Pub Date : 1995-05-09DOI: 10.1109/ICASSP.1995.480057
J. Farison, M. Quweider
A novel technique to classify image edge blocks is presented. It is based on defining a set of linearly independent signature vectors with a one to one association with the edge classes. A set of filter vectors emphasizing the projection of one signature vector and suppressing all others is then designed. Classification of an input edge block is accomplished by choosing the index of the filter with the maximum output magnitude. Coded images based on this classification are shown to preserve their quality and enjoy considerable dB gain over two existing methods. The new technique can be easily implemented using a parallel algorithm with little storage requirement.
{"title":"Image edge block classification for CVQ using the SD filter","authors":"J. Farison, M. Quweider","doi":"10.1109/ICASSP.1995.480057","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.480057","url":null,"abstract":"A novel technique to classify image edge blocks is presented. It is based on defining a set of linearly independent signature vectors with a one to one association with the edge classes. A set of filter vectors emphasizing the projection of one signature vector and suppressing all others is then designed. Classification of an input edge block is accomplished by choosing the index of the filter with the maximum output magnitude. Coded images based on this classification are shown to preserve their quality and enjoy considerable dB gain over two existing methods. The new technique can be easily implemented using a parallel algorithm with little storage requirement.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"38 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":"123815147","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.1995.479397
K. Ries, F. D. Buø, Ye-Yi Wang
The perplexity of corpora is typically reduced by more than 30% compared to advanced n-gram models by a new method for the unsupervised acquisition of structural text models. This method is based on new algorithms for the classification of words and phrases from context and on new sequence finding procedures. These procedures are designed to work fast and accurately on small and large corpora. They are iterated to build a structural model of a corpus. The structural model can be applied to recalculate the scores of a speech recogniser and improves the word accuracy. Further applications such as preprocessing for neural networks and (hidden) Markov models in language processing, which exploit the structure finding capabilities of this model, are proposed.
{"title":"Improved language modelling by unsupervised acquisition of structure","authors":"K. Ries, F. D. Buø, Ye-Yi Wang","doi":"10.1109/ICASSP.1995.479397","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479397","url":null,"abstract":"The perplexity of corpora is typically reduced by more than 30% compared to advanced n-gram models by a new method for the unsupervised acquisition of structural text models. This method is based on new algorithms for the classification of words and phrases from context and on new sequence finding procedures. These procedures are designed to work fast and accurately on small and large corpora. They are iterated to build a structural model of a corpus. The structural model can be applied to recalculate the scores of a speech recogniser and improves the word accuracy. Further applications such as preprocessing for neural networks and (hidden) Markov models in language processing, which exploit the structure finding capabilities of this model, are proposed.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"43 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":"123918374","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.1995.479760
W. Padgett
The detection of nonstationary random signals is an important sonar problem which also has potential applications in diverse areas such as biomedical signal processing and spread spectrum communications. The primary problem with applying a powerful test like the generalized likelihood ratio test (GLRT) is the computational effort required to search for the maximum likelihood model parameters for the observed signal. The computation required is multiplied many times over when a signal parameter is nonstationary. A computationally efficient detector of nonstationary Gaussian random signals based on the GLRT was presented at ICASSP94 [1]. A slightly enhanced version of the detector is described below, along with new simulation results demonstrating that the detector performs nearly optimally and is quite robust to signal model inaccuracy.
{"title":"Performance analysis of a detector for nonstationary random signals","authors":"W. Padgett","doi":"10.1109/ICASSP.1995.479760","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479760","url":null,"abstract":"The detection of nonstationary random signals is an important sonar problem which also has potential applications in diverse areas such as biomedical signal processing and spread spectrum communications. The primary problem with applying a powerful test like the generalized likelihood ratio test (GLRT) is the computational effort required to search for the maximum likelihood model parameters for the observed signal. The computation required is multiplied many times over when a signal parameter is nonstationary. A computationally efficient detector of nonstationary Gaussian random signals based on the GLRT was presented at ICASSP94 [1]. A slightly enhanced version of the detector is described below, along with new simulation results demonstrating that the detector performs nearly optimally and is quite robust to signal model inaccuracy.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"33 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":"123985980","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.1995.479402
S. Sagayama, Satoshi Takahashi
This paper describes an algorithm for reducing the amount of arithmetic operations in the likelihood computation of continuous mixture HMM (CMHMM) with diagonal covariance matrices while retaining high performance. The key points are the use of the scalar quantization of the input observation vector components and table look-up. These make multiplication, squaring and division operations entirely unnecessary in the whole HMM computation (i.e., output probability calculation and trellis/Viterbi computation). It is experimentally proved in an large-vocabulary isolated word recognition task that scalar quantization into no less than 16 levels does not cause significant degradation in the speech recognition performance. Scalar quantization is also utilized in the computation truncation for unlikely distributions; the total number of distribution likelihood computations can be reduced by 66% with only a slight performance degradation. This "multiplication-free" HMM algorithm has high potentiality in speech recognition applications on personal computers.
