List of Recently Published Papers (by K.K. Paliwal)

 
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2023
  1. Sisi Shi, K.K. Paliwal and Andrew Busch, ``On DCT-based MMSE estimation of short time spectral amplitude for single-channel speech enhancement'', Applied Acoustics, Vol. 202, Article No. 109134, Jan. 2023. [pdf]


2022
  1. S.K. Roy and K.K. Paliwal, ``Robustness and sensitivity metrics-based tuning of the augmented Kalman filter for single-channel speech enhancement'', Applied Acoustics, Vol. 185, Article No. 108355, Jan. 2022. [pdf]
  2. Jaspreet Singh, T. Litfin, K.K. Paliwal, Jaswinder Singh and Y. Zhou, ``SPOT-Contact-LM: Improving single-sequence-based prediction of protein contact map using a transformer language model'', Bioinformatics, Vol. 38, Issue 7, pp. 1888-1894, Apr. 2022. [pdf]
  3. M. Solayman, T. Litfin, Jaswinder Singh, K.K. Paliwal, Y. Zhou and J. Zhan, ``Probing RNA structures by solvent accessibility: An overview from experimental and computational perspectives'', Briefings in Bioinformatics, Vol. 23, Issue 3, pp. 1-16, May 2022. [pdf]
  4. Jaspreet Singh, K.K. Paliwal, T. Litfin, Jaswinder Singh and Y. Zhou, ``SPOT-1D-LM: Reaching Alignment-profile-based Accuracy in Predicting Protein Secondary and Tertiary Structural Properties without Alignment'', Scientific Reports, Vol. 12, Article No. 7607, pp. 1-9, 2022. [pdf]
  5. S.K. Roy, A. Nicolson and K.K. Paliwal, ``On training targets for supervised LPC estimation to augmented Kalman filter-based speech enhancement'', Speech Communication, Vol. 142, pp. 49-60, July 2022. [pdf]
  6. Jaswinder Singh, K.K. Paliwal, T. Litfin, Jaspreet Singh and Y. Zhou, ``Predicting RNA distance-based contact maps by integrated deep learning on physics-inferred secondary structure and evolutionary-derived mutational coupling'', Bioinformatics, Vol. 38, Issue 16, pp. 3900-3910, Aug. 2022. [pdf]


2021
  1. S. Shi, A. Busch, K.K. Paliwal and T. Fickenscher, ``On the use of discrete cosine transform polarity spectrum in speech enhancement'', Proc. 28th European Signal Processing Conference (EUSIPCO), pp. 421-425, Jan. 2021. [pdf]
  2. T. Roberts and K.K. Paliwal, ``An objective measure of quality for time-scale modification of audio'', Journ. Acoust. Soc. America, Vol. 149, Issue 3, pp. 1843-1854, March 2021. [pdf]
  3. S.K. Roy, A. Nicolson and K.K. Paliwal, ``DeepLPC: A deep learning approach to augmented Kalman filter-based single-channel speech enhancement'', IEEE Access, Vol. 9, pp. 64524-64538, 2021. [pdf]
  4. A. Nicolson and K.K. Paliwal, ``On training targets for deep learning approaches to clean speech magnitude spectrum estimation'', Journ. Acoust. Soc. America, Vol. 149, Issue 5, pp. 3273-3293, May 2021. [pdf]
  5. S.K. Roy, A. Nicolson and K.K. Paliwal, ``DeepLPC-MHANet: Multi-head self-attention for augmented Kalman filter-based speech enhancement'', IEEE Access, Vol. 9, pp. 70516-70530, 2021. [pdf]
  6. Jaswinder Singh, K.K. Paliwal, Jaspreet Singh and Y. Zhou, ``RNA backbone torsion and pseudotorsion angle prediction using dilated convolutional neural networks'', Journal of Chemical Information and Modeling, Vol. 61, pp. 2610-2622, 2021. [pdf]
  7. S.K. Roy and K.K. Paliwal, ``Robustness and sensitivity tuning of the Kalman filter for speech enhancement'', Signals, Vol. 2, Issue 3, pp. 434-455, 2021. [pdf]
  8. S.K. Roy and K.K. Paliwal, ``A noise PSD estimation algorithm using derivative-based high-pass filter in non-stationary noise conditions'', EURASIP Journal on Audio, Speech, and Music Processing, Article No. 32, pp. 1-18, Aug. 2021. [pdf]
  9. T. Roberts, A. Nicolson and K.K Paliwal. ``Deep learning-based single-ended objective quality measures for time-scale modified audio'', Journal of Audio Engineering Society, Vol. 69, Issue 9, pp. 644-655, Sept. 2021. [pdf]
  10. Jaswinder Singh, K.K. Paliwal, T. Zhang, Jaspreet Singh, T. Litfin and Y. Zhou, ``Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning'', Bioinformatics, Vol. 37, Issue 17, pp. 2589-2600, Sept. 2021. [pdf]
  11. Jaspreet Singh, T. Litfin, K.K. Paliwal, Jaswinder Singh, A.K. Hanumanthappa and Y. Zhou, ``SPOT-1D-Single: Improving the single-sequence-based prediction of protein secondary structure, backbone angles, solvent accessibility and half-sphere exposures using a large training set and ensembled deep learning'', Bioinformatics, Vol. 37, Issue 20, pp. 3464-3472, Oct. 2021. [pdf]
  12. Jaspreet Singh, Jaswinder Singh, K.K. Paliwal, A. Busch and Y. Zhou, ``SPOT-1D2: Improving protein secondary structure prediction using high sequence identity training set and an ensemble of recurrent and residual-convolutional neural networks'', Proc. 2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Melbourne, Australia, Oct. 2021.
  13. T. Zhang, Jaswinder Singh, T. Litfin, J. Zhan, K.K. Paliwal and Y. Zhou, ``RNAcmap: A fully automatic pipeline for predicting contact maps of RNAs by evolutionary coupling analysis'', Bioinformatics, Vol. 37, Issue 20, pp. 3494-3500, Oct. 2021. [pdf]


2020
  1. J. Hanson, T. Litfin, K.K. Paliwal and Y. Zhou, ``Identifying molecular recognition features in intrinsically disordered regions of proteins by transfer learning'', Bioinformatics, Vol. 36, Issue 4, pp. 1107-1113, Feb. 2020. [pdf]
  2. M. Nikzad, A. Nicolson, Y. Gao, J. Zhou, K.K. Paliwal and F. Shang, ``Deep residual-dense lattice network for speech enhancement'', Proc. Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), pp. 8552-8559, 2020. [pdf]
  3. Y. Cai, X. Li, Z. Sun, Y. Lu, H. Zhao, J. Hanson, K.K. Paliwal, T. Litfin, Y. Zhou and Y. Yang, ``SPOT-Fold: Fragment-free protein structure prediction guided by predicted backbone structure and contact map'', Journal of Computational Chemistry, Vol. 48, Issue 8, pp. 745-750, Mar. 2020. [pdf]
  4. Q. Zhang, A.M. Nicolson, M. Wang, K.K. Paliwal and C.X. Wang, ''DeepMMSE: A deep learning approach to MMSE-based noise power spectral density estimation'', IEEE/ACM Trans. on Audio, Speech, and Language Processing, Vol. 28, Issue 1, pp. 1404-1415, Apr. 2020. [pdf]
  5. J. Hanson, K.K. Paliwal, T. Litfin, Y. Yang and Y. Zhou, ``Getting to know your neighbor: Protein structure prediction comes of age with contextual machine learning'', Journal of Computational Biology, Vol. 27, No. 5, pp. 796-814, 2020. [pdf]
  6. A. Barik, A. Katuwawala, J. Hanson, K.K. Paliwal, Y. Zhou and L. Kurgan, ``DEPICTER: Intrinsic disorder and disorder function prediction server'', Journal of Molecular Biology, Vol. 432, Issue 11, pp. 3379-3387, 2020. [pdf]
  7. T. Roberts and K.K. Paliwal, ``A time-scale modification dataset with subjective quality labels'', Journ. Acoust. Soc. America, Vol. 148, Issue 1, pp. 201-210, July 2020. [pdf]
  8. S.K. Roy, A. Nicolson and K.K. Paliwal, ``Deep learning with augmented Kalman filter for single-channel speech enhancement'', Proc. IEEE International Symposium on Circuits and Systems (ISCAS), Oct. 2020. [pdf]
  9. A. Nicolson and K.K. Paliwal, ``Sum-product networks for robust automatic speaker identification'', Proc. Interspeech, Shanghai, China, Oct. 2020. [pdf]
  10. S.K. Roy, A. Nicolson and K.K. Paliwal, ``A deep learning-based Kalman filter for speech enhancement'', Proc. Interspeech, Shanghai, China, Oct. 2020. [pdf]
  11. A. Nicolson and K.K. Paliwal, ``Spectral distortion level resulting in a just-noticeable difference between an a priori signal-to-noise ratio estimate and its instantaneous case'', Journ. Acoust. Soc. America, Vol. 148, Issue 4, pp. 1879-1889, Oct. 2020. [pdf]
  12. A.K. Hanumanthappa, Jaswinder Singh, K.K. Paliwal, Jaspreet Singh and Y. Zhou, ''Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network'', Bioinformatics, Vol. 36, Issue 21, pp. 5169–5176, Nov. 2020. [pdf]
  13. S.K. Roy and K.K. Paliwal, ``Causal convolution encoder decoder-based augmented Kalman filter for speech enhancement'', 14th International Conference on Signal Processing and Communication Systems (ICSPCS), Adelaide, Australia, Dec. 2020. [pdf]
  14. S.K. Roy and K.K. Paliwal, ``Sensitivity metric-based tuning of the augmented Kalman filter for speech enhancement'', 14th International Conference on Signal Processing and Communication Systems (ICSPCS), Adelaide, Australia, Dec. 2020. [pdf]
  15. S.K. Roy and K.K. Paliwal, ``Deep Residual Network-Based Augmented Kalman Filter for Speech Enhancement'', Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA-ASC), Auckland, New Zealand, Dec. 2020. [pdf]
  16. S.K. Roy and K.K. Paliwal, ``Causal convolutional neural network-based Kalman filter for speech enhancement'', Asia-Pacific Conference on Computer Science and Data Engineering, Gold Coast, Australia, Dec. 2020. [pdf]
  17. A. Nicolson and K.K. Paliwal, ``Masked multi-head self-attention for causal speech enhancement'', Speech Communication, Vol. 125, pp. 80-96, Dec. 2020. [pdf]


