based LPC model. Experimental results are recorded for different values of signal to noise ratio (SNR) of the input signals, and a comparative study is presented with instantaneous error squares based adaptive filter. These results show the preference of proposed predictor over the other.

关键词： linear predictive coding adaptive filter total least squares

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Improved Frame Loss Recovery Using Closed-Loop Estimation of Very Low Bit Rate Side Information

Improved Frame Loss Recovery Using Closed-Loop Estimation of...

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9th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2008)

作者： Gournay, Philippe Univ Sherbrooke Speech & Audio Res Grp Sherbrooke PQ J1K 2R1 Canada

ISBN: (纸本)9781615673780

In CELP coders, the past excitation signal used to build the adaptive codebook is known to be the main source of error propagation when a frame is lost. This paper presents a novel resynchronization technique using very low bit rate side information to correct the past excitation signal after a frame erasure, the novelty being that the correction is computed in a closed loop fashion, based on the actual error introduced by the concealment. Subjective test results show that this approach is a promising area for future research on frame loss recovery.

关键词： speech codecs linear predictive coding error correction robustness

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A Comparative Performance Study of Several Pitch Detection Algorithms

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IEEE Transactions on Acoustics, Speech, and Signal Processing 1976年第5期24卷 399-418页

作者： Rabiner, Lawrence R. Cheng, Michael J. Rosenberg, Aaron E. Mcgonegal, Carol A. Bell Laboratories Murray Hill NJ 07974 United States

A comparative performance study of seven pitch detection algorithms was conducted. A speech data base, consisting of eight utterances spoken by three males, three females, and one child was constructed. Telephone, close talking microphone, and wideband recordings were made of each of the utterances. For each of the utterances in the data base, a “standard” pitch contour was semiautomatically measured using a highly sophisticated interactive pitch detection program. The “standard” pitch contour was then compared with the pitch contour that was obtained from each of the seven programmed pitch detectors. The algorithms used in this study were 1) a center clipping, infinite-peak clipping, modified autocorrelation method (AUTOC), 2) the cepstral method (CEP), 3) the simplified inverse filtering technique (SIFT) method, 4) the parallel processing time-domain method (PPROC), 5) the data reduction method (DARD), 6) a spectral flattening linear predictive coding (LPC) method, and 7) the average magnitude difference function (AMDF) method. A set of measurements was made on the pitch contours to quantify the various types of errors which occur in each of the above methods. Included among the error measurements were the average and standard deviation of the error in pitch period during voiced regions, the number of gross errors in the pitch period, and the average number of voiced-unvoiced classification errors. For each of the error measurements, the individual pitch detectors could be rank ordered as a measure of their relative performance as a function of recording condition, and pitch range of the various speakers. Performance scores are presented for each of the seven pitch detectors based on each of the categories of error. Copyright © 1976 by The Institute of Electrical and Electronics Engineers, Inc.

关键词： Detection algorithms Detectors Measurement standards linear predictive coding Speech Telephony Microphones Wideband Filtering algorithms Autocorrelation

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Low-Complexity Vector Precoding for Multi-user Systems

Low-Complexity Vector Precoding for Multi-user Systems

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46th Asilomar Conference on Signals, Systems and Computers

作者： Barrenechea, Maitane Burg, Andreas Mendicute, Mikel Univ Mondragon Dept Elect & Comp Sci Arrasate Mondragon 20500 Spain Ecole Polytech Fed Lausanne Inst Elect Engn CH-1015 Lausanne Switzerland

ISBN: (纸本)9781467350518

Vector precoding enables non-cooperative signal acquisition in the multi-user broadcast channel. The performance advantage with respect to the more straightforward linear precoding algorithms comes as a consequence of an added perturbation vector, which enhances the properties of the precoded signal. Nevertheless, the computation of the perturbation signal entails a search for the closest point in an infinite lattice, which is known to belong in the class of non-deterministic polynomial-time hard (NP-hard) problems. This contribution presents a novel tree search scheme that achieves an error-rate performance that is close to the optimum given by the sphere encoder, but with a significantly simpler tree-search structure that only considers the most promising nodes for expansion. With the aim of better showcasing the low-complexity and simple datapath of the proposed tree-search technique, its hardware implementation on a 65 nm ASIC target device has been performed.

关键词： computational complexity linear predictive coding polynomials signal detection

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DSP restoration techniques for audio

DSP restoration techniques for audio

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IEEE International Conference on Image Processing (ICIP 2007)

作者： Moorer, James A. Adobe Syst Inc San Jose CA 95110 USA

ISBN: (纸本)9781424414369

The CD revolution of 1984 unleashed a massive campaign of rerelease of vintage analog recordings. To their collective horror, record labels found that many of the original master recordings had deteriorated. Often the only existing copy of a recording was a vinyl pressing. This rush to release beloved music in the new digital form spawned intense interest in digital methods of restoring these old recordings. A number of DSP techniques have been developed to give new life to these recordings. This paper is a survey of some of those methods.

