Dr. Vishala Pannala

About

Currently working as Assistant Professor at Koneru Lakshmaiah Education Foundation (KLEF), Hyderabad, Telangana. Prior to this, obtained PhD in ECE from IIIT Hyderabad.

Employment

• Koneru Lakshmaiah Education Foundation Assistant Professor
  2022 - Present

Education

• International Institute of Information Technology Hyderabad Doctor of Philosophy (PhD)
  2015 - 2021
• Jawaharlal Nehru Technological University Hyderabad Bachelor of Technology (B.Tech)
  2004 - 2008

Projects & Funding

Projects & funding information is unavailable.

Publications (10)

• Processing group delay spectrograms for study of formant and harmonic contours in speech signals
  The Journal of the Acoustical Society of America 2024 DOI: 10.1121/10.0032364
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• Study of dynamic characteristics of air cavity resonances from tyre-pavement interaction noise using single frequency filtering
  The Journal of the Acoustical Society of America 2023 DOI: 10.1121/10.0019496
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• Time-Frequency analysis of acoustic signals from tyre-pavement interaction
  The Journal of the Acoustical Society of America 2022 DOI: 10.1121/10.0009269
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• Application of single frequency filtering for speech and speaker specific tasks
  2021
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• Robustness and Accuracy of Time Delay Estimation in a Live Room
  2021 National Conference on Communications (NCC) 2021 DOI: 10.1109/ncc52529.2021.9530120
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• A neural network approach for speech activity detection for Apollo corpus
  Computer Speech & Language 2021 DOI: 10.1016/J.CSL.2020.101137
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• Enhancing formant information in spectrographic display of speech
  Proc. Interspeech 2020 2020 DOI: 10.21437/Interspeech.2020-2653
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• Processing of speech signals for robust recognition in practical environments
  CSI Transactions on ICT 2017 DOI: 10.1007/s40012-016-0153-5
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• Robust Estimation of Fundamental Frequency using Single Frequency Filtering Approach
  Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2016 DOI: 10.21437/INTERSPEECH.2016-1401
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• Voice Activity Detection using Temporal Characteristics of Autocorrelation Lag and Maximum Spectral Amplitude in Sub-bands
  Proceedings of the 11th International Conference on Natural Language Processing 2014
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