{"title":"On the use of scalar quantization for fast HMM computation","authors":"S. Sagayama, Satoshi Takahashi","doi":"10.1109/ICASSP.1995.479402","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479402","url":null,"abstract":"This paper describes an algorithm for reducing the amount of arithmetic operations in the likelihood computation of continuous mixture HMM (CMHMM) with diagonal covariance matrices while retaining high performance. The key points are the use of the scalar quantization of the input observation vector components and table look-up. These make multiplication, squaring and division operations entirely unnecessary in the whole HMM computation (i.e., output probability calculation and trellis/Viterbi computation). It is experimentally proved in an large-vocabulary isolated word recognition task that scalar quantization into no less than 16 levels does not cause significant degradation in the speech recognition performance. Scalar quantization is also utilized in the computation truncation for unlikely distributions; the total number of distribution likelihood computations can be reduced by 66% with only a slight performance degradation. This \"multiplication-free\" HMM algorithm has high potentiality in speech recognition applications on personal computers.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"19 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":"123356014","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.1995.480058
M. Skoglund
A Hadamard-based framework for soft decoding in vector quantization over a Rayleigh fading channel is presented. We also provide an efficient algorithm for decoding calculations. The system has relatively low complexity, and gives low transmission rate since no redundant channel coding is used. Our image coding simulations indicate that the soft decoder outperforms its hard decoding counterpart. The relative gain is larger for bad channels. Simulations also indicate that encoder training for hard decoding suffices to get good results with the soft decoder.
{"title":"A soft decoder vector quantizer for a Rayleigh fading channel: application to image transmission","authors":"M. Skoglund","doi":"10.1109/ICASSP.1995.480058","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.480058","url":null,"abstract":"A Hadamard-based framework for soft decoding in vector quantization over a Rayleigh fading channel is presented. We also provide an efficient algorithm for decoding calculations. The system has relatively low complexity, and gives low transmission rate since no redundant channel coding is used. Our image coding simulations indicate that the soft decoder outperforms its hard decoding counterpart. The relative gain is larger for bad channels. Simulations also indicate that encoder training for hard decoding suffices to get good results with the soft decoder.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"302 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":"123620533","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.1995.479471
H. Abut, A. Bilgin, R. Bernardi, L. Wherry
Presents findings on image processing applications to the continuous and automatic monitoring and verification of the status of control devices and vehicle speed estimation on the Interstate-15 Reversible High Occupancy Vehicle (HOV) lanes as examples of "IVHS at Work". The overall goal of the study has been to supply additional enhanced monitoring capabilities for the HOV operations. These capabilities have been intended to assist, rather than to eliminate the human operators from the loop. The authors describe this unique undertaking together with the issues related to the systems architecture, hardware and software components, the integration, image processing tools, and preliminary field test results.
{"title":"A case study in IVHS implementation: an image processing application for I-15 HOV lanes","authors":"H. Abut, A. Bilgin, R. Bernardi, L. Wherry","doi":"10.1109/ICASSP.1995.479471","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479471","url":null,"abstract":"Presents findings on image processing applications to the continuous and automatic monitoring and verification of the status of control devices and vehicle speed estimation on the Interstate-15 Reversible High Occupancy Vehicle (HOV) lanes as examples of \"IVHS at Work\". The overall goal of the study has been to supply additional enhanced monitoring capabilities for the HOV operations. These capabilities have been intended to assist, rather than to eliminate the human operators from the loop. The authors describe this unique undertaking together with the issues related to the systems architecture, hardware and software components, the integration, image processing tools, and preliminary field test results.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"59 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":"123689917","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.1995.479542
William Y. Hueng, B. Rao
The performance of text dependent, short utterance speaker verification systems degrades significantly with channel and background artifacts. The authors investigate maximum likelihood and adaptive techniques to compensate for a stationary channel and noise. Maximum likelihood channel and noise compensation was introduced by Cox and Bridle (1989), and has been shown to be effective in many other speech applications. For adaptive estimation, a Bussgang like algorithm is developed which is more suitable for real-time implementation. These techniques are evaluated on a speaker verification system that uses the nearest neighbor metric. The results show that for telephone speech with channel differences, channel compensation can provide substantial performance improvement. For un-cooperative speakers, background compensation resulted in a 35% improvement.
