A low-power hardware search architecture for speech recognition

Patrick J. Bourke, Robin A Rutenbar

Research output: Contribution to journalConference article

Abstract

High-performance speech recognition is extremely computationally expensive, limiting its use in the mobile domain. We therefore propose a low-power hardware speech recognition architecture for mobile applications, exploiting the orders-of-magnitude efficiency improvements dedicated hardware can offer. Our system is based on the Sphinx 3.0 software recognizer developed at Carnegie Mellon University, capable of large-vocabulary, speaker-independent, continuous, real-time speech recognition. We show through cycle-accurate simulation that our hardware, targeting the backend search stage of recognition, is capable of recognizing speech from a 5,000 word vocabulary 1.3 times faster than real-time, within an approximately 200mW power budget.

Original languageEnglish (US)
Pages (from-to)2102-2105
Number of pages4
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
StatePublished - Dec 1 2008
EventINTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association - Brisbane, QLD, Australia
Duration: Sep 22 2008Sep 26 2008

Keywords

  • Circuit
  • Hardware
  • Low power
  • Search
  • Speech recognition

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Sensory Systems

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