K. Paliwal

Publications411
h-index56
Citations17,824
Highly Influential Citations1,484
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Bidirectional recurrent neural networks
TLDR
It is shown how the proposed bidirectional structure can be easily modified to allow efficient estimation of the conditional posterior probability of complete symbol sequences without making any explicit assumption about the shape of the distribution.
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Efficient vector quantization of LPC parameters at 24 bits/frame
TLDR
It is shown that the split vector quantizer can quantize LPC information in 24 bits/frame with an average spectral distortion of 1 dB and less than 2% of the frames having spectral distortion greater than 2 dB.
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Efficient vector quantization of LPC parameters at 24 bits/frame
  • K. Paliwal, B. Atal
  • Computer Science
    [Proceedings] ICASSP 91: International…
  • 1 May 1990
TLDR
It is shown that the split vector quantizer can quantize LPC information in 24 bits/frame with an average spectral distortion of 1 dB and less than 2% of the frames having spectral distortion greater than 2 dB.
View on IEEE
Speech Coding and Synthesis
TLDR
An introduction to speech coding, W.B. Kleijn evaluation of speech coders, and a robust algorithm for pitch tracking (RAPT), D. McAulay and T.F. Quatieri waveform interpolation for coding and synthesis.
Efficient vector quantization of LPC parameters at 24 bits/frame
TLDR
A split vector quantization approach is used to overcome the complexity problem of LPC vector and each part is vector‐quantized separately.
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Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning
TLDR
The accuracy of the iterative use of predicted secondary structure and backbone torsion angles and dihedrals based on Cα atoms is higher than those of model structures from current state-of-the-art techniques, suggesting the potentially beneficial use of these predicted properties for model assessment and ranking.
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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…
TLDR
The application of LSTM‐BRNN to the prediction of protein structural properties makes the most significant improvement for residues with the most long‐range contacts over a previous window‐based, deep‐learning method SPIDER2.
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Identity verification using speech and face information
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Fast features for face authentication under illumination direction changes
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A speech enhancement method based on Kalman filtering
  • K. Paliwal, A. Basu
  • Engineering
    ICASSP '87. IEEE International Conference on…
  • 6 April 1987
TLDR
A delayed-Kalman filtering method is proposed which improves the speech enhancement performance of Kalman filter further and is found to be significantly better than the Wiener filtering method.
View on IEEE
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