|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Peer Review Status:||Refereed|
|Title:||A biologically inspired onset and offset speech segmentation approach|
|Citation:||Abel A, Hunter D & Smith L (2015) A biologically inspired onset and offset speech segmentation approach In: 2015 International Joint Conference on Neural Networks (IJCNN), Washington DC, USA: IEEE Computer Society. International Joint Conference on Neural Networks, 12.7.2015 - 17.7.2105, Killarney, Ireland.|
|Conference Name:||International Joint Conference on Neural Networks|
|Conference Location:||Killarney, Ireland|
|Abstract:||A key component in the processing of speech is the division of longer input sounds into a number of smaller sections. For speech interpretation it is generally easier to classify single sections. Similarly, when processing speech for other purposes (e.g. speech filtering), it can be easier and more relevant to process individual phonemes. Here, we propose a biologically inspired speech segmentation technique that filters the speech into multiple bandpassed channels using a Gammatone filterbank, and then uses an essentially energy-based spike coding technique in order to find the onsets and offsets present in an audio signal. These onsets and offsets are then processed using leaky integrate-and-fire neurons, and the spikes from these used to determine the speech segmentation. We evaluate this new system using a quantitative evaluation metric, and the promising results of segmentation of both clean speech and speech in noise demonstrate the effectiveness of this technique.|
|Rights:||© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.|
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