2019
  1. S.K. Roy and K.K. Paliwal, ``An iterative Kalman filter with reduced-biased Kalman Gain for single channel speech enhancement in non-stationary noise condition'', International Journal of Signal Processing Systems, Vol. 7 No. 1, pp. 7, 2019.
  2. J. Hanson, K.K. Paliwal, T. Litfin, Y. Yang and Y. Zhou, ``Improving prediction of protein secondary structure, backbone angles, solvent accessibility, and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks'', Bioinformatics, Vol. 35, Issue 14, pp. 2403-2410, July 2019. [pdf]
  3. A. Nicolson and K.K. Paliwal, ``Deep learning for minimum mean-square error approaches to speech enhancement'', Speech Communication, Vol. 111, pp. 44-55, Aug. 2019. [pdf]
  4. T. Roberts and K.K. Paliwal, ``Time-Scale Modification Using Fuzzy Epoch-Synchronous Overlap-Add (FESOLA'', IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, pp. 31-34, Oct. 2019. [pdf]
  5. Jaswinder Singh, J. Hanson, K.K. Paliwal and Y. Zhou, ``RNA secondary structure prediction using an ensemble of two-dimensional recurrent and residual convolutional neural networks and transfer learning'', Nature Communications, Vol. 10, Article No. 5407, Nov. 2019. [pdf]
  6. J. Hanson, K.K. Paliwal, T. Litfin and Y. Zhou, ``SPOT-Disorder2: Improved protein intrinsic disorder prediction by ensembled deep learning'', Genomics, Proteomics and Bioinformatics, Vol. 17, Issue 6, pp. 645-656, Dec. 2019. [pdf]


2018
  1. J. O'Connell, Z. Li, J. Hanson, R. Heffernan, J. Lyons, K.K. Paliwal, A. Dehzangi, Y. Yang and Y. Zhou, ``SPIN2: Predicting sequence profiles from protein structures using deep neural networks'', Proteins: Structure, Function, and Bioinformatics, Vol. 86, Issue 6, pp. 629-633, Feb. 2018. [pdf]
  2. S. So and K.K. Paliwal, ``Reconstruction of a signal from the real part of its discrete Fourier transform'', IEEE Signal Process. Mag., Vol. 35, No. 2, pp. 162-174, Mar. 2018. [pdf]
  3. A. Nicolson, J. Hanson, J. Lyons and K.K. Paliwal, ``Spectral subband centroids for robust speaker identification using marginalization-based missing feature theory'', International Journal of Signal Processing Systems, Vol. 6, No. 1, pp. 12-16, Mar. 2018. [doi: 10.18178/ijsps.6.1.12-16] [pdf]
  4. Y. Yang, J. Gao, J. Wang, R. Heffernan, J. Hanson, K.K. Paliwal and Y. Zhou, ``Sixty-five years of the long march in protein secondary structure prediction: the final stretch?'', Briefings in Bioinformatics, Vol. 19, Issue 3, pp. 482-494, May 2018. [pdf]
  5. A. Alatwi and K.K. Paliwal, ``A smoothed and thresholded linear prediction analysis for efficient speech coding'', Journal of Communications, Vol. 13, No. 5, pp. 230-235, May 2018. [doi: 10.12720/jcm.13.5.230-235]
  6. R. Heffernan, K.K. Paliwal, J. Lyons, J. Singh, Y. Yang and Y. Zhou, ``Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning'', Journal of Computational Chemistry, Vol. 39, pp. 2210-2216, 2018. [pdf]
  7. J. Singh, J. Hanson, R. Heffernan, K.K. Paliwal, Y. Yang and Y. Zhou, ``Detecting proline and non-proline cis-isomers in protein structures from sequences using deep residual ensemble learning'', Journal of Chemical Information and Modeling, Vol. 58, Issue 9, pp. 2033-2042, Sept. 2018. [pdf]
  8. J. Hanson, K.K. Paliwal and Y. Zhou, ``Accurate single-sequence prediction of protein intrinsic disorder by an ensemble of deep recurrent and convolutional architectures'', Journal of Chemical Information and Modeling, Vol. 58, Issue 11, pp. 2369-2376, Nov. 2018. [pdf]
  9. A.E.W. George, S. So, R. Ghosh and K.K. Paliwal, ``Robustness metric-based tuning of the augmented Kalman filter for the enhancement of speech corrupted with coloured noise'', Speech Communication, Vol. 105, pp. 62-76, Dec. 2018. [pdf]
  10. A. Nicolson and K.K. Paliwal, ``Bidirectional long-short term memory network-based estimation of reliable spectral component locations'', Proc. Interspeech, Hyderabad, India, Sept. 2018. [pdf]
  11. T. Roberts and K.K. Paliwal, ``Stereo time-scale modification using sum and difference transformation'' Intern. Conf. on Signal Processing and Communication Systems, ICSPCS-2018, Cairns, Australia, Dec. 2018. [pdf]
  12. T. Roberts and K.K. Paliwal, ``Frequency dependent time-scale modification'' Intern. Conf. on Signal Processing and Communication Systems, ICSPCS-2018, Cairns, Australia, Dec. 2018. [pdf]
  13. S.K. Roy and K.K. Paliwal, ``A non-iterative Kalman filter for single channel speech enhancement in non-stationary noise condition'' Intern. Conf. on Signal Processing and Communication Systems, ICSPCS-2018, Cairns, Australia, Dec. 2018.
  14. J. Hanson, K.K. Paliwal, T. Litfin, Y. Yang and Y. Zhou, ``Accurate prediction of protein contact maps by coupling residual two-dimensional bidirectional long short-term memory with convolutional neural networks'', Bioinformatics, Vol. 34, Issue 23, pp. 4039-4045, Dec. 2018. [pdf]


2017
  1. J. Hanson, Y. Yang, K.K. Paliwal and Y. Zhou, ``Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks", Bioinformatics, Vol. 33, Issue 5, pp. 685-692, Mar. 2017. [pdf]
  2. Y. Yang, R. Heffernan, K.K. Paliwal, J. Lyons, A. Dehzangi, A. Sharma, J. Wang, A. Sattar and Y. Zhou, ``SPIDER2: a package to predict secondary structure, accessible surface area, and main-chain torsional angles by deep neural networ'' in Y. Zhou, A. Kloczkowski, E. Faraggi, and Y. Yang (eds), Prediction of Protein Secondary Structure, Methods in Molecular Biology, Springer, New York, pp. 55-63, 2017. [pdf]
  3. S. So, A.E.W. George, R. Ghosh and K.K. Paliwal, ``Kalman filter with sensitivity tuning for improved noise reduction in speech'', Circuits, Systems and Signal Processing, Vol. 36, pp. 1476-1492, 2017. [pdf]
  4. R. Heffernan, Y. Yang, K.K. Paliwal and Y. Zhou, ``Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility'', Bioinformatics, Vol. 33, Issue 18, pp. 2842-2849, Sep. 2017. [pdf]
  5. A. Nicolson, J. Hanson, J. Lyons and K.K. Paliwal, ``Spectral subband centroids for robust speaker identification using marginalization-based missing feature theory'', Proc. 9th International Conference on Signal Processing Systems, Auckland, New Zealand, Nov. 2017. [pdf]
  6. A. Alatwi and K.K. Paliwal, ``A smoothed and thresholded linear prediction analysis for efficient speech coding'', Proc. 9th International Conference on Signal Processing Systems, Auckland, New Zealand, Nov. 2017. [pdf]


