Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.479721
K. Jemili, J. Westerkamp
A new signal estimation technique is introduced for highly non-stationary signals. The system uses the wavelet transform to extract time-frequency components of the signal plus noise, followed by a radial basis function neural network that adaptively estimates the underlying signal. The method is applied to the visual evoked potential (EP) signal, which is a transient signal corrupted by the ongoing electroencephalogram (EEG) noise, with a signal-to-noise ratio often less than -6 dB. The proposed system gives good time-varying estimates of the EP, while suppressing the on-going EEG.
{"title":"A kernel based system for the estimation of non-stationary signals","authors":"K. Jemili, J. Westerkamp","doi":"10.1109/ICASSP.1995.479721","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479721","url":null,"abstract":"A new signal estimation technique is introduced for highly non-stationary signals. The system uses the wavelet transform to extract time-frequency components of the signal plus noise, followed by a radial basis function neural network that adaptively estimates the underlying signal. The method is applied to the visual evoked potential (EP) signal, which is a transient signal corrupted by the ongoing electroencephalogram (EEG) noise, with a signal-to-noise ratio often less than -6 dB. The proposed system gives good time-varying estimates of the EP, while suppressing the on-going EEG.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131785762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.479398
Claudia Pateras, G. Dudek, R. Mori
In the domain of mobile robotic task execution under dialogue control, a primary goal is to identify the task target which is specified by a natural language description. A number of concepts are expressed in the user spoken language by vague terms like "the big box" and "very close to the door". We use fuzzy logic to map these vague terms onto the quantitative data collected by system sensors. Fuzziness may cause uncertainty in interpretation and, in particular, in understanding references. This uncertainty is abated by collecting additional information through queries to the user and autonomous sensing. Entropy is used to select the queries having the greatest discriminatory power among referent candidates. In addition, we examine the trade-off between querying, sensing and uncertainty. A framework to deal with each of these issues has been developed and is presented.
{"title":"Understanding referring expressions in a person-machine spoken dialogue","authors":"Claudia Pateras, G. Dudek, R. Mori","doi":"10.1109/ICASSP.1995.479398","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479398","url":null,"abstract":"In the domain of mobile robotic task execution under dialogue control, a primary goal is to identify the task target which is specified by a natural language description. A number of concepts are expressed in the user spoken language by vague terms like \"the big box\" and \"very close to the door\". We use fuzzy logic to map these vague terms onto the quantitative data collected by system sensors. Fuzziness may cause uncertainty in interpretation and, in particular, in understanding references. This uncertainty is abated by collecting additional information through queries to the user and autonomous sensing. Entropy is used to select the queries having the greatest discriminatory power among referent candidates. In addition, we examine the trade-off between querying, sensing and uncertainty. A framework to deal with each of these issues has been developed and is presented.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128954896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.480555
H. Belt, A. C. Brinker, F. Benders
A second-order IIR filter is considered as the basic component of an adaptive line enhancer (ALE). As a new feature, the bandwidth of the proposed ALE is adapted simultaneously with the center frequency. This leads to the possibility of combining the convergence speed and accuracy. The adaptation of the filter poles is controlled by a sign algorithm. The step sizes are chosen such that transients caused by the retuning of the filter are ensured to remain much smaller in amplitude than the response of the filter to the input signal. When the input signal consists of a sinusoid corrupted by wideband noise, an accurate frequency parameter estimate can be obtained with the algorithm given in the paper.
{"title":"Adaptive line enhancement using a second-order IIR filter","authors":"H. Belt, A. C. Brinker, F. Benders","doi":"10.1109/ICASSP.1995.480555","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.480555","url":null,"abstract":"A second-order IIR filter is considered as the basic component of an adaptive line enhancer (ALE). As a new feature, the bandwidth of the proposed ALE is adapted simultaneously with the center frequency. This leads to the possibility of combining the convergence speed and accuracy. The adaptation of the filter poles is controlled by a sign algorithm. The step sizes are chosen such that transients caused by the retuning of the filter are ensured to remain much smaller in amplitude than the response of the filter to the input signal. When the input signal consists of a sinusoid corrupted by wideband noise, an accurate frequency parameter estimate can be obtained with the algorithm given in the paper.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130931258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.479946
C. Mosquera, Pablo Irarrazabal, D. Nishimura
The paper addresses the properties of the noise in gridding reconstruction, an algorithm for reconstruction from nonuniform samples. Sequences with time-varying gradients, such as spiral or projection reconstruction (PR) techniques, are being increasingly used in magnetic resonance imaging (MRI). Since these techniques sample k-space nonuniformly, some kind of algorithm is needed to map the data onto a Cartesian frame to allow an inverse Fourier transform through an FFT. The authors present an analytical characterization of the image noise after gridding and inverse Fourier transform for the most popular sampling techniques used in MRI.
