| Paper: | SP-P8.6 | ||
| Session: | Voice Activity Detection and Speech Segmentation | ||
| Time: | Wednesday, May 19, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Speech Processing: Speech Analysis | ||
| Title: | SOUND FEATURE DETECTION USING LEAKY INTEGRATE-AND-FIRE NEURONS | ||
| Authors: | Leslie Smith; University of Stirling | ||
| Dagmar Fraser; University of Stirling | |||
| Abstract: | We present a neurally inspired technique for detecting onsets in sound. The outputs from a cochlea-like filter are spike coded, in a way similar to the auditory nerve. These AN-like spikes are presented to leaky integrate-and-fire (LIF) neurons through a depressing synapse. The spike outputs from these are then processed by another layer of LIF neurons. Onsets are detected with essentially zero latency. We present results from the TIMIT database. | ||
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