{"title":"A statistical study of a regularized method for long auto-regressive spectral estimation","authors":"J. Giovannelli, G. Demoment","doi":"10.1109/ICASSP.1993.319613","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319613","url":null,"abstract":"The authors address the problem of power spectral density estimation of time series with auto-regressive (AR) models when only a short span of data is available for analysis. The AR coefficients are estimated through a regularized method proposed by G. Kitagawa and W. Gersch (1985). An experimental study of this method and a comparison with the classical least squares (LS) method are outlined. The principles of the statistical study and computation results are presented.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128546556","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}
{"title":"Multi-speaker/speaker-independent architectures for the multi-state time delay neural network","authors":"H. Hild, A. Waibel","doi":"10.1109/ICASSP.1993.319284","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319284","url":null,"abstract":"The authors present an improved multistate time delay neural network (MS-TDNN) for speaker-independent, connected letter recognition which outperforms an HMM (hidden Markov model) based system (SPHINX) and previous MS-TDNNs. They also explore new network architectures with internal speaker models. Four different architectures characterized by an increasing number of speaker-specific parameters are introduced. The speaker-specific parameters can be adjusted by automatic speaker identification or by speaker adaptation, allowing for tuning-in to a new speaker. Both methods lead to significant improvements over the straightforward speaker-independent architecture. Even unsupervised tuning-in (speech is unlabeled) works well.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128940227","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}
{"title":"A compound primitive operator approach to the realisation of video sub-band filter banks","authors":"D. Bull, G. Wacey, J. Stone, J. M. Soloff","doi":"10.1109/ICASSP.1993.319141","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319141","url":null,"abstract":"A new video subband filtering architecture appropriate for VLSI implementation is presented. The system employs a reduced complexity multiply-accumulate structure realized using an extension to the primitive operator graph synthesis technique. This, in conjunction with a data multiplexing regime which implements a two channel quadrature mirror filter on a single finite impulse response (FIR) structure, has facilitated the fabrication of a sixty-four subband coder/decoder on a single gate array. The circuitry is reconfigurable, allowing vertical and horizontal filtering in analysis or synthesis mode. The authors describe the conceptual development of the new approach and present novel architectural features associated with its implementation. Also included are complexity comparisons with conventional approaches.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129014999","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}
{"title":"A new speech recognition method based on VQ-distortion measure and HMM","authors":"S. Nakagawa, Hideyuki Suzuki","doi":"10.1109/ICASSP.1993.319401","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319401","url":null,"abstract":"A speech recognition method which integrates a VQ (vector quantization)-distortion measure and a discrete HMM (hidden Markov model) is proposed. This VQ-distortion-based HMM uses a VQ-distortion measure at each state instead of the discrete output probability used by a discrete HMM. Although this method is regarded as a refined version of the VQ-distribution based recognition method proposed by D.K. Burton et al (IEEE Trans. vol. ASSP-33, no.4, p.837-49 of 1985), it is also considered as a special case of a mixtured distribution density HMM. The authors describe the relationship between the VQ-distortion-based HMM and conventional HMMs, and compare their speech recognition performance through experiments on speaker-dependent digit recognition. A recognition accuracy of 100% using the new method was obtained.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129251707","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}
{"title":"The biorthonormal filter bank convolver, and application in low sensitivity FIR filter structures","authors":"See-May Phoong, P. Vaidyanathan","doi":"10.1109/ICASSP.1993.319461","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319461","url":null,"abstract":"It was shown by P.P. Vaidyanathan (1993) that in the case of orthonormal and biorthonormal filter banks one can convolve two signals x(n) and g(n) by directly convolving the subband signals and combining the results. In the present work, this result is further generalized. The coding gain for a biorthonormal convolver is also derived. As an application, a novel low-sensitivity FIR (finite impulse response) filter structure is derived from the convolution theorem. This FIR filter structure is shown to be attractive when the filter coefficients are quantized to low bit rate. For a fixed word length implementation, the deterministic coding gain over direct convolution for the cases of quantizing the input signal and filter coefficients is considered.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124669145","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}
