A comparison of low-complexity real-time feature extraction for neuromorphic speech recognition
This paper presents a real-time, low-complexity neuromorphic speech recognition system using a spiking silicon cochlea, a feature extraction module and a population encoding method based Neural Engineering Framework (NEF)/Extreme Learning Machine (ELM) classifier IC. Several feature extraction metho...
| Main Authors: | , , , , , |
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| 其他作者: | |
| 格式: | Journal Article |
| 語言: | English |
| 出版: |
2018
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/85120 http://hdl.handle.net/10220/45134 |