On the preprocessing and postprocessing of HRTF individualization based on sparse representation of anthropometric features
Individualization of head-related transfer functions (HRTFs) can be realized using the person's anthropometry with a pretrained model. This model usually establishes a direct linear or non-linear mapping from anthropometry to HRTFs in the training database. Due to the complex relation between a...
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Main Authors: | , , |
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格式: | Conference or Workshop Item |
語言: | English |
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2016
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在線閱讀: | https://hdl.handle.net/10356/82913 http://hdl.handle.net/10220/40370 |
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