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Forward-Decoding Kernel-Based Phone Sequence Recognition 02

Forward-Decoding Kernel-Based Phone Sequence Recognition

引用

Annual Conference on Neural Information processing Systems

作者： Shantanu Chakrabartty Gert Cauwenberghs Center for Language and Speech Processing Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD 21218

ISBN: (纸本)0262025507

Forward decoding kernel machines (FDKM) combine large-margin classifiers with hidden Markov models (HMM) for maximum a posteriori (MAP) adaptive sequence estimation. State transitions in the sequence are conditioned on observed data using a kernel-based probability model trained with a recursive scheme that deals effectively with noisy and partially labeled data. Training over very large datasets is accomplished using a sparse probabilistic support vector machine (SVM) model based on quadratic entropy, and an on-line stochastic steepest descent algorithm. For speaker-independent continuous phone recognition, FDKM trained over 177, 080 samples of the TIMIT database achieves 80.6% recognition accuracy over the full test set, without use of a prior phonetic language model.

关键词： Telephone modelling languages Support Vector Network observational data label data steepest descent algorithm speaker-independent

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Reducing pronunciation lexicon confusion and using more data without phonetic transcription for pronunciation modeling 7

Reducing pronunciation lexicon confusion and using more data...

引用

7th International Conference on Spoken language processing, ICSLP 2002

作者： Zheng, Fang Song, Zhanjiang Fung, Pascale Byrne, William Center of Speech Technology State Key Lab of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua Univ. Beijing100084 China Department of Electrical and Electronic Engineering Hong Kong Univ. of Science and Technology Hong Kong Center for Language and Speech Processing Johns Hopkins Univ. United States Beijing D-Ear Technologies Co. Ltd. China

The multiple-pronunciation lexicon (MPL) is very important to model the pronunciation variations for spontaneous speech recognition. But the introduction of MPL brings out two problems. First, the MPL will increase the among-lexicon confusion and degrade the recognizer's performance. Second, the MPL needs more data with phonetic transcription so as to cover as many surface forms as possible. Accordingly, two solutions are proposed, they are the context-dependent weighting method and the iterative forced-alignment based transcription method. The use of them can compensate what the MPL causes and improve the overall performance. Experiments across a naturally spontaneous speech database show that the proposed methods are effective and better than other methods.

关键词： Iterative methods

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Discriminative speaker adaptation with conditional maximum likelihood linear regression 7

Discriminative speaker adaptation with conditional maximum l...

引用

7th European Conference on speech Communication and Technology - Scandinavia, EUROspeech 2001

作者： Gunawardana, Asela Byrne, William Department of Electrical and Computer Engineering Center for Language and Speech Processing Johns Hopkins University 3400 N. Charles St. BaltimoreMD21218 United States

ISBN: (纸本)8790834100

We present a simplified derivation of the extended Baum-Welch procedure, which shows that it can be used for Maximum Mutual Information (MMI) of a large class of continuous emission density hidden Markov models (HMMs). We use the extended Baum-Welch procedure for discriminative estimation of MLLR-Type speaker adaptation transformations. The resulting adaptation procedure, termed Conditional Maximum Likelihood Linear Regression (CMLLR), is used successfully for supervised and unsupervised adaptation tasks on the Switchboard corpus, yielding an improvement over MLLR. The interaction of unsupervised CMLLR with segmental minimum Bayes risk lattice voting procedures is also explored, showing that the two procedures are complimentary.

关键词： Hidden Markov models

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Automatic selection of transcribed training material

Automatic selection of transcribed training material

引用

IEEE Workshop on Automatic speech Recognition and Understanding

作者： T.M. Kamm G.G.L. Meyer Center for Language and Speech Processing Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

Conventional wisdom says that incorporating more training data is the surest way to reduce the error rate of a speech recognition system. This, in turn, guarantees that speech recognition systems are expensive to train, because of the high cost of annotating training data. We propose an iterative training algorithm that seeks to improve the error rate of a speech recognizer without incurring additional transcription cost, by selecting a subset of the already available transcribed training data. We apply the proposed algorithm to an alpha-digit recognition problem and reduce the error rate from 10.3% to 9.4% on a particular test set.

关键词： speech recognition Error analysis Iterative algorithms Training data Costs System testing Natural languages speech processing Data mining Automatic speech recognition

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Hybrid support vector machine/hidden Markov model approach for continuous speech recognition

Hybrid support vector machine/hidden Markov model approach f...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： S. Chakrabartty G. Singh G. Cauwenberghs Center for Language and Speech processing Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

A hybrid support vector machine (SVM) and hidden Markov model (HMM) approach is proposed for designing continuous speech recognition systems. Using novel properties of SVMs and combining them with HMMs one can obtain models that map easily to hardware and lead to more modular and scalable design. The overall architecture of the proposed system is based on the MAP (maximum a posteriori) framework which offers a direct, feedforward recognition model. The SVMs generate smooth estimates of local transition probabilities in the HMM, conditioned on the acoustic inputs. The transition probabilities are then used to estimate the global posterior probabilities of HMM state sequences. A parallel architecture that implements a simple speech recognition model in real-time is presented.

