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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Price, M. Glass, J. Chandrakasan, A.P. |
| Copyright Year | 2014 |
| Description | Author affiliation: Massachusetts Inst. of Technol., Cambridge, MA, USA (Price, M.; Glass, J.; Chandrakasan, A.P.) |
| Abstract | Hardware-accelerated speech recognition is needed to supplement today's cloud-based systems in power- and bandwidth-constrained scenarios such as wearable electronics. With efficient hardware speech decoders, client devices can seamlessly transition between cloud-based and local tasks depending on the availability of power and networking. Most previous efforts in hardware speech decoding [1-2] focused primarily on faster decoding rather than low-power devices operating at real-time speed. More recently, [3] demonstrated real-time decoding using 54mW and 82MB/s memory bandwidth, though their architectural optimizations are not easily generalized to the weighted finite-state transducer (WFST) models used by state-of-the-art software decoders. This paper presents a 6mW speech recognition ASIC that uses WFST search networks and performs end-to-end decoding from audio input to text output. |
| Starting Page | 454 |
| Ending Page | 455 |
| File Size | 4579040 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781479909186 |
| ISSN | 01936530 |
| e-ISBN | 9781479909209 |
| DOI | 10.1109/ISSCC.2014.6757510 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-02-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Decoding Speech recognition Speech Hidden Markov models Bandwidth Real-time systems Acoustics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering |
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