Journal Publications

Journal Publications:

  1. Srikanth Raj Chetupalli, T. V. Sreenivas, "Joint Bayesian Estimation of Time-Varying LP Parameters and Excitation for Speech", accepted for publication in IEEE Signal Processing Letters, 2017.
  2. A. S. Murthy, C. S. Seelamantula, and T. V. Sreenivas, "Optimum short-time polynomial regression for signal analysis," accepted to Sadhana Journal of the Indian Academy of Sciences.
  3. Harshavardhan Sundar, TV Sreenivas, "Who spoke what? A Latent variable framework for the joint decoding of multiple speakers and their keywords", arXiv:1504.08021. [link]
    1. Neeraj K. Sharma, TV Sreenivas, "Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation", Elsevier Signal Processing, Vol 116, pp - 43-54, Nov. 2015. [link]
    2. Mrugesh Gajjar, TV Sreenivas, Govindarajan, R. “Fast Likelihood Computation in Speech Recognition using Matrices,” J. Sig. Proc. Syst. for Signal, Image, and Video Tech., Vol.70, No.2, pp 219-234, Feb. 2013.
    3. Harshavardhan Sundar, TV Sreenivas, W. Kellerman, “Identification of Active Sources in Single-Channel Convolutive Mixtures Using Known Source Models,” IEEE Signal Proc. Letters,, Mar 2013.
  4. Harshavardhan Sundar, C. S. Seelamantula, and T. V. Sreenivas, "A mixture model approach for formant tracking and the robustness of Student's-t distribution," IEEE Tr. Audio, Speech, Lang. Proc., Vol.20, No.10, pp 2626-2636, Dec 2012.
    1. Nishanth U. Nair and T.V. Sreenivas, “Multi-Pattern Viterbi Algorithm for Joint Decoding of Multiple Patterns,” accepted for Signal Processing (Els), Mar 2010. [link]
    2. Nishanth Ulhas Nair and TV Sreenivas: “Joint evaluation of multiple speech patterns for speech recognition and training,” Computer, Speech and Language, (Acad Press) May 2009. [link]
    3. Saikat Chatterjee and TV Sreenivas: “Reduced complexity two stage vector quantization,” Digital Signal Processing: A Review Journal, In Press, Dec 2008 [link]
    4. Chandra Sekhar, S. and TV Sreenivas: “Block-artifacts in speech/audio: Dynamic auditory-model-based characterization and optimal time-frequency smoothing,” Signal Processing (Elsevier), Vol. 89, No.4, pp 523-531, Apr 2009. [link]
    5. Suresh K and TV Sreenivas: “Linear Filtering in DCT-IV/DST-IV and MDCT/MDST Domains,” Signal Processing (Elsevier), In Press, Dec 2008. [link]
    6. Suresh K and TV Sreenivas, “Block Convolution using Discrete Trigonometric Transforms and Discrete Fourier Transform,” IEEE Signal Processing Letters, Vol. 15, pp 469-472, 2008. [link]
    7. Saikat Chatterjee and TV Sreenivas: “Optimum Switched Split Vector Quantization of LSF Parameters,” Signal Processing (Elsevier), Vol.88, Issue 6, pp 1528-1538, Jun 2008. [link]
    8. Saikat Chatterjee and TV Sreenivas: “Optimum transform domain split VQ,” IEEE Processing Letters, Vol.15, pp 285-288, 2008. [link]
    9. Saikat Chatterjee and TV Sreenivas: “Predicting VQ Performance Bound for LSF Coding,” IEEE Signal Processing Letters, Vol.15, pp 166-169, 2008. [link]
    10. Saikat Chatterjee and TV Sreenivas: “Switched Conditional PDF-Based Split VQ using Gaussian Mixture Model,” IEEE Signal Processing Letters, Vol.15, pp 91-94, 2008. [link]
    11. Saikat Chatterjee and TV Sreenivas: “Analysis of Conditional PDF Based Split VQ,” IEEE Signal Processing Letters, Volume 14, Issue 11, pp 781-784, Nov. 2007. [link]
    12. Saikat Chatterjee and TV Sreenivas: “Conditional pdf based split vector quantization of wide-band LSF parameters,” IEEE Signal Processing Letters, Vol.14, No.9, pp 641-44, Sep 2007. [link]
    13. Krishnakumar, S and TV Sreenivas: “On watermark-to-host correlation of uniform random phase watermarks in audio signals,” Signal Processing (Elsevier), No.1, Vol.87, pp 61-67, Jan 2007. [link]