{"title":"On the estimation of hyperparameters in Bayesian approach of solving inverse problems","authors":"A. Mohammad-Djafari","doi":"10.1109/ICASSP.1993.319857","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319857","url":null,"abstract":"The author proposes a new view on the estimation of hyperparameters (the parameters of the prior law) when a Bayesian approach with maximum entropy (ME) priors is used to solve the inverse problems which arise in signal and image reconstruction and restoration problems. In particular, he compares two methods; the expectation maximization (EM) algorithm which aims to find the marginalized maximum likelihood (MML) estimate and the generalized maximum likelihood (GML). Some simulation results with application in image restoration are provided to show the performance of the GML method. The convergence of the present implementation of the GML method depends essentially on the initialization of the hyperparameters and the image. If one starts with good initial values, the GML works satisfactorily.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130411266","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}
{"title":"Partial parsing as a robust parsing strategy","authors":"P. Baggia, C. Rullent","doi":"10.1109/ICASSP.1993.319247","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319247","url":null,"abstract":"The authors describe a robust parsing strategy where partial parsing is seen not as a back-up strategy, but as the normal mode of operation of the parser. The goal is to extract from a lattice of word hypotheses the information content of an utterance using the minimum amount of linguistic knowledge. A system for accessing a train timetable in Italian has been implemented and tested on a test set of 600 utterances. The proposed approach to partial parsing represents a compromise between the need for accurate linguistic knowledge to avoid misunderstanding and the need to reduce the amount of linguistic knowledge to be used by the system, given its high development cost and the related reduction in efficiency and robustness. The approach makes it possible to increase robustness to spontaneous speech and to reduce the effect of limitations in the syntactic/semantic coverage of the grammar. The experiments show that the method has a good ability to extract correctly many concepts even when recognition problems do not make it possible to extract all of them.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130516640","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}
{"title":"Subpixel accuracy image registration by spectrum cancellation","authors":"S. P. Kim, Wen-Yu Su","doi":"10.1109/ICASSP.1993.319770","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319770","url":null,"abstract":"An image registration algorithm which achieves subpixel accuracy using a frequency-domain technique is proposed. This approach is efficient compared with the conventional approaches based on interpolation or correlations in the spatial/frequency domain. This approach can achieve subpixel accuracy registration even when images contain aliasing errors due to undersampling. The FFTs (fast Fourier transforms) of the images have computational complexities smaller than the interpolation or convolution computations by orders of magnitude. The accuracy of the proposed approach is demonstrated through computer simulations for different types of images.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126653186","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}
{"title":"Maximum likelihood estimation of spectral moments at low signal to noise ratios","authors":"J. Bioucas-Dias, J. Leitão","doi":"10.1109/ICASSP.1993.319616","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319616","url":null,"abstract":"A maximum likelihood (ML) estimator of spectral moments of a zero-mean complex Gaussian vector process, immersed in independent additive Gaussian white noise is proposed. The covariance function is assumed known in advance, apart from a vector of parameters which are related with the spectral moments. Since the maximization of the log-likelihood function yields a highly cumbersome algorithm, a more manageable objective function is considered. This objective function provides estimates consistent with probability one, and that are asymptotically efficient, which are the asymptotic properties of the ML estimator. For finite sample sizes, and signal to noise ratio (SNR) tending to zero, the results are similar to the ML results. Statistical characterization and simulation examples are presented.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126962011","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}
{"title":"Scalable video coding using 3-D subband velocity coding and multirate quantization","authors":"E. Chang, A. Zakhor","doi":"10.1109/ICASSP.1993.319876","DOIUrl":"https://doi.org/10.1109/ICASSP.1993.319876","url":null,"abstract":"The authors have developed a class of scalable video compression algorithms capable of producing one compressed full-resolution video bit stream with various subsets corresponding to different resolutions/rates of the same video sequence. The strategy is to use velocity-based 3-D subband coding to decompose the video into different spatiotemporal resolutions, and to multirate quantize each subband in order to achieve a large number of bit rates with fine granularity. This scheme results in a minimum rate of 55 kbit/s and maximum rate of 3.024 Mbit/s for the 'Football' sequence with 33 intermediate rates. The MSE (mean square error) of the proposed system is 11-17% higher than that of MPEG1 (Motion Picture Expert Group 1) for the three bit rates tested.<<ETX>>","PeriodicalId":428449,"journal":{"name":"1993 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130660020","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}