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NETWORK-BASED ISOLATED DIGIT RECOGNITION USING VECTOR QUANTIZATION

IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1985年第4期33卷 850-867页

作者： KOPEC, GE BUSH, MA Schlumberger Computer Aided Systems Research Palo Alto CA USA

This paper describes a network-based approach to speaker-independent digit recognition. The digits are modeled by a pronunciation network whose arcs represent classes of acoustic-phonetic segments. Each arc is associated with a matcher for rating an input speech interval as an example of the corresponding segment class. The matchers are based on vector quantization of LPC spectra. Recognition involves finding a minimum quantization distortion path through the network by dynamic programming. The system has been evaluated in an extensive series of speaker-independent isolated digit (one-nine, oh and zero) recognition experiments using a 225-talker. multidialect database developed by Texas Instruments (TI). The best recognizer configurations achieved accuracies of 97-99 percent on the TI database.

关键词： Vector quantization Hidden Markov models Pattern matching Databases Vocabulary Acoustic testing Speech linear predictive coding Dynamic programming Instruments

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On-line signature verification using LPC cepstrum and neural networks

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 1997年第1期27卷 148-153页

作者： Wu, QZ Jou, IC Lee, SY TELECOMMUN LABS CHUNGLITAIWAN

In this paper, an on-line signature verification scheme based on linear Prediction coding (LPC) cepstrum and neural networks is proposed. Cepstral coefficients derived from linear predictor coefficients of the writing trajectories are calculated as the features of the signatures. These coefficients are used as inputs to the neural networks. A number of single-output multilayer perceptrons (MLP's), as many as the number of words in the signature, are equipped for each registered person to verify the input signature. If the summation of output values of all MLP's is larger than verification threshold, the input signature is regarded as a genuine signature;otherwise, the input signature is a forgery. Simulations show that this scheme can detect the genuineness of the input signatures from our test database with an error rate as low as 4%.

关键词： Handwriting recognition linear predictive coding Cepstrum Neural networks Cepstral analysis Writing Trajectory Multilayer perceptrons Forgery Testing

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DESIGN OF A PITCH SYNCHRONOUS INNOVATION CELP CODER FOR MOBILE COMMUNICATIONS

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 1995年第1期13卷 31-41页

作者： MANO, K MORIYA, T MIKI, S OHMURO, H IKEDA, K IKEDO, J NIPPON TELEGRAPH & TEL PUBL CORP YOKOSUKA ELECT COMMUN LABS RADIO COMMUN SYST LABS YOKOSUKA KANAGAWA 23803 JAPAN

This paper describes the design of a speech coder called pitch synchronous innovation CELP (PSI-CELP) for low bit-rate mobile communications. PSI-CELP is based on CELP, but has more adaptive excitation structures. In voiced frames, instead of conventional random excitation vectors, PSI-CELP converts even the random excitation vectors to have pitch periodicity by repeating stored random vectors as well as by using an adaptive codebook. In silent, unvoiced, and transient frames, the coder stops using the adaptive codebook and switches to fixed random codebooks. The PSI-CELP coder also implements novel structures and techniques: an FIR-type perceptual weighting filter using unquantized LPC parameters, a random codebook with a conjugate structure trained to be robust against channel errors, codebook search with delayed decision, a gain quantization with sloped amplitude, and a moving average prediction coding of LSP parameters. Our speech coder is implemented by DSP chips. Its coded speech quality at 3.6 kb/s with 2.0 kb/s redundancy is comparable to that of the Japanese full-rate VSELP coder at 6.7 kb/s with 4.5 kb/s redundancy. The basic structure of this PSI-CELP coder has been chosen as the Japanese half-rate speech codec for digital cellular telecommunications.

关键词： Technological innovation Speech Redundancy Mobile communication Switches Filters linear predictive coding Robustness Delay Quantization

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AMPLITUDE OPTIMIZATION AND PITCH PREDICTION IN MULTIPULSE CODERS

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1989年第3期37卷 317-327页

作者： SINGHAL, S ATAL, BS AT&T BELL LABS ACOUST RES DEPTMURRAY HILLNJ 07974 AT&T BELL LABS DIV SPEECH & IMAGING PROC RESMURRAY HILLNJ 07974

Although the multipulse model is conceptually simple, the problem of locating the pulses is computationally complex. The authors discuss the basic multipulse model and describe a procedure to compute the excitation with optimally adjusted amplitudes. The algorithm provides a framework for computing multipulse excitation with varying degrees of optimization and computational complexity. The authors find that speech quality depends on the pulse rate. They also find that for the same quality, female speech requires a higher pulse rate than male speech. The pitch dependence can be reduced and speech quality improved for high-pitched speakers by incorporating long delay prediction in the multipulse model.< >

关键词： Speech synthesis Speech enhancement linear predictive coding Filters Bit rate Speech analysis Signal synthesis predictive models Speech coding White noise

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A split-band predictive coding system at 16 kb/s

A split-band predictive coding system at 16 kb/s

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： J. Welch C. Teacher Aeronutronic Ford Corporation Willow Grove Pa.

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Discriminative training for neural predictive coding applied to speech features extraction

Discriminative training for neural predictive coding applied...