    14. Prasanta K. Ghosh and TV Sreenivas: “Time-varying filter interpretation of Fourier transform and its variants,” Signal Processing (Elsevier), Vol.86, No.11, Nov 2006, pp 3258-3263. [link]
    15. S Chandra Sekhar and TV Sreenivas: “Signal-to-noise ratio estimation using higher-order moments,” Signal Processing (Elsevier), Vol.86, No.4, Apr 2006, pp 716-732. [link]
    16. S Chandra Sekhar and TV Sreenivas: ‘Adaptive window Zero-crossing based instantaneous frequency estimation,’ EURASIP J. Applied Signal Processing, No.12, Sept 2004. [link]
    17. S Chandra Sekhar and TV Sreenivas: ‘Adaptive spectrogram Vs adaptive pseudo Wigner-Ville distribution for instantaneous frequency estimation,’ Signal Processing Journal (Elsevier), Vol.83, pp1529-1543, July 2003. [link]
    18. S Chandra Sekhar and TV Sreenivas: ‘E?ect of interpolation on IF estimation using polynomial Wigner-Ville distribution’, Signal Processing Journal (Elsevier), Vol.84, No.1, pp107-116, Jan 2004. [link]
    19. S Chandra Sekhar and TV Sreenivas: ‘Auditory motivated level-crossing approach to Instantaneous frequency estimation,’ IEEE Tr. Signal Processing, Apr 2005. [link]
    20. B Mondal and TV Sreenivas, “Time-varying sinusoidal models for speech/audio,” J. Acoust. Soc. Am.,accepted for publication, March 2005.[link]
    21. JV Avadhanulu and TV Sreenivas, ‘Matched ?ltering approach to robust speech recognition,’ J. Ind. Inst.Science, Vol.79, No.3, May 1999. [link]
    22. G Viswanath and TV Sreenivas, ‘Instantaneous frequency estimation using higher order TFRs,’ Signal Processing (Elsevier), Vol.82, No.2, pp 127-132, Feb 2002. [link]
    23. G Viswanath and TV Sreenivas, ‘Cone-kernel representation Vs Instantaneous power spectrum,’ IEEE Trans. Signal Processing, Vol.47, No.1, pp 250-54, Jan 1999. [link]
    24. RNV Sitaram and TV Sreenivas, ‘Incorporating phonemic properties in HMMs for speech recognition,’ J. Acoust. Soc. Am., Vol. 102, No.2, pp 1149-1156, Aug 1997. [link]
    25. TV Sreenivas and P Kirnapure, ‘Codebook constrained iterative Wiener filtering for speech enhancement,’ IEEE Trans. Speech and Audio Processing, Vol.4, No.5, Sep 1996. [link]
    26. TV Sreenivas and RJ Niederjohn, ‘Zero-crossing based spectral analysis and ‘SVD’ spectral analysis for formant frequency estimation in noise,’ IEEE Trans. Acoust. Speech and Signal Processing, Vol.SP-40, No.2, Feb 1992. [link]
    27. TV Sreenivas, ‘On designing a microprogram translator,’ Signal Processing (Elsevier), Vol.13, No.1, pp 91-100, Jul 1987. [link]
    28. TV Sreenivas, ‘Simulation of a programmable signal processor,’ Signal Processing (Elsevier), Vol.6, No.2,pp 135-142, Apr 1984. [link]
    29. TV Sreenivas and PVS Rao, ‘Functional demarcation of pitch,’ Signal Processing (Elsevier), Vol.3, No.3, pp 277-284, Jul 1981. [link]
    30. TV Sreenivas and PVS Rao, ‘High resolution narrow band spectra by FFT pruning,’ IEEE Trans. Acoust.Speech and Signal Processing, Vol.ASSP-28, No.2, pp 254-257, Apr 1980. [link]
    31. TV Sreenivas and PVS Rao, ‘FFT algorithm for both input and output pruning,’ IEEE Trans. Acoust.Speech and Signal Processing, Vol.ASSP-27, No.3, pp 291-292, Jun 1979. [link]
    32. TV Sreenivas and PVS Rao, ‘Pitch extraction from corrupted harmonics of the power spectrum,’ J. Acoust.Soc. of America, Vol.65, No.1, pp 223-228, Jan 1979. [link]
    33. KK Paliwal, TV Sreenivas and PVS Rao, ‘A vowel recognition experiment using vocal tract area functions,’ J. Acoust. Soc. of India, Vol.6, No.4, pp 132-137, Oct 1978. [link]
    34. J. Acoust. Soc. of India, Vol.6, No.4, pp 132-137, Oct 1978.