• DocumentCode
    1778265
  • Title

    Hierarchical automatic speech recognition powered by data infrastructure

  • Author

    Jagatheesan, Arun ; Ahnn, Jong-Hoon ; Phan, Thomas ; Singh, Abhishek ; Lee, Juhan

  • Author_Institution
    Samsung Research America - Silicon Valley, San Jose, CA 95134, USA
  • fYear
    2014
  • fDate
    10-13 Jan. 2014
  • Firstpage
    1140
  • Lastpage
    1141
  • Abstract
    Automatic Speech Recognition (ASR) has evolved remarkably over the years and is expected to become a primary form of input to mobile devices including smartphones and wearables. Most large-scale mobile platforms perform speech recognition in the cloud today. There are both advantages and disadvantages to this Cloud-based ASR (Cloud-ASR) approach. Cloud-ASR approach allows for a context oriented humancomputer- interaction using speech rather than a mere speech-totext translation. A Cloud-ASR also has disadvantages such as interruption of the speech service when there is no access to the Cloud-ASR, and also the energy consumption for radio communications, which can drain a mobile battery sooner. We propose the usage of Hierarchical Speech Recognizer (HSR) as an alternative approach to overcome the shortcomings of the Cloud-ASR approach. In the HSR approach, mobile devices perform "selective speech recognition" by themselves as much as possible without contacting an external cloud-based ASR service. In this demonstration, we show our proof-of-concept HSR along with its feasibility and advantages.
  • Keywords
    Acoustics; Batteries; Computational modeling; Smart phones; Speech; Speech recognition; Automatic Speech Recognition; Consumer Electronics; Data infrastructure; S-Voice; Smart Phone;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Communications and Networking Conference (CCNC), 2014 IEEE 11th
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-1-4799-2356-4
  • Type

    conf

  • DOI
    10.1109/CCNC.2014.6994435
  • Filename
    6994435