2016
  1. R. Heffernan, A. Dehzangi, J. Lyons, K.K. Paliwal, A. Sharma, J. Wang and A. Sattar, ``Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins'', Bioinformatics, Vol. 32, Issue 6, pp. 843-849, Mar. 2016. [pdf]
  2. J. Lyons, K.K. Paliwal, A. Dehzangi, R. Heffernan, T. Tsunoda and A. Sharma, ``Protein fold recognition using HMM-HMM alignment and dynamic programming'', Journal of Theoretical Biology, Vol. 393, pp. 67-74, Mar. 2016. [pdf]
  3. R. Chappel, B. Schwerin and K.K. Paliwal, ``Phase distortion resulting in a just noticeable difference in the perceived quality of speech'', Speech Communication, Vol. 81, pp. 138-147, July 2016. [pdf]
  4. S. So, A.E.W. George, R. Ghosh and K.K. Paliwal, ``A non-iterative Kalman filtering algorithm with dynamic gain adjustment for single-channel speech enhancement'', International Journal of Signal Processing Systems, Vol. 4, No. 4, pp. 263-268, Aug. 2016. [pdf]
  5. A. Chatterjee and K.K. Paliwal, ``Spectral subband centroids for tone vocoder simulations of cochlear implants'', International Journal of Signal Processing Systems, Vol. 4, No. 4, pp. 289-294, Aug. 2016. [pdf]
  6. A. Alatwi, S. So and K.K. Paliwal, ``A noise-robust linear prediction analysis for efficient speech coding'', Proc. 16th Australasian International Conf. on Speech Science and Technology (SST-2016), Parramatta, Sydney, Australia, pp. 205-208, Dec. 2016.
  7. A. Alatwi, S. So and K.K. Paliwal, ``Noise-robust linear prediction cepstral features for network speech recognition'', Proc. 16th Australasian International Conf. on Speech Science and Technology (SST-2016), Parramatta, Sydney, Australia, pp. 245-248, Dec. 2016.
  8. A.E.W. George, S. So, R. Ghosh and K.K. Paliwal, ``A Kalman filtering algorithm with joint metrics-based tuning for single-channel speech enhancement'' Proc. 16th Australasian International Conf. on Speech Science and Technology (SST-2016), Parramatta, Sydney, Australia, pp. 173-176, Dec. 2016.
  9. A. Alatwi, S. So and K.K. Paliwal, ``Perceptually motivated linear prediction features for network speech recognition'', Proc. 10th International Conf. on Signal Processing and Communication Systems, Surfers Paradise, Gold Coast, Australia, Dec. 2016. [pdf]


2015
  1. K.K. Paliwal and B. Schwerin, ``Modulation processing for speech enhancement'' in: T. Ogunfunmi, R. Togneri and M. Narasimha (eds.), Speech and Audio Processing for Coding, Enhancement and Recognition, Springer, New York, pp. 319-345, 2015.
  2. A. Dehzangi, R. Heffernan, A. Sharma, J. Lyons K.K. Paliwal and A. Sattar, ``Gram-positive and gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou's general PseAAC'', Journal of Theoretical Biology, Vol. 364, pp. 284-294, Jan. 2015. [pdf]
  3. A. Dehzangi, A. Sharma, K.K. Paliwal, J. Lyons and A. Sattar, ``A mixture of physicochemical and evolutionary-based feature extraction approaches for protein fold recognition'', International Journ. of Data Mining and Bioinfomatics, Vol. 11, No. 1, pp. 115-138, 2015. [pdf]
  4. A. Dehzangi, J. Lyons, A. Sharma, K.K. Paliwal and A. Sattar, ``Gram-positive and gram-negative subcellular localization using rotation forest and physicochemical-based features'', BMC Bioinformatics, 16(Suppl 4):51, Feb. 2015. [pdf]
  5. A. Sharma and K.K. Paliwal, ``A deterministic approach to regularized linear discriminant analysis'', Neurocomputing, Vol. 151, Part 1, pp. 207-214, Mar. 2015. [pdf]
  6. R. Heffernan, K.K. Paliwal, J. Lyons, A. Dehzangi, A. Sharma, J. Wang, A. Sattar, Y. Yang and Y. Zhou, ``Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning'', Scientific Reports, Vol. 5, Article No. 11476, June 2015. [pdf]
  7. A. Sharma and K.K. Paliwal, ``Linear discriminant analysis for small sample size problem: An overview'', Intern. Journal of Machine Learning and Cybernatics, Vol. 6, Issue 3, pp. 443-454, June 2015. [pdf]
  8. H. Saini, G. Raicar, A. Sharma, S. Lal, A. Dehzangi, J. Lyons, K.K. Paliwal, S. Imoto and S. Miyano, ``Probabilistic expression of spatially varied amino acid dimers into general form of Chou׳s pseudo amino acid composition for protein fold recognition'', Journal of Theoretical Biology, Vol. 380, pp. 291-298, Sept. 2015. [pdf]
  9. K.K. Paliwal, J. Lyons and R. Heffernan, ``A short review of deep learning neural networks in protein structure prediction problems'', Advanced Techniques in Biology and Medicine, Vol. 3, Issue 3, pp. 1-3, Sept. 2015. [pdf]
  10. J. Lyons, A. Dehzangi, R. Heffernan, Y. Yang, Y. Zhou, A. Sharma and K.K. Paliwal, ``Advancing the accuracy of protein fold recognition by utilizing profiles from hidden Markov models'', IEEE Trans. on NanoBioscience, Vol. 14, Issue 7, pp. 761-772, Oct. 2015. [pdf]
  11. R. Sharma, A. Dehzangi, J. Lyons, K.K. Paliwal, T. Tsunoda and A. Sharma, ``Predict Gram-positive and Gram-negative subcellular localization via incorporating evolutionary information and physicochemical features into Chou's general PseAAC'', IEEE Trans. on NanoBioscience, Vol. 14, Issue 8, pp. 915-926, Dec. 2015. [pdf]
  12. A. Sharma, R. Sharma, A. Dehzangi, J. Lyons and K.K. Paliwal and T. Tsunoda, ``Importance of dimensionality reduction in protein fold recognition'', Proc. 2nd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE), Fiji, Dec. 2015.


2014
  1. A. Dehzangi, K.K. Paliwal, J. Lyons, A. Sharma and A. Sattar, ``Proposing a higly accurate protein structural class predictor using segmentation-based features'', BMC Genomics, 15(Suppl 1):S2, Jan. 2014. [pdf]
  2. R. Chappel and K.K. Paliwal, ``An educational platform to demonstrate speech processing techniques on Android based smart phones and tablets'', Speech Communication, Vol. 57, pp. 13-38, Feb. 2014. [pdf]
  3. B. Schwerin and K.K. Paliwal, ``Using STFT real and imaginary parts of modulation signals for MMSE-based speech enhancement'', Speech Communication, Vol. 58, pp. 49-68, Mar. 2014. [pdf]
  4. A. Sharma, K.K. Paliwal, S. Imoto, S. Miyano, V. Sharma and R. Ananthanarayanan, ``A feature selection method using fixed-point algorithm for DNA microarray gene expression data'', Intern. Journal of Knowledge Based and Intelligent Engineering Systems, Vol. 18, No. 1, pp. 55-59, Mar. 2014. [pdf]
  5. K.K. Paliwal, A. Sharma, J. Lyons and A. Dehzangi, ``A tri-gram based feature extraction technique using linear probabilities of position specific scoring matrix for protein fold recognition'', IEEE Trans. Nanobioscience, Vol. 13, No. 1, pp. 44-50, Mar. 2014. [pdf]
  6. A. Sharma, K.K. Paliwal, S. Imoto and S. Miyano, ``A feature selection method using improved regularized linear discriminant analysis'', Machine Vision and Applications, Vol. 25, Issue 3, pp. 775-786, April 2014. [pdf]
  7. A. Dehzangi, K.K. Paliwal, A. Sharma, J. Lyons and A. Sattar, ``A segmentation-based method to extract structural and evolutionary features for protein fold recognition'', IEEE/ACM Trans. on Computational Biology and Bioinformatics, Vol. 11, No. 3, pp. 510-519, May-June 2014. [pdf]
  8. H. Saini, G. Raicar, A. Sharma, S. Lal, A. Dehzangi, A. Rajeshkannan, J. Lyons, N. Biswas and K.K. Paliwal, ``Protein structural class prediction via k-separated bigrams using position specific scoring matrix'', Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 18, No. 4, pp. 474-479, July 2014. [pdf]
  9. J. Lyons, N. Biswas, A. Sharma, A. Dehzangi and K.K. Paliwal, ``Protein fold recognition by alignment of amino acid residues using kernelized dynamic time warping'', Journal of Theoretical Biology, Vol. 354, pp. 137-145, Aug. 2014. [pdf]
  10. A. Dehzangi, J. Lyons, A. Sharma, K.K. Paliwal and A. Sattar, ``Gram-positive and gram-negative subcellular localization using rotation forest and physicochemical-based features'', Proc. 9th IAPR Intrenational Conference Pattern Recognition in Bioinformatics, PRIB 2014, Stockholm, Sweden, August 21-23, 2014.
  11. J. Lyons, A. Dehzangi, R. Hefferman, A. Sharma, K.K. Paliwal, A. Sattar, Y. Zhou and Y. Yang, ``Predicting backbone Ca angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network'', Journ. of Computational Chemistry, Vol. 35, No. 28, pp. 2040-2046, Oct. 2014. [pdf]
  12. B. Schwerin and K.K. Paliwal, ``An improved speech transmission index for intelligibility prediction'', Speech Communication, Vol. 65, pp. 9-19, Nov.-Dec. 2014. [pdf]
  13. K.K. Paliwal, A. Sharma, J. Lyons and A. Dehzangi, ``Improving protein fold recognition using the amalgamation of evolutionary-based and structural-based information'', BMC Bioinformatics, 15(Suppl 16):S12, Dec. 2014. [pdf]


