| Paper: | ITT-P1.5 | ||
| Session: | Speech and Language Applications | ||
| Time: | Thursday, May 20, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Industry Technology Track: Speech Recognition | ||
| Title: | CUSTOM ARITHMETIC FOR HIGH-SPEED, LOW-RESOURCE ASR SYSTEMS | ||
| Authors: | Jonathan Malkin; University of Washington | ||
| Xiao Li; University of Washington | |||
| Jeff Bilmes; University of Washington | |||
| Abstract: | With the skyrocketing popularity of mobile devices, new processing methods tailored for low-resource systems have become necessary. One useful technique is the use of custom arithmetic, arithmetic logic tailored to a specific application. In a system with all parameters quantized to low precision, such arithmetic can be implemented through a set of small, fast table lookups. We present here a framework for the design of such a system architecture, and several heuristic algorithms to optimize system performance. In addition, we apply our techniques to an automatic speech recognition (ASR) application. Our simulations on various architectures show that on most modern processor designs, we can expect a cycle-count speedup of at least 3 times while requiring a total of only 59kB of ROMs to hold the lookup tables. | ||
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