{"title":"Noise behavior in gridding reconstruction","authors":"C. Mosquera, Pablo Irarrazabal, D. Nishimura","doi":"10.1109/ICASSP.1995.479946","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479946","url":null,"abstract":"The paper addresses the properties of the noise in gridding reconstruction, an algorithm for reconstruction from nonuniform samples. Sequences with time-varying gradients, such as spiral or projection reconstruction (PR) techniques, are being increasingly used in magnetic resonance imaging (MRI). Since these techniques sample k-space nonuniformly, some kind of algorithm is needed to map the data onto a Cartesian frame to allow an inverse Fourier transform through an FFT. The authors present an analytical characterization of the image noise after gridding and inverse Fourier transform for the most popular sampling techniques used in MRI.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130937353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.480482
A. Mertins
Methods for switching filter coefficients and filter bank structures and methods for processing finite length signals are studied. The problem of designing optimal boundary and transition filters is solved directly via singular value decomposition (SVD) while the optimality criterion is based on the subband statistics. The optimized filters provide a good match between the subband statistics in the transition regions (and at the boundaries) to the statistics in the steady state. The filter banks considered are maximally decimated M-channel linear and non-linear phase (biorthogonal and paraunitary) filter banks with real filter coefficients.
{"title":"Time-varying and support preservative filter banks: design of optimal transition and boundary filters via SVD","authors":"A. Mertins","doi":"10.1109/ICASSP.1995.480482","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.480482","url":null,"abstract":"Methods for switching filter coefficients and filter bank structures and methods for processing finite length signals are studied. The problem of designing optimal boundary and transition filters is solved directly via singular value decomposition (SVD) while the optimality criterion is based on the subband statistics. The optimized filters provide a good match between the subband statistics in the transition regions (and at the boundaries) to the statistics in the steady state. The filter banks considered are maximally decimated M-channel linear and non-linear phase (biorthogonal and paraunitary) filter banks with real filter coefficients.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131200218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.479788
J. Bellegarda, P. D. Souza, D. Nahamoo, M. Padmanabhan, M. Picheny, L. Bahl
Speaker adaptation typically involves customizing some existing (reference) models in order to account for the characteristics of a new speaker. This work considers the slightly different paradigm of customizing some reference data for the purpose of populating the new speaker's space, and then using the resulting (augmented) data to derive the customized models. The data augmentation technique is based on the metamorphic algorithm first proposed in Bellegarda et al. [1992], assuming that a relatively modest amount of data (100 sentences) is available from each new speaker. This contraint requires that reference speakers be selected with some care. The performance of this method is illustrated on a portion of the Wall Street Journal task.
{"title":"Experiments using data augmentation for speaker adaptation","authors":"J. Bellegarda, P. D. Souza, D. Nahamoo, M. Padmanabhan, M. Picheny, L. Bahl","doi":"10.1109/ICASSP.1995.479788","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479788","url":null,"abstract":"Speaker adaptation typically involves customizing some existing (reference) models in order to account for the characteristics of a new speaker. This work considers the slightly different paradigm of customizing some reference data for the purpose of populating the new speaker's space, and then using the resulting (augmented) data to derive the customized models. The data augmentation technique is based on the metamorphic algorithm first proposed in Bellegarda et al. [1992], assuming that a relatively modest amount of data (100 sentences) is available from each new speaker. This contraint requires that reference speakers be selected with some care. The performance of this method is illustrated on a portion of the Wall Street Journal task.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133174454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.479623
T. Kosaka, S. Matsunaga, Mikio Kuraoka
This paper proposes a novel method for speaker-independent phone modeling based on the composition and clustering method (CCL) of speaker-dependent HMMs. In general, HMM phone models are trained by the Baum-Welch (B-W) algorithm. We, however, propose a speaker-independent phone modeling in which speaker-dependent (SD) HMMs are combined to form speaker-independent (SI) HMMs without parameter reestimation. Furthermore, by using this method, we investigate how different kinds of reference speakers influence the development of the SI models. The method is evaluated in Japanese phoneme and phrase recognition experiments. Results show that the performance of this method is similar to the conventional B-W algorithm's with great reduction of computational cost.