2013
  1. A. Sharma, J. Lyons, A. Dehzangi and K.K. Paliwal, ``A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition'', Journal of Theoretical Biology, Vol. 320, pp. 41-46, Mar. 7, 2013. [pdf]
  2. A. Sharma, K.K. Paliwal, A. Dehzangi, J. Lyons, S. Imoto and S. Miyano, ``A strategy to select suitable physicochemical attributes of amino acids for protein fold recognition'', BMC Bioinformatics, 14:233, pp. 1-11, 2013. [pdf]
  3. A. Dehzangi, K.K. Paliwal, A. Sharma, O. Dehzangi and A. Sattar, ``A combination of feature extraction methods with an ensemble of different classifiers for protein structure class prediction problem'', IEEE/ACM Trans. on Computational Biology and Bioinformatics, Vol. 10, No. 3, pp. 564-575, May 2013. [pdf]
  4. A. Dehzangi, K.K. Paliwal, J. Lyons, A. Sharma and A. Sattar, ``Enhancing protein fold prediction accuracy using evolutionary and structural features'', Proc. Eight IAPR Intern. Conf. on Pattern Recognition in Bioinformatics (PRIB13), Nice, France, June 2013; Also in Pattern Recognition in Bioinformatics, Lecture Notes in Computer Science, Vol. 7986, pp. 196-207, June 2013.
  5. A. Dehzangi, K.K. Paliwal, J. Lyons, A. Sharma and A. Sattar, ``Exploring potential discriminatory information embedded in PSSM to enhance protein structural class prediction accuracy'', Proc. Eight IAPR Intern. Conf. on Pattern Recognition in Bioinformatics (PRIB13), Nice, France, June 2013; Also in Pattern Recognition in Bioinformatics, Lecture Notes in Computer Science, Vol. 7986, pp. 208-219, June 2013.
  6. A. Dehzangi, K.K. Paliwal, A. Sharma, J. Lyons and A. Sattar, ``Protein fold recognition using an overlapping segmentation approach and a mixture of feature extraction models'', Proc. 26th Australasian Joint Conf. on Artificial Intelligence, Dunedin, NZ, Dec. 2013; Also in AI 2013: Advances in Artificial Intelligence, Lecture Notes in Computer Science, Volume 8272, pp. 32-43, Dec. 2013.


2012
  1. A. Sharma and K.K. Paliwal, ``A gene selection algorithm using Bayesian classification'', American Journal of Applied Science, Vol. 9, No. 1, pp. 127-131, 2012. [pdf]
  2. K.K. Paliwal, B. Schwerin and K. Wojcicki, ``Speech enhancement using a minimum mean-square error short-time spectral modulation magnitude estimator'', Speech Communication, Vol. 54, No. 2, pp. 282-305, Feb. 2012. [pdf]
  3. K.K. Paliwal and A. Sharma, ``Improved pseudoinverse linear discriminant analysis method for dimensionality reduction'', International Journal of Pattern Recognition and Artificial Intelligence, Vol. 26, No. 1, pp. 1250002-1--1250002-9, Feb. 2012. [pdf]
  4. A.M. Gomez, B. Schwerin and K.K. Paliwal, ``Improving objective intelligibility prediction by combining correlation and coherence based methods with a measure based on the negative distortion ratio'', Speech Communication, Vol. 54, No. 3, pp. 503-515, Mar. 2012. [pdf]
  5. A. Sharma and K.K. Paliwal, ``A new perspective to null linear discriminant analysis method and its fast implementation using random matrix multiplication with sacatter matrices'', Pattern Recognition, Vol. 45, No. 6, pp. 2205-2213, June 2012. [pdf]
  6. A. Sharma and K.K. Paliwal, ``A two-stage linear discriminant analysis for face recognition'', Pattern Recognitioni Letters, Vol. 33, No. 9, pp. 1157-1162, July 2012. [pdf]
  7. R. Chappel and K.K. Paliwal, ``Speech Enhancement for Android (SEA): A Speech Processing Demonstration Tool for Android Based Smart Phones and Tablets'', Proc. INTERSPEECH 2012, Portland, Oregon, USA, Sept. 2012. [pdf]
  8. J.G. O'Connell, K.K. Paliwal and Kamil Wojcicki, ``Speech enhancement of spectral magnitude bin trajectories using Gaussian mixture-model based minimum mean-square error estimators", Proc. Australian Conf. Speech Science and Technology (SST-2012), Sydney, Australia, pp. 25-28, Dec. 2012. [pdf]
  9. B. Schwerin and K.K. Paliwal, ``Speech enhancement using STFT of real and imaginary parts of modulation signals", Proc. Australian Conf. Speech Science and Technology (SST-2012), Sydney, Australia, pp. 33-36, Dec. 2012. [pdf]
  10. R. Chappel and K.K. Paliwal, ``A speech processing research platform for Android based smart phones and ablets", Proc. Australian Conf. Speech Science and Technology (SST-2012), Sydney, Australia, pp. 177-180, Dec. 2012. [pdf]
  11. A. Sharma, K.K. Paliwal, S. Imoto and S. Miyano, ``Principal component analysis using QR decomposition'', International Journal of Machine Learning and Cybernetics, Published online Sept. 2012, DOI: 10.1007/s13042-012-0131-7. [pdf]


2011
  1. A. Stark and K.K. Paliwal, ``Use of speech presence uncertainity with MMSE spectral energy estimation for robust speech recognition'', Speech Communication, Vol. 53, No. 1, pp. 51-61, Jan. 2011. [pdf]
  2. K.K. Paliwal, B. Schwerin and K.K. Wojcicki, ``Role of modulation magnitude and phase spectrum towards speech intelligibility'', Speech Communication, Vol. 53, No. 3, pp. 327-339, Mar. 2011. [pdf]
  3. S. So and K.K. Paliwal, ``Suppressing the influence of additive noise on Kalman filter gain for low residual noise speech enhancement'' Speech Communication, Vol. 53, No. 3, pp. 355-378, Mar. 2011. [pdf]
  4. A. Stark and K.K. Paliwal, ``MMSE estimation of log-filterbank energies for robust speech recognition'', Speech Communication, Vol. 53, No. 3, pp. 403-416, Mar. 2011. [pdf]
  5. K.K. Paliwal, K.K. Wojcicki and B.J. Shannon, ``The importance of phase in speech enhancement'', Speech Communication, Vol. 53, No. 4, pp. 465-494, Apr. 2011. [pdf]
  6. S. So and K.K. Paliwal, ``Modulation-domain Kalman filtering for single-channel speech enhancement'', Speech Communication, Vol. 53, No. 6, pp. 818-829, July 2011. [pdf]
  7. K.K. Paliwal, B. Schwerin and K. Wojcicki, ``Single channel speech enhancement using MMSE estimation of short-time modulation magnitude spectrum'', Proc. INTERSPEECH 2011, Florence, Italy, pp. 1209-1212, Aug. 2011. [pdf]
  8. A. Gomez, B. Schwerin and K.K. Paliwal, ``Objective Intelligibility prediction of speech by combining correlation and distortion based techniques'', Proc. INTERSPEECH 2011, Florence, Italy, pp. 1225-1228, Aug. 2011. [pdf]
  9. K.K. Paliwal and A. Sharma, ``Approximate LDA technique for dimensionality reduction in the small sample size case'', Journal of Pattern Recognition Research, Vol. 6, No. 2, pp. 298-306, 2011. [pdf]


