Contains an introduction and reports on five research projects.National Science Foundation Grant MIP 87-14969National Science Foundation FellowshipU.S. Air Force - Electronic Systems Division Contract F1 9628-89-K-0041U.S. Navy - Office of Naval Research Contract N00014-89-J-148

Brandstein, Michael S.

Cheung, Shiufun

Hardwick, John C.

Lim, Jae S.

Picard, Rosalind W.

Wang, Katherine S.

DSpace@MIT

Chapter 2. Speech Processing Research ProgramChapter 2. Speech Processing Research ProgramAcademic and Research StaffProfessor Jae S. Lim, Giovanni Aliberti, Giampiero SciuttoGraduate StudentsMichael S. Brandstein, Shiufun Cheung, Warren Chou, John C. Hardwick, Rosalind W. Picard,Paul Shen, Katherine S. WangTechnical and Support StaffHassan Gharavy, Cynthia LeBlanc, Julia Sharp2.1 IntroductionThe objective of this research program is todevelop methods for solving importantspeech communication problems. Currentresearch topics in progress include (1) real-time implementation of a multibandexcitation vocoder operating at bit ratesranging between 2.4 and 8.0 kbits/sec and(2) development of algorithms for enhancingspeech degraded by background noise andfor modifying the time scale of speech. Weare also investigating methods for displayingspectrograms more efficiently.2.2 Development of aSpeech Vocoder1.5 KbpsSponsorsNational Science FoundationGrant MIP 87-14969National Science Foundation FellowshipU.S. Air Force - Electronic Systems DivisionContract F1 9628-89-K-0041Project StaffMichael S. Brandstein, Professor Jae S. LimThe recently developed Multi-Band Excita-tion Speech Model accurately reproduces awide range of speech signals without manyof the limitations inherent in existing speechmodel based systems.' The robustness of thismodel makes it particularly applicable to lowbit rate, high quality speech vocoders. InGriffin and Lim, 2 a 9.6 Kbps speech coderbased on this model was first described.Later work resulted in a 4.8 Kbps speechcoding system.3 We have shown that both ofthese systems are capable of high qualityspeech reproduction in both low and highSNR conditions.The purpose of this research is to exploremethods of using the new speech model atthe 1.5 Kbps rate. Results indicate that asubstantial amount of redundancy existsbetween the model parameters. Currentresearch is focused on exploiting theseredundancies to quantize these parametersmore efficiently. Attempts are also underway to simplify the existing model withoutsignificantly reducing speech quality.1 D.W. Griffin and J.S. Lim, "A New Model-Based Speech Analysis/Synthesis System," IEEE International Confer-ence on Acoustic, Speech and Signal Processing, Tampa, Florida, March 26-29, 1985, pp. 513-516.2 D.W. Griffin and J.S. Lim, "A High Quality 9.6 kbps Speech Coding System," IEEE International Conference onAcoustic, Speech and Signal Processing, Tokyo, Japan, April 8-11, 1986.3 J.C. Hardwick, A 4.8 Kbps Multi-Band Excitation Speech Coder, S.M. thesis, Dept. of Electr. Eng. and Comput.Sci., MIT, 1988.253Chapter 2. Speech Processing Research Program2.3 A New Method forRepresenting SpeechSpectrogramsSponsorsNational Science FoundationGrant MIP 87-14969U.S. Navy - Office of Naval ResearchContract N00014-89-J-1489Project StaffShiufun Cheung, Professor Jae S. LimThe spectrogram, which is a two-dimensionaltime-frequency display of a one-dimensionalsignal, is used extensively in speech research.Existing spectrograms are generally dividedinto two types, wide-band spectrograms andnarrow-band spectrograms, according to thebandwidth of the filters used to generatethem. Due to the different characteristics ofthe two types of spectrograms, they areemployed for different purposes. The wide-band spectrogram is valued for its quicktemporal response and is used for wordboundary location and formant tracking. Onthe other hand, the narrow-band spectro-gram, with its high frequency resolution, isprimarily used for measuring pitch frequency.Since each of the spectrograms has its ownadvantages and weaknesses, efforts are beingmade to incorporate the desirable aspects ofthe two spectrograms into one display. Oneapproach is to mimic the human auditorysystem and use critical band filters to gen-erate neural spectrograms. Another methodis to construct an optimum window, which isthe temporal equivalent of the filter.In this research, we propose an entirely dif-ferent view of the problem. Instead ofviewing the spectrogram as a transformedspeech signal, we consider it an image ordigital picture. Given this type of approach,the whole gamut of image processing tech-niques is available for use, and the problembecomes theoretically much simpler. In fact,the most interesting aspect of this research isthat we transform a problem in speech pro-cessing into an image-processing problem.2.4 A Dual Excitation SpeechModelSponsorsNational Science FoundationGrant MIP 87-14969U.S. Air Force - Electronic Systems DIvisionContract F1 9628-89-K-0041Project StaffJohn C. Hardwick, Professor Jae S. LimOne class of speech analysis/synthesissystems (vocoders) which have been exten-sively studied and used in practice are basedon an underlying model of speech. Eventhough traditional vocoders have been quitesuccessful in synthesizing intelligible speech,they have not successfully synthesized highquality speech. The Multi-Band Excitation(MBE) speech model, introduced by Griffin,improves the quality of vocoder speechthrough the use of a series of frequencydependent voiced/unvoiced decisions. TheMBE speech model, however, results in aloss of quality as compared to the originalspeech. This degradation