关键词： music signal restoration signal processing linear predictive coding Wiener filtering

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Voiced-Unvoiced Classification of Speech Using a Neural Network Trained with LPC Coefficients

Voiced-Unvoiced Classification of Speech Using a Neural Netw...

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International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)

作者： Struwe, Kevin Univ Rostock Inst Appl Microelect & Comp Engn D-18051 Rostock Germany

ISBN: (纸本)9781509065363

Voiced-Unvoiced classification (V-UV) is a well understood but still not perfectly solved problem. It tackles the problem of determining whether a signal frame contains harmonic content or not. This paper presents a new approach to this problem using a conventional multi-layer perceptron neural network trained with linear predictive coding (LPC) coefficients. LPC is a method that results in a number of coefficients that can be transformed to the envelope of the spectrum of the input frame. As a spectrum is suitable for determining the harmonic content, so are the LPC-coefficients. The proposed neural network works reasonably well compared to other approaches and has been evaluated on a small dataset of 4 different speakers.

关键词： Neural Network linear predictive coding Voiced-Unvoiced Classification Cochlear Implants

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Audio Watermark Detection Using Undetermined ICA

Audio Watermark Detection Using Undetermined ICA

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8th International Conference on Independent Component Analysis and Signal Separation

作者： Seok, Jongwon Malik, Hafiz Changwon Natl Univ Dept Informat & Commun Engn Chang Won Kyongnam South Korea Univ Michigan Dept Elect & Com Dearborn MI USA

ISBN: (纸本)9783642005985

This paper presents a blind watermark detection scheme for additive watermark embedding model. The proposed estimation-correlation-based watermark detector first estimates the embedded watermark by exploiting non-Gaussian of the real-world audio signal and the mutual independence between the host-signal and the embedded watermark and then a correlation-based detector is used to determine the presence or the absence of the watermark. For watermark estimation, blind Source separation (BSS) based on underdetermined independent component analysis (UICA) is used. Low watermark-to-signal ratio (WSR) is one to the limitations of blind detection for additive embedding model. The proposed detector uses two-stage processing to improve WSR at the blind detector;first stage removes the audio spectrum from the watermarked audio signal using linear predictive (LP) filtering and the second stage uses resulting residue from the LP filtering stage to estimate the embedded watermark using BSS based on UICA. Simulation results show that the proposed detector performs significantly better than existing estimation-correlation-based detection schemes.

关键词： Audio Watermark Detection Blind Source Separation Mean-Field Approaches Independent Component Analysis linear predictive coding

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Scalable innovation coding

Scalable innovation coding

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Nordén, F Hedelin, P Chalmers Univ Technol Informat Theory Lab SE-41296 Gothenburg Sweden

ISBN: (纸本)0780374029

Low-complexity scalable methods are of importance to achieve multi-rate and variable rate speech coding. Adopting the CELP concept, we focus on the innovation coding, suggesting an adaptive companding VQ. We present a scheme having essentially no increase in complexity as the rate is increased, yet having a competitive distortion performance. This is acheived by avoiding an explicit perceptual filtering step in the coding, still utilizing close to optimal VQ techniques in a perceptual domain. Subjective and objective distortion performance is better than, or in parity with, that of conventional white noise excitation methods or multipulse structures.

关键词： linear predictive coding speech coding vector quantisation compandors scalable innovation coding multi-rate coding variable rate coding speech coding CELP adaptive companding VQ perceptual domain objective distortion performance subjective distortion performance

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Adaptive selection of lag-window shape for linear predictive analysis in the 3GPP EVS codec

Adaptive selection of lag-window shape for linear predictive...

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3rd IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Kamamoto, Yutaka Moriya, Takehiro Harada, Noboru NTT Corp NTT Commun Sci Labs Atsugi Kanagawa Japan

ISBN: (纸本)9781479975914

Lag windowing has long been used for the auto-correlation method of linear predictive (LP) analysis to prevent possible instability of the synthesis filter with the obtained coefficients. We have investigated the lag-window shape in terms of the trade-offs between stability and the coding efficiency. On the basis of these investigations, we have devised an adaptive selection scheme in which the window shape selected depends on the periodicity of the signal. This scheme has proven to be effective for LP analysis to enhance the coding efficiency in both time and frequency domains in general. This scheme has thus been included in the speech and audio coding schemes of the newly established 3GPP EVS codec standard.

关键词： lag-window linear predictive coding fundamental frequency pitch-gain 3GPP EVS codec

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