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International Joint Conference on Neural Networks (IJCNN)

作者： M. Chetouani B. Gas J.L. Zarader C. Chavy Laboratoire des Instruments et Systèmes (d'IIe de France (LISIF) Université Paris VI Paris Cedex 05 FRANCE

We present a predictive neural network called neural predictive coding (NPC). This model is used for nonlinear discriminant features extraction applied to phoneme recognition. We validate the nonlinear prediction improvement of the NPC model. We also, present a new extension of the NPC model: NPC-3. In order to evaluate the performances of the NPC-3 model, we carried out a study of Darpa-Timit phonemes (in particular /b/, /d/, /g/ and /p/, /t/, /q/ phonemes) recognition. Comparisons with traditional coding methods are presented. We also show how an adaptative constraint allows improvements on the recognition task.

关键词： predictive coding Speech coding Feature extraction predictive models Nonlinear filters linear predictive coding Neural networks Speech recognition Mel frequency cepstral coefficient Instruments

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Vector predictive quantization of the spectral parameters for low rate speech coding

Vector predictive quantization of the spectral parameters fo...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Y. Shoham Dpt. of Signal Processing Research AT and T Bell Laboratories Inc. Murray Hill NJ USA

Vector predictive Quantization (VPQ) is proposed for coding the short-term spectral envelope of speech. The proposed VPQ scheme predicts the current spectral envelope from several past spectra, using a predictor codebook. The residual spectrum is coded by a residual codebook. The system operates in the log-spectral domain using a sampled version of the spectral envelope. Experimental results indicate a prediction gain in the range of 9 to 13 dB and an average log-spectral distance of 1.3 to 1.7 dB. Informal listening tests suggest that replacing the conventional scalar quantizer in a 4.8 Kbits/s CELP coder by a VPQ system allows a reduction of the rate assigned to the LPC data from 1.8 Kbits/s to 1.0 Kbits/s without any obvious difference in the perceptual quality.

关键词： Quantization Speech coding Vectors Speech analysis linear predictive coding Delay Switches Signal processing System testing Nonlinear filters

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Transform predictive coding of wideband speech signals

Transform predictive coding of wideband speech signals

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Juin-Hwey Chen Dongmei Wang Speech Coding Research Department AT and T Bell Laboratories Inc. Murray Hill NJ USA AT&T Bell Laboratories Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)0780331923

This paper presents a novel wideband speech coding algorithm called transform predictive coding (TPC). The main emphasis is on low complexity. TPC uses short-term and long-term prediction to remove the redundancy in speech. The prediction residual is quantized in the frequency domain based on a calculated noise masking threshold. In its simplest form, the TPC coder uses only open-loop quantization and therefore has a low complexity. A 16 kb/s full-duplex, open-loop TPC coder takes only 22% of the CPU load on a 150 MHz SGI Indy workstation and about 34% on a 90 MHz Pentium PC. The speech quality of TPC is almost transparent at 32 kb/s, very good at 24 kb/s, and acceptable at 16 kb/s. In the second half of the paper, we report our recent progress in using closed-loop quantization techniques to improve TPC output speech quality.

关键词： predictive coding Wideband Speech coding linear predictive coding Quantization Sampling methods Narrowband Workstations Speech processing Application software

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Adaptively Weighted L2-Minimization in predictive Speech coding

Adaptively Weighted L2-Minimization in Predictive Speech Cod...

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MILCOM, Military Communications Conference

作者： George Benke L. Thomas Ramsey Speech and Signal Processing Laboratory George town University McLean VA USA MITRE Corporation Speech and Signal Processing Laboratory McLean Virginia 22102

Current narrow-band speech coding algorithms (for transmission rates of 2400-4800 bits per second) typically excite linear filters with impulse trains to model voiced speech. The excitation function that would reproduce the speech exactly is the prediction residual; however, the usual selection of filter coefficients does not produce the most pulse-like prediction residuals. Thus other choices for filters offer an opportunity to improve the quality of narrow-band coding. The strategy of this paper is to minimize a dynamically weighted prediction error, to allow the largest values of the prediction residuals to be unconstrained and thus make the residuals more pulse-like. The idea was tested on voiced speech with over 300 predictive models, which contained quadratic and cubic terms as well as linear. Models with fewer than eight terms were not enhanced. The idea worked well with other models, particularly those with 8 to 11 terms.

关键词： predictive models Speech coding linear predictive coding Speech synthesis Narrowband Nonlinear filters Speech enhancement Speech processing Signal processing algorithms Testing

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Multilayered network for LPC based speech recognition

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 1998年第2期44卷 435-438页

作者： Patil, PB Coll Engn Dept Elect & Telecommun Badnera India

This paper presents efficient artificial neural network based linear predictive coding. Speech recognition is fundamentally pattern classification task. The objective is to input pattern, the speech and classify a sequence of patterns. The linear predictive coefficients of the slowly varying speech signals are stored. A feedforward network is determined by linear predictive coefficients. A three layered feedforward network was used with back propagation as the training algorithm. The network and learning techniques are proved for their correctness and applied to the problem of speech recognition. The suggested novel scheme yields results in finite accuracy and recognition performance.

关键词： linear predictive coding Speech recognition Finite impulse response filter Speech analysis Artificial neural networks Speech coding Low pass filters Pattern classification Signal analysis Frequency

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