2010
  1. K.K. Paliwal and K. Yao, ``Robust speech recognition under noisy ambient conditions'' in: H. Aghajan, R.L. Delgado and J.C. Augusto (eds.), Human-Centric Interfaces for Ambient Intelligence, Elsevier, Amsterdam, pp. 135-162, 2010. [pdf]
  2. K.K. Paliwal, K.K. Wojcicki and B. Schwerin, ``Single-channel speech enhancement using spectral subtraction in the short-time modulation domain'', Speech Communication, Vol. 52, Issue 5, pp. 450-475, May 2010. [pdf]
  3. A. Sharma and K.K. Paliwal, ``Regularisation of eigenfeatures by extrapolation of scatter-matrix in face-recognition problem'', Electronics Letters, Vol. 46, No. 10, pp. 682-683, May 2010. [pdf]
  4. A. Sharma and K.K. Paliwal, ``An improved nearest centroid classifier with shrunken distance measure for null LDA method on cancer classification problem'', Electronics Letters, Vol. 16, No. 18, pp. 1251-1252, Sept. 2010. [pdf]
  5. S. So, K.K. Wojcicki and K.K. Paliwal, ``Single-channel speech enhancement using Kalman filtering in modulation domain'', Proc. INTERSPEECH 2010, Chiba, Japan, pp. 993-996, Sept. 2010. [pdf]
  6. S. So and K.K. Paliwal, ``Fast converging iterative Kalman filtering for speech enhancement using long and overlapped tapered windows with large side lobe attenuation'', Proc. INTERSPEECH 2010, Chiba, Japan, pp. 1081-1084, Sept. 2010. [pdf]
  7. K.K. Paliwal, J.G. Lyons, S. So, A.P. Stark and K.K. Wojcicki, ``Comparative evaluation of speech enhancement methods for automatic speech recognition'', Proc. International Conference on Signal Processing and Communication Systems, Gold Coast, Australia, Dec. 2010. [pdf]
  8. K.K. Paliwal, J.G. Lyons and K.K. Wojcicki, ``Preference for 20-40 ms window duration in speech analysis'', Proc. International Conference on Signal Processing and Communication Systems, Gold Coast, Australia, Dec. 2010. [pdf]
  9. J.G. Lyons, J.G. O'Connell and K.K. Paliwal, ``Using long-term information to improve robustness in speaker identification'', Proc. International Conference on Signal Processing and Communication Systems, Gold Coast, Australia, Dec. 2010. [pdf]
  10. K.K. Paliwal and A. Sharma, ``Improved direct LDA and its application to DNA gene microarray data'', Pattern Recognion Letters, Vol. 31, No. 16, pp. 2489-2492, Dec. 2010. [pdf]


2009
  1. K.K. Paliwal, B.J. Shannon, J.G. Lyons and K.K. Wojcicki, ``Speech-signal-based frequency warping'', IEEE Signal Processing Letters, Vol. 16, pp. 319-322, Apr. 2009. [pdf]
  2. S. So, K.K. Wojcicki, J.G. Lyons, A.P. Stark and K.K. Paliwal, ``Kalman filter with phase spectrum compensation algorithm for speech enhancement'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Taipei, Taiwan, pp. 4405-4408, Apr. 2009. [pdf]
  3. A.P. Stark and K.K. Paliwal, ``Group-delay-deviation based spectral analysis of speech'', Proc. INTERSPEECH 2009, Brighton, U.K., pp. 1083-1086, Sep. 2009. [pdf]
  4. K.K. Paliwal, B. Schwerin and K.K. Wojcicki, ``Modulation domain spectral subtraction for speech enhancement'', Proc. INTERSPEECH 2009, Brighton, U.K., pp. 1327-1330, Sep. 2009. [pdf]


2008
  1. A. Sharma and K.K. Paliwal, ``A gradient linear discriminant analysis for small sample sized problem'', Neural Processing Letters, Vol. 27, No. 1, pp. 17-24, Feb. 2008. [pdf]
  2. K.K. Wojcicki, M. Milacic, A. Stark, J.G. Lyons and K.K. Paliwal, ``Exploiting conjugate symmetry of the short-time Fourier spectrum for speech enhancement'', IEEE Signal Processing Letters, Vol. 15, pp. 461-464, 2008. [pdf]
  3. A. Sharma and K.K. Paliwal, "Cancer classification by gradient LDA technique using microarray gene expression data", Data and Knowledge Engineering, Vol. 66, pp. 338-347, 2008. [pdf]
  4. A. Sharma and K.K. Paliwal, ``Rotational linear discriminant analysis technique for dimensionality reduction'', IEEE Trans. Knowledge and Data Engineering, Vol. 20, No. 10, pp. 1336-1347, Oct. 2008. [pdf]
  5. K.K. Wojcicki, and K.K. Paliwal. ``On the relative importance of the short-time magnitude and phase spectra towards speaker dependent information'', Proc. ISCA Tutorial and Research Workshop (ITRW), Aalborg, Denmark, Jun. 2008. [pdf]
  6. J.G. Lyons and K.K. Paliwal, ``Effect of compressing the dynamic range of the power spectrum in modulation filtering based speech enhancement'', Proc. INTERSPEECH 2008, Brisbane, Australia, pp. 387-390, Sep. 2008. [pdf]
  7. S. So and K.K. Paliwal, ``A long state vector Kalman filter for speech enhancement'', Proc. INTERSPEECH 2008, Brisbane, Australia, pp. 391-394, Sep. 2008. [pdf]
  8. A.P. Stark, K.K. Wojcicki, J.G. Lyons and K.K. Paliwal, ``Noise driven short time phase spectrum compensation procedure for speech enhancement'', Proc. INTERSPEECH 2008, Brisbane, Australia, pp. 549-552, Sep. 2008. [pdf]
  9. A.P. Stark and K.K. Paliwal, ``Speech analysis using instantaneous frequency deviation'', Proc. INTERSPEECH 2008, Brisbane, Australia, pp. 2602-2605, Sep. 2008. [pdf]
  10. M.C. Cohen and K.K. Paliwal, ``Classifying microarray cancer datasets using nearest subspace classification'', Proc. Third IAPR Intern. Conf. Pattern Recognition in Bioinformatics (PRIB 2008), Melbourne, Australia, Oct. 2008. [pdf]
  11. K.K. Paliwal and K.K. Wojcicki, ``Effect of analysis window duration on speech intelligibility'', IEEE Signal Processing Letters, Vol. 15, pp. 785-788, 2008. [pdf]
  12. S. So and K.K. Paliwal, ``Quantization of speech features: source coding'' in: Z.H. Tan and B. Lindberg (eds.), Automatic Speech Recognition on Mobile Devices and over Communication Networks, Springer-Verlag, London, pp. 131-161, 2008. [pdf]
  13. B. Schwerin and K.K. Paliwal, ``Local-DCT features for facial recognition'', Proc. Intern. Conf. Signal Processing and Communication Systems, Gold Coast, Australia, Dec. 2008. [pdf]
  14. M. Davaatsagaan and K.K. Paliwal, 'A response generation in the Mongolian spoken language system for accessing to multimedia knowledge base', Proc. IEEE Workshop on Spoken Language Technology, Goa, India, Dec. 2008.


