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Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Authors: Abel, Andrew
Hunter, Dean
Smith, Leslie
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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 2015 International Joint Conference on Neural Networks (IJCNN), International Joint Conference on Neural Networks, Killarney, Ireland, 12.7.2015 - 17.7.2105, Washington DC, USA: IEEE Computer Society.
Issue Date: Sep-2015
Conference Name: International Joint Conference on Neural Networks
Conference Dates: 2015-07-12T00:00:00Z
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.
Type: Conference Paper
Status: Author Version
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.
Affiliation: Computing Science - CSM Dept
University of Stirling
Computing Science - CSM Dept

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