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A Clustering Method for Sound Localization Transfer Functions
A new algorithm is proposed which prepares a set of sound localization transfer functions (SLTFs) for a sound localization system with binaural earphones. A listener in a teleconference system can choose the best SLTFs from the set prepared in advance. This avoids the trouble of measuring SLTFs individually and maintains good perceptual localization performance. This algorithm reduces the vector order of the individual SLTFs, for example, from 512 to 16, using cepstrum parameters. The SLTF vectors are classified ito several clusters using the Linde, Buzo, and Gray method, and the SLTF nearest each cluster's centroid is chosen as the typical SLTF in the cluster. The subjective performance of sound localization is shown in which the proposed algorithm selects typical SLTFs from among 94 measured SLTFs.
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