2007
  1. L.D. Alsteris and K.K. Paliwal, ``Iterative reconstruction of speech from short-time Fourier transform phase and magnitude spectra'', Computer Speech and Language, Vol. 21, No. 1, pp. 174-186, Jan. 2007. [pdf]
  2. S. So and K.K. Paliwal, ``A comparative study of LPC parameter representations and quantisation schemes for wideband speech coding'', Digital Signal Processing, Vol. 17, No. 1, pp. 114-137, Jan. 2007. [pdf]
  3. S. So and K.K. Paliwal, ``Efficient product code vector quantisation using the switched split vector quantiser'', Digital Signal Processing, Vol. 17, No. 1, pp. 138-171, Jan. 2007. [pdf]
  4. K.K. Wojcicki and K.K. Paliwal, ``Importance of the dynamic range of an analysis window function for phase-only and magnitude-only reconstruction of speech'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Honolulu, Hawaii, USA, Vol. IV, pp. 729-733, Apr. 2007. [pdf]
  5. B. Shannon and K.K. Paliwal, ``Effect of speech and noise cross correlation on AMFCC speech recognition features'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Honolulu, Hawaii, USA, Vol. IV, pp. 1033-1036, Apr. 2007. [pdf]
  6. L.D. Alsteris and K.K. Paliwal, ``Short-time phase spectrum in speech processing: A review and some experimental results'', Digital Signal Processing, Vol. 17, pp. 578-616, May 2007. [pdf]
  7. A. Sharma and K.K. Paliwal, ``Fast principal component analysis using fixed-point algorithm'', Pattern Recognition Letters, Vol. 28, No. 10, pp. 1151-1155, July 2007. [pdf]
  8. K.K. Wojcicki, S. So and K.K. Paliwal, ``The effect of the additivity assumption on time and frequency domain Wiener filtering for speech enhancement'', Proc. INTERSPEECH 2007, Antwerp, Belgium, pp. 798-601, Aug. 2007. [pdf]
  9. A. Sharma and K.K. Paliwal, ``Detecting masquerades using a combination of Naive Bayes and weighted RBF approach'', Journal in Computer Virology, Vol. 1, No. 3, pp. 237-245, Aug. 2007. [pdf]
  10. S. So and K.K. Paliwal, ``Efficient vector quantisation of wideband LPC parameters using the ML-SSVQ'', Proc. Griffith School of Engineering Research Conference, Brisbane, Australia, Oct. 2007.
  11. B.R. Wildermoth and K.K. Paliwal, ``A new approach to speaker modelling in speaker recognition'', Proc. Griffith School of Engineering Research Conference, Brisbane, Australia, Oct. 2007.
  12. A. Stark and K.K. Paliwal, ``An empirical comparison of three initialization techniques for categorical K-means algorithms'', Proc. Griffith School of Engineering Research Conference, Brisbane, Australia, Oct. 2007.
  13. J.G. Lyons and K.K. Paliwal, ``Robustness of speech reconstructed from MFCC and LPC features'', Proc. Griffith School of Engineering Research Conference, Brisbane, Australia, Oct. 2007.
  14. K.K. Wojcicki and K.K. Paliwal, ``Effect of the dynamic range of an analysis window on phase-only and magnitude-only speech reconstruction for human speaker verification'', Proc. Griffith School of Engineering Research Conference, Brisbane, Australia, Oct. 2007.
  15. A. Sharma, A.K. Pujari and K.K. Paliwal, ``Intrusion detection using text processing techniques with a kernel based similarity measure'', Computers and Security, No. 7-8, pp. 488-495, Dec. 2007. [pdf]


2006
  1. A. Sharma, K.K. Paliwal and G.C. Onwubolu, ``Splitting technique initialization in local PCA'', Journal of Computer Science, Vol. 2, No. 1, pp. 53-58, 2006. [pdf]
  2. B. Gajic and K.K. Paliwal, ``Robust speech recognition in noisy environments based on subband spectral centroid histograms'', IEEE Trans. Audio, Speech and Language Processing, Vol. 14, No. 2, pp. 600-608, Mar. 2006. [pdf]
  3. S. So and K.K. Paliwal, ``Multi-frame GMM-based block quantisation for distributed speech recognition under noisy conditions'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Toulouse, France, Vol. I, pp. 189-192, May 2006. [pdf]
  4. L.D. Alsteris and K.K. Paliwal, ``Further intelligibility results from human listening tests using the short-time phase spectrum'', Speech Communication, Vol. 48, No. 6, 727-736, June 2006. [pdf]
  5. S. So and K.K. Paliwal, ``Scalable distributed speech recognition using Gaussian mixture model-based block quantization'', Speech Communication, Vol. 48, No. 6, pp. 746-758, June 2006. [pdf]
  6. A. Sharma, K.K. Paliwal and G.C. Onwubolu, ``Class-dependent PCA, MDC, and LDA: A combined classifier for pattern recognition'', Pattern Recognition, Vol. 39, No. 7, pp. 1215-1229, July 2006. [pdf]
  7. S. So and K.K. Paliwal, ``Empirical lower bound on the bitrate for the transparent memoryless coding of wideband LPC parameters'', IEEE Signal Processing Letters, Vol. 13, No. 9, pp. 569-572, Sept. 2006. [pdf]
  8. B. Shannon and K.K. Paliwal, ``Role of phase estimation in speech enhancement'', Proc. Intern. Conf. Spoken Language Processing (INTERSPEECH 2006 - ICSLP), Pittsburgh, USA, pp. 1423-1426, Sept. 2006. [pdf]
  9. B. Shannon and K.K. Paliwal, ``Speech enhancement based on spectral estimation from higher-lag autocorrelation'', Proc. Intern. Conf. Spoken Language Processing (INTERSPEECH 2006 - ICSLP), Pittsburgh, USA, pp. 1427-1430, Sept. 2006. [pdf]
  10. A. Sharma and K.K. Paliwal, ``Subspace independent component analysis using vector kurtosis'', Pattern Recognition, Vol. 39, No. 11, pp. 2227-2232, Nov. 2006. [pdf]
  11. A. Sharma, K.K. Paliwal and G.C. Onwubolu, ``Rotational linear discriminant analysis using Bayes rule for dimensionality reduction'', Journal of Computer Science, Vol. 2, No. 9, pp. 754-757, 2006. [pdf]
  12. B. Shannon and K.K. Paliwal, ``Feature extraction from higher-lag autocorrelation coefficients for robust speech recognition'', Speech Communication, Vol. 48, No. 11, pp. 1458-1485, Nov. 2006. [pdf]
  13. K.K. Wojcicki and K.K. Paliwal, ``Spectral subtraction with variance reduced noise spectrum estimates'', Proc. Australian Conf. Speech Science and Technology (SST-2006), Auckland, New Zealand, pp. 76-81, Dec. 2006. [pdf]


2005
  1. K.K. Paliwal and L.D. Alsteris, ``On the usefulness of STFT phase spectrum in human listening tests'', Speech Communication, Vol. 45, No. 2, pp. 153-170, Feb. 2005. [pdf]
  2. S. So and K.K. Paliwal, ``Multi-frame GMM-based block quantisation of line spectral frequencies for wideband speech coding'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Philadelphia, Vol. I, pp. 121-124, Mar. 2005. [pdf]
  3. B. Shannon and K.K. Paliwal, ``Influence of autocorrelation lag ranges on robust speech recognition'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Philadelphia, Vol. I, pp. 545-548, Mar. 2005. [pdf]
  4. K. Yao, K.K. Paliwal and T.W. Lee, ``Generative factor analyzed HMM for automatic speech recognition'', Speech Communication, Vol. 45, No. 4, pp. 435-454, Apr. 2005. [pdf]
  5. K.K. Paliwal and S. So, ``A fractional bit encoding technique for the GMM-based block quantization of images'', Digital Signal Processing, Vol. 15, No. 3, pp. 255-275, May 2005. [pdf]
  6. K.K. Paliwal and S. So, ``Low complexity GMM-based block quantisation of images using the discrete cosine transform'', Signal Processing: Image Communication, Vol. 20, No. 5, pp. 435-446, June 2005. [pdf]
  7. B. Shannon and K.K. Paliwal, ``Spectral estimation using higher-lag autocorrelation coefficients with applications to speech recognition'', Proc. Intern. Symp. on Signal Processing and Its Applications (ISSPA-2005), Sydney, Australia, Aug. 2005. [pdf]
  8. S. So and K.K. Paliwal, ``A comparison of LSF and ISP representations for wideband LPC parameter coding using the switched split vector quantiser'', Proc. Intern. Symp. on Signal Processing and Its Applications (ISSPA-2005), Sydney, Australia, Aug. 2005. [pdf]
  9. L.D. Alsteris and K.K. Paliwal, ``Evaluation of the modified group delay feature for isolated word recognition'', Proc. Intern. Symp. on Signal Processing and Its Applications (ISSPA-2005), Sydney, Australia, Aug. 2005. [pdf]
  10. S. So and K.K. Paliwal, ``Switched split vector quantisation of line spectral frequencies for wideband speech coding'', Proc. European Conference on Speech Communication and Technology (INTERSPEECH 2005 - EUROSPEECH), Lisbon, Portugal, pp. 2705-2708, Sept. 2005. [pdf]
  11. L.D. Alsteris and K.K. Paliwal, ``Some experiments on iterative reconstruction of speech from STFT phase and magnitude spectra'', Proc. European Conference on Speech Communication and Technology (INTERSPEECH 2005 - EUROSPEECH), Lisbon, Portugal, pp. 337-340, Sept. 2005. [pdf]
  12. S. So and K.K. Paliwal, ``Improved noise-robustness in distributed speech recognition via perceptually-weighted vector quantisation of filterbank energies'', Proc. European Conference on Speech Communication and Technology (INTERSPEECH 2005 - EUROSPEECH), Lisbon, Portugal, pp. 941-944, Sept. 2005. [pdf]
  13. A. Sharma, K.K. Paliwal and G.C. Onwubolu, ``Pattern classification: An improvement using combination of VQ and PCA techniques'', American Journal of Applied Science, Vol. 2, No. 10, pp. 1445-1455, 2005. [pdf]
  14. B. Wildermoth and K.K. Paliwal, ``Speaker recognition using acoustically derived units'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2005. [pdf]
  15. S. So and K.K. Paliwal, ``Switched split vector quantiser and its application to LPC parameter quantisation in wideband speech coding'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2005. [pdf]
  16. B. Shannon and K.K. Paliwal, ``Noise robust speech recognition using higher-lag autocorrelation coefficients'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2005. [pdf]
  17. D. Zhu, S.Nakamura, K.K. Paliwal and R. Wang, ``Maximum likelihood sub-band adaptation for robust speech recognition'', Speech Communication, Vol. 47, No. 3, pp. 243-264, Nov. 2005. [pdf]
  18. S. So and K.K. Paliwal, ``Multi-frame GMM-based block quantisation of line spectral frequencies'', Speech Communication, Vol. 47, No. 3, pp. 265-276, Nov. 2005. [pdf]


