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Computational Bioacoustics: Biodiversity Monitoring and Assessment de Todor Ganchev

Computational Bioacoustics: Biodiversity Monitoring and Assessment: Speech Technology and Text Mining in Medicine and Healthcare

Autor Todor Ganchev
en Limba Engleză Electronic book text – 7 mai 2017
  • Latest advances in signal processing and machine learning methods for speech and audio processing.
  • Coverage of various methods and techniques for measuring and calibrating auditory communication.
  • Includes technology, methods and good practices in computational bioacoustics.
The book covers the fundamentals and applications of computational bioacoustics in monitoring and control applications.  The work provides a thorough discussion of cross-disciplinary research, including new engineering technology with a discussion of codes and demos illustrating the application of various audio parameterization and machine learning techniques on the task of automated recognition and monitoring.  The concepts can be used in monitoring of healthcare patients, but can also be used in broader biodiversity monitoring and assessment.
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Specificații

ISBN-13: 9781614519669
ISBN-10: 1614519668
Pagini: 233
Ilustrații: 100 schw.-w. u. 20 farb. Abb., 20 schw.-w. Tab.
Editura: De Gruyter
Colecția De Gruyter
Seria Speech Technology and Text Mining in Medicine and Healthcare

Locul publicării:Berlin/Boston

Notă biografică

Todor Ganchev, Technical University,Varna, Bulgaria

Descriere

  • Latest advances in signal processing and machine learning methods for speech and audio processing.
  • Coverage of various methods and techniques for measuring and calibrating auditory communication.
  • Includes technology, methods and good practices in computational bioacoustics.
The book covers the fundamentals and applications of computational bioacoustics in monitoring and control applications.  The work provides a thorough discussion of cross-disciplinary research, including new engineering technology with a discussion of codes and demos illustrating the application of various audio parameterization and machine learning techniques on the task of automated recognition and monitoring.  The concepts can be used in monitoring of healthcare patients, but can also be used in broader biodiversity monitoring and assessment.

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