• DocumentCode
    237553
  • Title

    Digital life assistant using automated speech recognition

  • Author

    Rawat, Seema ; Gupta, Puneet ; Kumar, Pranaw

  • Author_Institution
    Amity Univ., Noida, India
  • fYear
    2014
  • fDate
    28-29 Nov. 2014
  • Firstpage
    43
  • Lastpage
    47
  • Abstract
    Physical interaction in order to provide commands or gain access to a computer system is now a history. Voice or speech stimulated systems are a part of modern Smartphone culture. Automatic Speech Recognition is an important application of artificial intelligence. This paper provides a brief description of what automatic speech recognition is its various types and a overview of how the process works. After a precise review of Hidden Markov Model (HMM) & Mel Spectrum Cestrum Coefficient (MFCC), this paper discusses about the history of this technology, future aspects and scope. Applications of the technology in various fields are also discussed.
  • Keywords
    hidden Markov models; speech recognition; Mel spectrum cestrum coefficient; artificial intelligence; automated speech recognition; digital life assistant; hidden Markov model; physical interaction; smartphone culture; Acoustics; Automatic speech recognition; Computers; Feature extraction; Hidden Markov models; Speech; Digitized or Digital Life Assistant; Feature extraction; Hidden Markov Model (HMM); LPC; MFCC; PLP; Voice or Speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), 2014 Innovative Applications of
  • Conference_Location
    Ghaziabad
  • Type

    conf

  • DOI
    10.1109/CIPECH.2014.7019075
  • Filename
    7019075