2004
  1. K. Yao, K.K. Paliwal and S. Nakamura, ``Noise adaptive speech recognition based on sequential noise parameter estimation'', Speech Communication, Vol. 42, No. 1, pp. 5-23, Jan. 2004. [pdf]
  2. J. Chen, Y. Huang, Q. Li and K.K. Paliwal, ``Recognition of noisy speech using dynamic spectral subband centroids'', IEEE Signal Processing Letters, Vol. 11, No. 2, pp. 258-261, Feb. 2004. [pdf]
  3. D. Zhu and K.K. Paliwal, ``Product of power spectrum and group delay function for speech recognition'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Vol. I, pp. 125-128, Montreal, May 2004. [pdf]
  4. K.K. Paliwal and S. So, ``Multiple frame block quantization of line spectral frequencies using Gaussian mixture models'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Vol. I, pp. 149-152, Montreal, May 2004. [pdf]
  5. L.D. Alsteris and K.K. Paliwal, ``Importance of window shape for phase-only reconstruction of speech'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Vol. I, pp. 573-576, Montreal, May 2004. [pdf]
  6. C. Sanderson and K.K. Paliwal, ``Identity verification using speech and face information'', Digital Signal Processing, Vol. 14, No. 5, pp. 449-480, Sept. 2004. [pdf]
  7. B. Shannon and K.K. Paliwal, ``MFCC computation from magnitude spectrum of higher lag autocorrelation coefficients for robust speech recognition'', Proc. Intern. Conf. Spoken Language Processing (INTERSPEECH 2004 - ICSLP), Jeju, South Korea, Oct. 2004. [pdf]
  8. K.K. Paliwal and S. So, ``Scalable distributed speech recognition using multi-frame GMM-based block quantization'', Proc. Intern. Conf. Spoken Language Processing (INTERSPEECH 2004 - ICSLP), Jeju, South Korea, Oct. 2004. [pdf]
  9. L.D. Alsteris and K.K. Paliwal, ``ASR on speech reconstructed from short-time Fourier phase spectra'', Proc. Intern. Conf. Spoken Language Processing (INTERSPEECH 2004 - ICSLP), Jeju, South Korea, Oct. 2004. [pdf]
  10. S. So and K.K. Paliwal, ``Efficient Vector Quantisation of Line Spectral Frequencies Using the Switched Split Vector Quantiser'', Proc. Intern. Conf. Spoken Language Processing (INTERSPEECH 2004 - ICSLP), Jeju, South Korea, Oct. 2004. [pdf]


2003
  1. K.K. Paliwal, ``Usefulness of phase in speech processing'', Proc. IPSJ Spoken Language Processing Workshop, Gifu, Japan, pp. 1-6, Feb. 2003. [pdf]
  2. C. Sanderson and K.K. Paliwal, ``Noise compensation in a person verification system using face and multiple speech features'', Pattern Recognition, Vol. 36, No. 2, pp. 293-302, Feb. 2003. [pdf]
  3. B. Gajic and K.K. Paliwal, ``Robust speech recognition using features based on zero crossings with peak amplitudes'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Vol. I, pp. 64-67, Hong Kong, April 2003. [pdf]
  4. C. Sanderson and K.K. Paliwal, ``Noise resistant audio-visual verification via structural constraints'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Vol. V, pp. 716-719, Hong Kong, April 2003. [pdf]
  5. C. Sanderson and K.K. Paliwal, ``Features for robust face based identity verification'', Signal Processing, Vol. 83, No. 5, pp. 931-940, May 2003. [pdf]
  6. K.K. Paliwal and B.S. Atal, ``Frequency-related representation of speech'', Proc. European Conference on Speech Communication and Technology (INTERSPEECH 2003 - EUROSPEECH), Geneva, Switzerland, pp. 65-68, Sept. 2003. [pdf]
  7. D. Zhu, S. Nakamura, K.K. Paliwal and R. Wang, ``Maximum likelihood sub-band weighting for robust speech recognition'', Proc. European Conference on Speech Communication and Technology (INTERSPEECH 2003 - EUROSPEECH), Geneva, Switzerland, pp. 673-676, Sept. 2003. [pdf]
  8. K. Yao, K.K. Paliwal and T.W. Lee, ``Speech recognition with a generative factor analyzed hidden Markov model'', Proc. European Conference on Speech Communication and Technology (INTERSPEECH 2003 - EUROSPEECH), Geneva, Switzerland, pp. 849-852, Sept. 2003. [pdf]
  9. K. Yao, K.K. Paliwal and S. Nakamura, ``Model based speech recognition with environment parameters estimated by noise adaptive speech recognition with prior'', Proc. European Conference on Speech Communication and Technology (INTERSPEECH 2003 - EUROSPEECH), Geneva, Switzerland, pp. 1273-1276, Sept. 2003. [pdf]
  10. K.K. Paliwal and L.D. Alsteris, ``Usefulness of phase spectrum in human speech perception'', Proc. European Conference on Speech Communication and Technology (INTERSPEECH 2003 - EUROSPEECH), Geneva, Switzerland, pp. 2117-2120, Sept. 2003. [pdf]
  11. X. Wang and K.K. Paliwal, ``Feature extraction and dimensionality reduction algorithms and their applications in vowel recognition'', Pattern Recognition, Vol. 36, No. 10, pp. 2429-2439, Oct. 2003. [pdf]
  12. J. Chen, K.K. Paliwal and S. Nakamura, ``Cepstrum derived from differentiated power spectrum for robust speech recognition'' Speech Communication, Vol. 41, No. 2-3, pp. 469-484, Oct. 2003. [pdf]
  13. C. Sanderson and K.K. Paliwal, ``Fast features for face authentication under illumination direction changes'', Pattern Recognition Letters, Vol. 24, No. 14, pp. 2409-2419, Oct. 2003. [pdf]
  14. F. Golchin and K.K. Paliwal, ``Quadtree-based classification in subband image coding'', Digital Signal Processing, Vol. 13, No. 4, pp. 656-668, Oct. 2003. [pdf]
  15. L.D. Alsteris and K.K. Paliwal, ``Intelligibility of speech from phase spectrum'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2003. [pdf]
  16. B. Shannon and K.K. Paliwal, ``A comparative study of filter bank spacing for speech recognition'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2003. [pdf]
  17. B. Wildermoth and K.K. Paliwal, ``GMM based speaker recognition on readily available databases'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2003. [pdf]
  18. S. So and K.K. Paliwal, ``Low complexity Gaussian mixture model-based block quantisation of images'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2003. [pdf]
  19. C. Sanderson and K.K. Paliwal, ``Structurally noise resistant classifier for multi-modal person verification'', Pattern Recognition Letters, Vol. 24, No. 16, pp. 3089-3099, Dec. 2003. [pdf]


2002
  1. K. Yao, K.K. Paliwal and S. Nakamura, ``Noise adaptive speech recognition in time-varying noise based on sequential Kullback proximal algorithm'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Orlando, Florida, USA, pp. I189-I192, May 2002. [pdf]
  2. X. Wang and K.K. Paliwal, ``A modified minimum classification error (MCE) training algorithm for dimensionality reduction'', Journal of VLSI Signal Processing Systems, Vol. 32, No. 1-2, pp. 19-28, Aug. 2002. [pdf]
  3. K. Yao, K.K. Paliwal and S. Nakamura, ``Noise adaptive speech recognition with acoustic models trained from noisy speech evaluated on Aurora-2 database'', Proc. Intern. Conf. Spoken Language Processing (INTERSPEECH 2002 - ICSLP), Denver, Colorado, USA, pp. 2437-2440, Sept. 2002. [pdf]
  4. C. Sanderson and K.K. Paliwal, ``Polynomial features for robust face authentication'', Proc. IEEE Intern. Conf. on Image Processing, Rochester, NY, USA, Vol. III, pp. 997-1000, Sept. 2002. [pdf]
  5. C. Sanderson and K.K. Paliwal, ``Likelihood normalization for face authentication in variable recording conditions'', Proc. IEEE Intern. Conf. on Image Processing, Rochester, NY, USA, Vol. I, pp. 301-304, Sept. 2002. [pdf]
  6. X. Wang and K.K. Paliwal, ``Discriminative learning and informative learning in pattern recognition'', Proc. 9th Intern. Conf. on Neural Information Processing, (ICONIP-02), Vol. 2, pp. 862-865, Nov. 2002.
  7. S. So and K.K. Paliwal, ``Efficient block coding of images using Gaussian mixture models'', Proc. Fourth Australasian Workshop on Signal Processing and Applications, (WoSPA-2002), Brisbane, Australia, pp. 71-74, Dec. 2002. [pdf]
  8. X. Wang and K.K. Paliwal, ``Feature extraction for integrated pattern recognition systems'', Proc. Fourth Australasian Workshop on Signal Processing and Applications, (WoSPA-2002), Brisbane, Australia, pp. 85-88, Dec. 2002. [pdf]
  9. K.K. Paliwal and N.P. Koestoer, ``Robust linear prediction analysis for low bitrate speech coding'', Proc. Fourth Australasian Workshop on Signal Processing and Applications, (WoSPA-2002), Brisbane, Australia, pp. 97-100, Dec. 2002. [pdf]
  10. C. Sanderson and K.K. Paliwal, ``Fast feature extraction method for robust face verification'', Electronics Letters, Vol. 38, No. 25, pp. 1648-1650, Dec. 2002. [pdf]


