A spiking neural network for real-time Spanish vowel phonemes recognition
| Autor: | Gabriel Jimenez-Moreno, F. Gomez-Rodriguez, Angel Jimenez-Fernandez, L. Miro-Amarante |
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| Rok vydání: | 2017 |
| Předmět: |
Spiking neural network
0209 industrial biotechnology Artificial neural network Event (computing) Computer science Cognitive Neuroscience Speech recognition 02 engineering and technology Speech processing Computer Science Applications 020901 industrial engineering & automation Neuromorphic engineering Artificial Intelligence Vowel 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing |
| Zdroj: | Neurocomputing. 226:249-261 |
| ISSN: | 0925-2312 |
| DOI: | 10.1016/j.neucom.2016.12.005 |
| Popis: | This paper explores neuromorphic approach capabilities applied to real-time speech processing. A spiking recognition neural network composed of three types of neurons is proposed. These neurons are based on an integrative and fire model and are capable of recognizing auditory frequency patterns, such as vowel phonemes; words are recognized as sequences of vowel phonemes. For demonstrating real-time operation, a complete spiking recognition neural network has been described in VHDL for detecting certain Spanish words, and it has been tested in a FPGA platform. This is a stand-alone and fully hardware system that allows to embed it in a mobile system. To stimulate the network, a spiking digital-filter-based cochlea has been implemented in VHDL. In the implementation, an Address Event Representation (AER) is used for transmitting information between neurons. |
| Databáze: | OpenAIRE |
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