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Perceptual relevance of objectively measured descriptors for speaker characterization

Perceptual relevance of objectively measured descriptors for...

引用

1998 23rd IEEE International Conference on Acoustics, Speech and signal processing, ICASSP 1998

作者： Necioglu, Burhan F. Clements, Mark A. Barnwell, Thomas P. Schmidt-Nielsen, Astrid Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332 United States Code 5513 Naval Research Laboratory 4555 Overlook Ave SW Washington DC 20375 United States

ISBN: (纸本)0780344286

Subjective testing of speaker recognizability is an intricate, time consuming and very expensive process, but using objectively measurable descriptors to augment the subjective speaker recognizability tests could result in increased efficiency and reliability. This paper describes our investigation into the relevancy of a set of objective descriptors to human perception of speaker identity through multidimensional scaling (MDS) of subjective speaker pair similarity judgments. The evaluated objective descriptors can achieve same/different detection error rates as low as 4.13% for male speaker pairs, and 8.17% for female speaker pairs, with only 3 seconds of speech. Five descriptors related to glottal, vocal tract and prosodic features were found to have significant correlations with the perceptual dimensions of the MDS solutions. © 1998 IEEE.

关键词： Subjective testing

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Ultra low bit rate speech coding using an ergodic hidden Markov model

Ultra low bit rate speech coding using an ergodic hidden Mar...

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： M.E. Lee A.S. Durey E. Moore M. Clements Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

This paper presents the framework for an ultra low bit rate speech vocoder. The system is based on a recognition-synthesis paradigm in which a single ergodic hidden Markov model (EHMM) is used to capture the statistical characterizations of speech in a flexible manner capable of limiting the effects of recognition errors. Because predetermined speech units are not used, this system has the advantage of not requiring a transcription for the training data set. By incorporating a mixed excitation scheme based on an improved MELP formulation into the EHMM, additional gains in quality and speaker characterization are achieved at no cost to the bit rate.

关键词： Bit rate Speech coding Hidden Markov models Speech synthesis Vocoders Speech recognition Decoding Speech processing Character recognition signal synthesis

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Multiresolution Quadtree Beamformer

Multiresolution Quadtree Beamformer

引用

International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Seung-mok Oh James H. McClellan Center for Signal and Image Processing Georgia Institute of Technology School of Electrical and Computer Engineering Atlanta GA USA

The delay-sum beamformer (DSBF) is a space-time domain beamforming,method that performs coherent summation of sensor data. However, the computational complexity of finding the steered response over all angles is O(N 3 ). In this paper, an O(N 2 log 2 N) space-time domain beamforming algorithm it is proposed. This fast algorithm does not require uniform sensor spacing. It is called Quadtree Beamformer (QBF) because it is based on the iterative subband spectral decomposition method that has been used in the Quadtree BackProjection SAR imaging algorithm. The QBF is implemented by recursively performing a spectral decomposition process over the space-time domain sensor array data. It also provides intermediate stage data that can be used for multi-angle multiresolution beamforming.

关键词： Arrays Complexity theory Three dimensional displays signal resolution image resolution Array signal processing Imaging

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Estimation of elliptically contoured mixture models for hyperspectral imaging data

Estimation of elliptically contoured mixture models for hype...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： M.D. Farrell R.M. Mersereau Center for Signal & Image Processing School of Electrical & Computer Engineering Georgia Institute of Technology Atlanta GA USA

Gaussian mixture modeling (GMM) has become a popular method for representing the statistical variability of spectrally inhomogeneous hyperspectral imaging (HSI) data. Finite mixture models can be applied to image segmentation, which can be considered a sort of blind classification, which is useful when there is no a priori information available about the materials in the scene. However, the GMM approach can be insufficient for many HSI data sets since the Gaussian has fixed narrow tails, uncharacteristic of operational HSI data. Elliptically contoured distributions (ECDs), specifically the multivariate t, have been shown to better fit HSI data. In this paper we develop mixtures of ECDs for the task of robustly modeling hyperspectral image data. An approach based on the EM algorithm is developed for concurrently estimating all parameters in a t mixture, assuming nothing but that the number of components are known. Results from the automatic segmentation of AVIRIS data illustrate the utility of t mixture models using this EM approach for parameter estimation.

关键词： Hyperspectral imaging Hyperspectral sensors Layout Probability distribution image segmentation Robustness Parameter estimation Shape control signal processing image processing

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HMM ADAPTATION USING SPARSE PROBABILISTIC SPACE MAPPING FOR NOISY SPEECH

HMM ADAPTATION USING SPARSE PROBABILISTIC SPACE MAPPING FOR ...

引用

IEEE International Conference on Acoustics, Speech, and signal processing

作者： Kaustubh Kalgaonkar Mark A. Clements Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia 30339

ISBN: (纸本)9781424442959

This paper presents an extension of Probabilistic Space Maps (PS-MAPS) to adapt clean acoustic models to a noisy environment. In the presence of noise, the relationship between noisy and clean speech features (MFCC's, HDLA, etc.) is either nonlinear or unknown. Given the relationship between features, traditional methods try to linearize it using approximations. These methods cannot be used for systems where the mapping model for clean and noisy features is missing. Given sufficient training data, PS-MAPS [1] provides an excellent framework for extracting and modeling this relationship. The PS-MAP based approach to model adaptation is completely data driven. Experiments were performed on Aurora 2 dataset to evaluate the effectiveness of the algorithm.