{"title":"Channel and noise compensation for text dependent speaker verification over telephone","authors":"William Y. Hueng, B. Rao","doi":"10.1109/ICASSP.1995.479542","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479542","url":null,"abstract":"The performance of text dependent, short utterance speaker verification systems degrades significantly with channel and background artifacts. The authors investigate maximum likelihood and adaptive techniques to compensate for a stationary channel and noise. Maximum likelihood channel and noise compensation was introduced by Cox and Bridle (1989), and has been shown to be effective in many other speech applications. For adaptive estimation, a Bussgang like algorithm is developed which is more suitable for real-time implementation. These techniques are evaluated on a speaker verification system that uses the nearest neighbor metric. The results show that for telephone speech with channel differences, channel compensation can provide substantial performance improvement. For un-cooperative speakers, background compensation resulted in a 35% improvement.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"43 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120927302","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.1995.480435
K. Berberidis, S. Theodoridis
The algorithm presented in the paper is an exact block processing counterpart of the fast Newton transversal filtering (FNTF) algorithm [Moustakides and Theodorides, 1991]. The main trait of the new algorithm is that the block processing is done in such a way so that the resulting estimates are mathematically equivalent with the respective estimates of the FNTF algorithm. In cases where the involved filter is of medium to long order the new algorithm offers a substantial saving in computational complexity without sacrificing performance.
{"title":"An efficient block Newton-type algorithm","authors":"K. Berberidis, S. Theodoridis","doi":"10.1109/ICASSP.1995.480435","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.480435","url":null,"abstract":"The algorithm presented in the paper is an exact block processing counterpart of the fast Newton transversal filtering (FNTF) algorithm [Moustakides and Theodorides, 1991]. The main trait of the new algorithm is that the block processing is done in such a way so that the resulting estimates are mathematically equivalent with the respective estimates of the FNTF algorithm. In cases where the involved filter is of medium to long order the new algorithm offers a substantial saving in computational complexity without sacrificing performance.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"31 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":"114075246","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.1995.480434
A. Donder, M. Beck, M. Bossert, J. Hess, U. Ketzer, W. Teich
Simulation in Information Technology is a course on system simulation that is offered by the Department of Information Technology to graduate students which are majoring in communications engineering. The course imparts a fundamental knowledge of simulation tools and of mobile communication systems. The simulation tool which is used in the course is COSSAP (Communication Systems Simulation and Analysis Package) and the considered communication system is GSM (Global System for Mobile communications). The authors give an introduction into COSSAP, into GSM and especially into the course structure. In addition, some simulation results are given, i.e. the improvement of soft decision decoding versus hard decision decoding.
{"title":"Course on Simulation in Information Technology: the Global System for Mobile communications","authors":"A. Donder, M. Beck, M. Bossert, J. Hess, U. Ketzer, W. Teich","doi":"10.1109/ICASSP.1995.480434","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.480434","url":null,"abstract":"Simulation in Information Technology is a course on system simulation that is offered by the Department of Information Technology to graduate students which are majoring in communications engineering. The course imparts a fundamental knowledge of simulation tools and of mobile communication systems. The simulation tool which is used in the course is COSSAP (Communication Systems Simulation and Analysis Package) and the considered communication system is GSM (Global System for Mobile communications). The authors give an introduction into COSSAP, into GSM and especially into the course structure. In addition, some simulation results are given, i.e. the improvement of soft decision decoding versus hard decision decoding.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"5 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114091924","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.1995.479899
S. Young, N. Nasrabadi, M. Soumekh
This paper presents methods for detecting and identifying moving targets in a synthetic aperture radar (SAR) scene. An analytical expression is derived for the coherent SAR signature of a target. SAR system model of a moving target is developed. These principles are then used to construct a SAR signal statistic (energy function) in a parameter space which is defined by the target's coordinates, speed, and coherent SAR signature. Stochastic gradient techniques are used to search for the maximum point of this energy function which is located at the desired target's parameters.
{"title":"SAR moving target detection and identification using stochastic gradient techniques","authors":"S. Young, N. Nasrabadi, M. Soumekh","doi":"10.1109/ICASSP.1995.479899","DOIUrl":"https://doi.org/10.1109/ICASSP.1995.479899","url":null,"abstract":"This paper presents methods for detecting and identifying moving targets in a synthetic aperture radar (SAR) scene. An analytical expression is derived for the coherent SAR signature of a target. SAR system model of a moving target is developed. These principles are then used to construct a SAR signal statistic (energy function) in a parameter space which is defined by the target's coordinates, speed, and coherent SAR signature. Stochastic gradient techniques are used to search for the maximum point of this energy function which is located at the desired target's parameters.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"196 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":"124369486","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：