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dc.contributor.authorHARTE, NAOMI
dc.contributor.authorHINES, ANDREW
dc.date.accessioned2010-12-09T15:25:20Z
dc.date.available2010-12-09T15:25:20Z
dc.date.issued2010
dc.date.submitted2010en
dc.identifier.citationAndrew Hines and Naomi Harte, Evaluating Sensorineural Hearing Loss With An Auditory Nerve Model Using A Mean Structural Similarity Measure., European Signal Processing Conference (EUSIPCO '10)., Aalborg, Denmark, 2010en
dc.identifier.otherY
dc.identifier.urihttp://hdl.handle.net/2262/41261
dc.descriptionPUBLISHEDen
dc.description.abstractHearing loss research has traditionally been based on perceptual criteria, speech intelligibility and threshold levels. The development of computational models of the auditory-periphery has allowed experimentation via simulation to provide quantitative, repeatable results at a more granular level than would be practical with clinical research on human subjects. This work seeks to create an objective measure to automate this inspection process and ranks hearing losses based on auditory-nerve discharge patterns. A systematic way of assessing phonemic degradation using the outputs of an auditory nerve model for a range of sensorineural hearing losses would aid in rapid prototyping development of speech-processing algorithms for digital hearing aids. The effect of sensorineural hearing loss (SNHL) on phonemic structure was evaluated in this study using two types of neurograms: temporal fine structure (TFS) and average discharge rate or temporal envelope. The mean structural similarity index (MSSIM) is an objective measure originally developed to assess perceptual image quality. The measure is adapted here for use in measuring the phonemic degradation in neurograms derived from impaired auditory nerve outputs. A full evaluation of the choice of parameters for the metric is presented using a large amount of natural human speech. The metric?s boundedness and the results for TFS neurograms indicate it is a superior metric to standard point to point metrics of relative mean absolute error and relative mean squared error.en
dc.language.isoenen
dc.rightsYen
dc.subjectBiomaterialsen
dc.subjectHearing lossen
dc.titleEvaluating Sensorineural Hearing Loss With An Auditory Nerve Model Using A Mean Structural Similarity Measure.en
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/nharte
dc.identifier.rssinternalid68676


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