2001
  1. J. Chen, K.K. Paliwal and S. Nakamura, ``Subtraction of additive noise from corrupted speech for robust speech recognition'', Proc. Acoustical Society of Japan (ASJ) Conference, Tsukuba, Japan, pp. 63-64, March 2001. [pdf]
  2. K. Yao, K.K. Paliwal, B.E. Shi and S. Nakamura, ``Noise compensation by a sequential Kullback proximal algorithm'', Proc. Intern. Workshop on Hands-Free Speech Communication, Kyoto, Japan, pp. 139-142, Apr. 2001. [pdf]
  3. C. Sanderson and K.K. Paliwal, ``Noise compensation in a multi-modal verification system'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Salt Lake City, Utah, USA, pp. 157-160, May 2001. [pdf]
  4. B. Gajic and K.K. Paliwal, ``Robust feature extraction using subband spectral centroid histograms'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Salt Lake City, Utah, USA, pp. 85-88, May 2001. [pdf]
  5. J. Chen, K.K. Paliwal M. Mizumachi and S. Nakamura, ``Robust MFCCs derived from differentiated power spectrum'', Proc. Intern. Conf. on Speech Processing, TaeJon, Korea, Vol. 2, pp. 577-582, Aug. 2001. [pdf]
  6. C. Sanderson and K.K. Paliwal, ``Information fusion for robust speaker verification'', Proc. European Conf. Speech Communication and Technology (INTERSPEECH 2001 - EUROSPEECH), Aalborg, Denmark, pp. 755-758, Sept. 2001. [pdf]
  7. K. Yao, K.K. Paliwal and S. Nakamura, ``Sequential noise compensation by a sequential Kullback proximal algorithm'', Proc. European Conf. Speech Communication and Technology (INTERSPEECH 2001 - EUROSPEECH), Aalborg, Denmark, pp. 1139-1142, Sept. 2001. [pdf]
  8. J. Chen, K.K. Paliwal and S. Nakamura, ``Sub-band based additive noise removal for robust speech recognition'', Proc. European Conf. Speech Communication and Technology (INTERSPEECH 2001 - EUROSPEECH), Aalborg, Denmark, pp. 571-574, Sept. 2001. [pdf]
  9. B. Gajic and K.K. Paliwal, ``Robust parameters for speech recognition based on subband spectral centroid histograms'', Proc. European Conf. Speech Communication and Technology (INTERSPEECH 2001 - EUROSPEECH), Aalborg, Denmark, pp. 591-594, Sept. 2001. [pdf]
  10. T.A. Myrvoll, K.K. Paliwal and T. Svendsen, ``Fast adaptation using constrained affine transformations with hierarchical priors'', Proc. European Conf. Speech Communication and Technology (INTERSPEECH 2001 - EUROSPEECH), Aalborg, Denmark, pp. 1233-1236, Sept. 2001. [pdf]
  11. K. Yao, K.K. Paliwal and S. Nakamura, ``Feature extraction and model-based noise compensation for noisy speech recognition evaluated on AURORA 2 task'', Proc. European Conf. Speech Communication and Technology (INTERSPEECH 2001 - EUROSPEECH), Aalborg, Denmark, pp. 233-236, Sept. 2001. [pdf]
  12. B. Gajic and K.K. Paliwal, ``Speech parameterization for automatic speech recognition in noisy conditions'', Proc. Norwegian Symp. Signal Processing, NORSIG-01, Trondheim, Norway, Oct. 2001. [pdf]
  13. X. Wang and K.K. Paliwal, ``Generalized MCE training algorithm for feature dimensionality reduction'' Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2001. X. Wang and K.K. Paliwal, ``Generalized MCE training algorithm for feature dimensionality reduction'' Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2001. [pdf]
  14. C. Sanderson and K.K. Paliwal, ``Robust face-based identity verification'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2001. [pdf]
  15. S. So and K.K. Paliwal, ``Comparison of quantization techniques for DCT-based image coding'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2001. [pdf]
  16. N. Koestoer and K.K. Paliwal, ``Robust spectrum analysis for applications in speech processing'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2001. [pdf]
  17. B. Wildermoth and K.K. Paliwal, ``Reducing inter-session variability with transitional spectral information'', Proc. Microelectronic Engineering Research Conference, Brisbane, Australia, Nov. 2001. [pdf] ``Joint cohort normalization in a multi-feature speaker verification system'', Proc. 10th IEEE International Conference on Fuzzy Systems, Melbourne, Australia, pp. 232-235, Dec. 2001. [pdf]


2000
  1. F. Golchin and K.K. Paliwal, ``Lossless coding of MPEG-1 Layer III encoded audio streams'', Proc. IEEE Intern. Conf. on Acoustics, Speech and Signal Processing, Istanbul, Turkey, pp. 885-888, June 2000. [pdf]
  2. S. Sridharan, J. Leis and K.K. Paliwal, ``Speech coding'', in: S. Katagiri (ed.), Handbook of Neural Networks for Speech Processing, pp. 121-155, Artech House, Boston, 2000. [pdf]
  3. V. Ramasubramanian and K.K. Paliwal, ``Fast nearest-neighbor search algorithms based on approximation-elimination search'', Pattern Recognition, Vol. 33, No. 9, pp. 1497-1510, Sep. 2000. [pdf]
  4. K.K. Paliwal and J. Chen, ``Robust feature extraction for speech recognition'', Proc. Seventh Western Pacific Regional Acoustics Conference (WESTPRAC VII), Kumamoto, Japan, pp. 61-66, Oct. 2000.
  5. J. Chen, K.K. Paliwal and S. Nakamura, ``A block cosine transform and its application in speech recognition'', Proc. Intern. Conf. Spoken Language Processing (INTERSPEECH 2000 - ICSLP), Beijing, China, Vol. IV, pp. 117-120, Oct. 2000. [pdf]
  6. K.K. Paliwal and V. Ramasubramanian, ``Modified K-means algorithm for vector quantizer design'', IEEE Trans. Image Processing, Vol. 9, No. 11, pp. 1964-1967, Nov. 2000. [pdf]
  7. C. Sanderson and K.K. Paliwal, ``Adaptive multi-modal person verification system'', Proc. First IEEE Pacific-Rim Conference on Multimedia (IEEEPCM-2000), Sydney, Australia, pp. 210-213, Dec. 2000.
  8. X. Wang and K.K. Paliwal, ``Using minimum classification error training in dimensionality reduction'', in Neural Networks for Signal Processing, B. Widrow, L. Guan, K. Paliwal, T. Adali, J. Larsen, E. Wilson and S. Douglas (Eds.), pp. 338-345, IEEE Press, New York, Dec. 2000 (Proc. IEEE Workshop on Neural Networks for Signal Processing, Sydney, Australia, pp. 338-345, Dec. 2000). [pdf]
  9. C. Sanderson and K.K. Paliwal, ``Adaptation method for a multi-modal person verification system'', Proc. Australian International Conference on Speech Science and Technology (SST-2000), Canberra, Australia, pp. 312-317, Dec. 2000.
  10. B. Wildermoth and K.K. Paliwal, ``Use of voicing and pitch information for speaker recognition'', Proc. Australian International Conference on Speech Science and Technology (SST-2000), Canberra, Australia, pp. 324-328, Dec. 2000. [pdf]
  11. J. Chen, K.K. Paliwal, T. Matsui, K. Yao, K.P. Markov and S. Nakamura, ``Long-term effect removal for noisy speech recognition'', Technical Report of the Institute of Electronics, Information and Communication Engineers (IEICE, Japan), SP2000-77, Vol. 100, No. 522, pp. 13-18, Dec. 2000.