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 language | English (US) |
|---|---|
| Pages (from-to) | 2102-2105 |
| Number of pages | 4 |
| Journal | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
| State | Published - 2008 |
| Externally published | Yes |
| Event | INTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association - Brisbane, QLD, Australia Duration: Sep 22 2008 → Sep 26 2008 |
Keywords
- Circuit
- Hardware
- Low power
- Search
- Speech recognition
ASJC Scopus subject areas
- Human-Computer Interaction
- Signal Processing
- Software
- Sensory Systems