Rabu, 10 Desember 2014

~ Ebook Download Robust Emotion Recognition using Spectral and Prosodic Features (SpringerBriefs in Electrical and Computer Engineering), by K. Sreenivasa

Ebook Download Robust Emotion Recognition using Spectral and Prosodic Features (SpringerBriefs in Electrical and Computer Engineering), by K. Sreenivasa

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Robust Emotion Recognition using Spectral and Prosodic Features (SpringerBriefs in Electrical and Computer Engineering), by K. Sreenivasa

Robust Emotion Recognition using Spectral and Prosodic Features (SpringerBriefs in Electrical and Computer Engineering), by K. Sreenivasa



Robust Emotion Recognition using Spectral and Prosodic Features (SpringerBriefs in Electrical and Computer Engineering), by K. Sreenivasa

Ebook Download Robust Emotion Recognition using Spectral and Prosodic Features (SpringerBriefs in Electrical and Computer Engineering), by K. Sreenivasa

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Robust Emotion Recognition using Spectral and Prosodic Features (SpringerBriefs in Electrical and Computer Engineering), by K. Sreenivasa

In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner.
The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.

  • Sales Rank: #3082149 in eBooks
  • Published on: 2013-01-13
  • Released on: 2013-01-13
  • Format: Kindle eBook

From the Back Cover

In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner.

The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.

About the Author

K. Sreenivasa Rao is at Indian Institute of Technology, Kharagpur, India.
Shashidhar G, Koolagudi is at Graphic Era University, Dehradun, India.

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