关键词： Support vector machines Hidden Markov models speech recognition Hardware Natural languages Feedforward systems State estimation Parallel architectures Silicon Control systems

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Monaural separation of independent acoustical components

Monaural separation of independent acoustical components

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： G. Cauwenberghs Department of Electrical and Computer Engineering and Center for Language and Speech Processing Johns Hopkins University Baltimore MD USA

The problem of blindly separating signal mixtures with fewer mixture components than independent signal sources is mathematically ill-defined, and requires suitable prior information on the nature of the sources. Recently, it has been shown that sparse methods for function approximation using a Laplacian prior can be effective, but the method fails to separate a single mixture without further prior information. Other techniques track harmonics, but assume separability in the time-frequency domain. We show that a measure of temporal and spectral coherence provides an effective cue for separating independent acoustical or sonar sources, in the absence of spatial cues in the monaural case. The technique is shown to successfully separate single mixtures of sources with significant spectral overlap.

关键词： Signal processing Independent component analysis Time frequency analysis Data mining Laplace equations Acoustic measurements Sonar measurements Adaptive signal processing Biomedical signal processing Interference

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Growth Transform of A Sum of Rational Functions and Its Application in Estimating HMM Parameters 5

Growth Transform of A Sum of Rational Functions and Its Appl...

引用

5th International Conference on Spoken language processing, ICSLP 1998

作者： Luo, Xiaoqiang Center for Language and Speech Processing Department of Electrical and Computer Engineering The Johns Hopkins University BaltimoreMD21218 United States

Gopalakrishnan et al [1] described a method called "growth transform" to optimize rational functions over a domain, which has been found useful to train discriminatively Hidden Markov Models(HMM) in speech recognition [5, 6, 9]. A sum of rational functions is encountered when the contributions from other HMM states are weighted in estimating Gaussian parameters of a state, and the weights are optimized using cross-validation [8]. We will show that the growth transform of a sum of rational functions can be obtained by computing term-wise gradients and term-wise function values, as opposed to forming first a single rational function and then applying the result in [1]. This is computationally advantageous when the objective function consists of many rational terms and the dimensionality of the domain is high. We also propose a gradient directed search algorithm to find the appropriate transform constant C. © 1998. 5th International Conference on Spoken language processing, ICSLP 1998. All rights reserved.

关键词： Rational functions

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A simulator construction methodology for the Shiva multiprocessor system 3

A simulator construction methodology for the Shiva multiproc...

引用

3rd International Conference on Algorithms and Architectures for Parallel processing, ICA3PP 1997

作者： Slomka, S. Sterzl, K.F. Lakshmi Narasimhan, V. Speech Research Laboratory Signal Processing Research Center Queensland University of Technology GPO Box 2434 BrisbaneQLD4001 Australia PA SE Research Laboratory Department of Electrical and Computer Engineering University of Queensland St. LuciaQLD4072 Australia Information Management Group ITD DSTO SalisburySA5108 Australia

ISBN: (纸本)0780342291

This paper describes a simulator for the Shiva multiprocessor system and the simulator construction methodology (SCM) used in its creation. The SCM, based on the active functional unit (AFU) construct, is a modern SCM which is flexible, accurate, fast, easy to use, capable of dynamic reconfigurability at run-time, and most of all simple and capable of quick simulator construction. The AFU SCM is capable of all these things through the use of object-oriented software techniques. The Shiva simulator constructed using the AFU SCM is program-driven and capable of micro and macro architectural simulation. © 1997 IEEE.

关键词： Multiprocessing systems

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A simulator construction methodology for the Shiva multiprocessor system

A simulator construction methodology for the Shiva multiproc...

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IEEE International Conference on Algorithms and Architectures for Parallel processing (ICAP)

作者： S. Slomka K.F. Sterzl V. Lakshmi Narasimhan The Speech Research Laboratory Signal Processing Research Center Queensland University of Technology Brisbane QLD Australia The PA SE Research Laboratory Department of Electrical and Computer Engineering University of Queensland Saint Lucia QLD Australia Information Management Group ITD DSTO Salisbury SA Australia

关键词： Multiprocessing systems Computational modeling Object oriented modeling Signal generators Laboratories computer simulation Discrete event simulation speech processing Signal processing Information management

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A circuit model of hair-cell transduction for temporal processing and auditory feature extraction

A circuit model of hair-cell transduction for temporal proce...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： N. Kumar G. Cauwenberghs A.G. Andreou Center for Language and Speech Processin Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

We present a novel low-power circuit for level crossing interval measurements on continuous-time auditory signals, as obtained from the outputs of an analog cochlear filter bank. The circuit achieves immediate response for a given signal in the audio frequency range. Experimental results from a fabricated array of 9 level crossing transducers demonstrate frequency-to-voltage conversion over a range covering the audio band, with less than 120 /spl mu/W of power dissipated per cell from a 5 V supply.

关键词： Feature extraction Voltage Frequency Time measurement Integrated circuit measurements Capacitors Signal processing Noise measurement Very large scale integration Signal resolution

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