{"title":"Speaker-independent phone modeling based on speaker-dependent HMMs' composition and clustering","authors":"T. Kosaka, S. Matsunaga, Mikio Kuraoka","doi":"10.1109/ICASSP.1995.479623","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479623","url":null,"abstract":"This paper proposes a novel method for speaker-independent phone modeling based on the composition and clustering method (CCL) of speaker-dependent HMMs. In general, HMM phone models are trained by the Baum-Welch (B-W) algorithm. We, however, propose a speaker-independent phone modeling in which speaker-dependent (SD) HMMs are combined to form speaker-independent (SI) HMMs without parameter reestimation. Furthermore, by using this method, we investigate how different kinds of reference speakers influence the development of the SI models. The method is evaluated in Japanese phoneme and phrase recognition experiments. Results show that the performance of this method is similar to the conventional B-W algorithm's with great reduction of computational cost.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133503077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.479876
A. Sano, Y. Ashida, K. Ohnishi
The paper proposes a method for estimating the mixed spectrum which is composed of line and continuous spectra, the latter of which is characterized by an AR or ARMA noise model. Line spectrum is represented by multiple sinusoids. In order to avoid simultaneous minimization of a prediction error criterion with respect to all unknown parameters, the authors give an efficient iterative algorithm for estimating the frequencies of the sinusoids and other parameters separately. By adopting the genetic algorithm in choice of initial values of the AR or ARMA parameters in the iterative estimation, one can attain globally optimal estimates of unknown parameters. The frequency estimate is given by a modified Toeplitz approximation method using a shifted correlation matrix of observed signals. The effectiveness of the proposed algorithm is validated in numerical simulations.
{"title":"Estimation of mixed spectrum using genetic algorithm","authors":"A. Sano, Y. Ashida, K. Ohnishi","doi":"10.1109/ICASSP.1995.479876","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479876","url":null,"abstract":"The paper proposes a method for estimating the mixed spectrum which is composed of line and continuous spectra, the latter of which is characterized by an AR or ARMA noise model. Line spectrum is represented by multiple sinusoids. In order to avoid simultaneous minimization of a prediction error criterion with respect to all unknown parameters, the authors give an efficient iterative algorithm for estimating the frequencies of the sinusoids and other parameters separately. By adopting the genetic algorithm in choice of initial values of the AR or ARMA parameters in the iterative estimation, one can attain globally optimal estimates of unknown parameters. The frequency estimate is given by a modified Toeplitz approximation method using a shifted correlation matrix of observed signals. The effectiveness of the proposed algorithm is validated in numerical simulations.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133313072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.479986
M. Koschinski, H. Winkler, M. Lang
An efficient on-line recognition system for symbols within handwritten mathematical expressions is proposed. The system is based on the generation of a symbol hypotheses net and the classification of the elements within the net. The final classification is done by calculating the most probable path through the net under regard of the stroke group probabilities and the probabilities obtained by the symbol recognizer based on hidden Markov models.
{"title":"Segmentation and recognition of symbols within handwritten mathematical expressions","authors":"M. Koschinski, H. Winkler, M. Lang","doi":"10.1109/ICASSP.1995.479986","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479986","url":null,"abstract":"An efficient on-line recognition system for symbols within handwritten mathematical expressions is proposed. The system is based on the generation of a symbol hypotheses net and the classification of the elements within the net. The final classification is done by calculating the most probable path through the net under regard of the stroke group probabilities and the probabilities obtained by the symbol recognizer based on hidden Markov models.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133321971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.480464
Li-Chien Lin, C.-C. Jay Kuo
The bandlimited signal model has been widely used and bandlimited extrapolation has been extensively studied and applied in signal reconstruction. We examine a regularization technique for robust data extrapolation based on the wavelet representation. We first formulate the regularization problem and characterize the properties of its solution. Then, a practical iterative algorithm is proposed to achieve robust extrapolation.
{"title":"Regularized extrapolation of noisy data with a wavelet signal model","authors":"Li-Chien Lin, C.-C. Jay Kuo","doi":"10.1109/ICASSP.1995.480464","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.480464","url":null,"abstract":"The bandlimited signal model has been widely used and bandlimited extrapolation has been extensively studied and applied in signal reconstruction. We examine a regularization technique for robust data extrapolation based on the wavelet representation. We first formulate the regularization problem and characterize the properties of its solution. Then, a practical iterative algorithm is proposed to achieve robust extrapolation.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133653709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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