关键词： Probabilistic Maps Speech Enhancement Bayesian Estimation EM Speech enhancement Bayes methods Noisy environment Noise Speech Hidden Markov models

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Multicarrier modulation via finite-field transforms

Multicarrier modulation via finite-field transforms

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IEEE Digital signal processing Workshop

作者： F. Fekri D.B. Williams Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

Multicarrier modulation has rapidly become common in both wireline and wireless high speed digital communications applications. However, the large dynamic range of a multicarrier signal causes problems at both the transmitter and the receiver. Here, finite-field mathematics are examined as a means of controlling the signal's dynamic range. A framework for multicarrier modulation with finite-field transforms is constructed, and equivalence to certain maximum distance separable error-correcting codes is demonstrated. Implications on the assumed digital channel model caused by using finite-field mathematics in the transmitter and receiver are also discussed.

关键词： Discrete Fourier transforms Transmitters Dynamic range OFDM modulation Convolution Mathematics Modulation coding Equalizers Discrete transforms Digital modulation

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Digital singing voice synthesis using a new alternating reflection model

Digital singing voice synthesis using a new alternating refl...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： M.E. Lee M.J.T. Smith Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

Many models for computer generated singing voices have been proposed in the past and have been shown to produce a wide variety of synthesized voices. While many of these models are capable of synthesizing a particular singing voice with high musical quality, they typically are challenged with respect to naturalness, range, the ability to synthesize both male and female voices, as well as the ability to capture the identity of the singer. The analysis-by-synthesis/overlap-add (ABS/OLA) sinusoidal model has proven to be effective in producing high quality voices with manageable computational cost. It is based on the combination of a block overlap-add sinusoidal representation and an analysis-by-synthesis parameter estimation technique. ABS/OLA is flexible enough to allow for modifications such as time and pitch scaling; however, it can suffer from quality degradation under such conditions. This paper presents an analysis/synthesis model that incorporates new methods to improve synthesis. These improvements add to the naturalness and flexibility in controlling perceptually important musical characteristics.

关键词： Reflection signal synthesis Degradation Frequency modulation signal processing image processing signal generators Speech analysis Quality management Costs

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Migration of underground targets in UWB-SAR systems

Migration of underground targets in UWB-SAR systems

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IEEE International Conference on image processing

作者： W. Lertniphonphun J.H. McClellan Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (纸本)0780362977

Ultra-wideband synthetic aperture radar (UWB-SAR) systems can be used for imaging underground targets. However, conventional imaging algorithms that assume a constant velocity of propagation will exhibit degradations such as blurred targets and incorrect target locations. A superior approach is to do the processing by migrating the raw data collected by an array of sensors. In this paper, we use a filtering structure for migration as a 2-D all-pass filter, and present a practical processing method for UWB-SAR imaging. Improvements versus conventional SAR image focusing are included.

关键词： Focusing Sensor arrays Ultra wideband technology Filtering Iterative algorithms image generation image sensors Government Pixel signal processing

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PERCEPTUALLY MOTIVATED TEMPORAL MODELING OF FOOTSTEPS IN A CROSS-ENVIRONMENTAL DETECTION TASK

PERCEPTUALLY MOTIVATED TEMPORAL MODELING OF FOOTSTEPS IN A C...

引用

IEEE International Conference on Acoustics, Speech, and signal processing

作者： M. Umair Bin Altaf Taras Butko Biing-Hwang (Fred) Juang Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia.

ISBN: (纸本)9781479903573

Real world sounds are ubiquitous and form an important part of the edifice of our cognitive abilities. Their perception combines signatures from spectral and temporal domains, among others, yet traditionally their analysis is focused on the frame based spectral properties. We consider the problem of sound analysis from perceptual perspective and investigate the temporal properties of a "footsteps" sound, which is a particularly challenging from the time-frequency analysis viewpoint. We identify the irregular repetition of the self similarity and the sense of duration as significant to its perceptual quality and extract features using the Teager-Kaiser energy operator. We build an acoustic event detection system for "footsteps" which shows promising results for detection in cross-environmental conditions when compared with conventional approach.

关键词： Temporal modeling HMM Teager-Kaiser operator Acoustic event detection Hidden Markov models Event detection SOUND KCNK3 gene edifices time characteristic Modeling Vibration Hearing signatures

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Distributed initialization of sensor networks with communication and computation trees

Distributed initialization of sensor networks with communica...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Milind Borkar James H. McClellan Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

When compared to the tracking problem in which prior knowledge is available, generating the initial distribution for the state vector of a phenomenon of interest, with no prior knowledge of the desired state, is a challenging problem. In this paper, the authors develop a fully distributed initialization algorithm that fuses data in heterogeneous sensor networks using communication trees. Monte Carlo methods are used to fuse the collected data and to represent the desired state vector distribution. The presented algorithm utilizes an importance function that is additive in the local node posterior distributions, providing a robust alternative to belief propagation methods in which particles are generated according to the product of local node posteriors.

关键词： computer networks Distributed computing State estimation Sensor fusion Belief propagation Fuses image sensors signal processing image processing Knowledge engineering

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