is caused in partby the voiced/unvoiced decision process. Alarge number of frequency regions contain asubstantial amount of both voiced andunvoiced energy. If a region of this type isdeclared voiced, then a tonal or hollowquality is added to the synthesized speech.Similarly, if the region is declared unvoiced,then additional noise occurs in the synthe-sized speech. As the signal-to-noise ratiodecreases, the classification of speech aseither voiced or unvoiced becomes more dif-ficult, and, consequently, the degradationincreases.We have proposed a new speech model inresponse to the problems mentioned above.This model is referred to as the Dual Excita-tion (DE) speech model, because of its dualexcitation and filter structure. The DEspeech model is a generalization of most pre-vious speech models which, with the properselection of the model parameters, reduces toeither the MBE speech model or to a varietyof more traditional speech models.Currently, our research is examining the useof this speech model for speech enhance-ment, time scale modification and bandwidth254 RLE Progress Report Number 132compression. Additional areas of studyinclude further refinements to the model andimprovements in the estimation algorithms.2.5 Image Texture ModelingSponsorsNational Science FoundationGrant MIP 87-14969U.S. Navy - Office of Naval ResearchContract N00014-89-J-1489Project StaffRosalind W. Picard, Professor Jae S. LimTextured regions are the nemesis of manyimage processing algorithms. For example,algorithms for image segmentation or imagecompression usually assume stationarity orhigh correlation of the image gray-level data,failing in textured regions. In this research,we are developing a model with only a smallnumber of parameters which synthesizes thetextures. This model would have applica-tions for image enhancement, segmentation,scene synthesis, and low bit rate imagecoding.The ability to synthesize syntactically regular"structural" textures, e.g., a tiled wall, as wellas the more random "stochastic" textures,e.g., shrubbery, is desirable in a texturemodel. Most models assume only one ofthese cases and perform poorly when thedata is not perfectly periodic or stochastic.Our goal is to develop a model which iscapable of exhibiting a continuum of struc-tural and stochastic behavior.We have confirmed the fact that the MarkovRandom Field model, which is equivalent tothe Gibbs Distribution of statisticalmechanics, synthesizes a wide variety ofstochastic textures. By using concepts fromstatistical mechanics, we have modified theGibbs distribution so that it synthesizes agreater variety of textures. One modification,Chapter 2. Speech Processing Research Programimposing an "external field," allows disconti-nuities to appear in the texture. We haveexplored other modifications which simulate"physical" processes. Recently, by usingdominant spectral coefficients, we haveinduced some structure in the random field.We are currently investigating the limitationsof this mixed structural and stochastic modelby estimating the structural and stochasticparameters of natural textures and trying tosynthesize visually similar textures.2.6 Speech EnhancementTechniques for the DualExcitation Vocoder ModelSponsorsNational Science FoundationGrant MIP 87-14969National Science Foundation FellowshipU.S. Navy - Office of Naval ResearchContract N00014-89-J-1489Project StaffKatherine S. Wang, Professor Jae S. LimWe are exploring some conventional methodsfor speech enhancement in the presence ofadditive white noise,4 in a new frameworkwhere the voiced estimation provided by theMBE model5 allows us to perform noisereduction separately on voiced and unvoicedcomponents. Conventional methods whichtake advantage of the periodic structure ofvoiced speech include comb filtering andadaptive noise cancellation. A techniquebased on short-time spectral amplitude esti-mation obtains the minimum mean-square-error, linear estimator of the speech signal bynoncausal Wiener filtering, which we couldapproximate by an adaptive Wiener filteringtechnique. Speech enhancement can also bemodel based, such as using classical esti-mation theory applied to an all pole model ofspeech. We will draw from some of theseconventional techniques to create a speech4 J.S. Lim and A.V. Oppenheim, "Enhancement and Bandwidth Compression of Noisy Speech," Proc. IEEE 67 (12):(1979); ed. J.S. Lim, Speech Enhancement. (Englewood Cliffs, New Jersey: Prentice Hall, 1983).5 D.W. Griffin and J.S. Lim, "A New Model-Based Speech Analysis/Synthesis System," IEEE International Confer-ence on Acoustics, Speech and Signal Processing, Tampa, Florida, March 26-29, 1985, pp. 513-516.255Chapter 2. Speech Processing Research Programenhancement system customized to the traitsof the Multi-Band Excitation (MBE) Vocoderand, subsequently, to the Dual ExcitationModel. 6 The noise-like characteristics ofunvoiced speech and the harmonic structureof voiced speech suggest that noise can mosteffectively be reduced in speech that hasbeen separated into the two components,rather than attempting to categorize the fre-quency band as purely voiced and unvoiced.We have shown that the recently developedMulti-Band Excitation (MBE) Speech Modelaccurately reproduces a wide range ofspeech signals without many of the limita-tions inherent in existing speech model basedsystems.6 John C. Hardwick, Ph.D. research, MIT.256 RLE Progress Report Number 132

Speech Processing Research Program

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Speech Processing Research Program

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