Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: Spherical microphone arrays capture a three-dimensional sound field (P(?c, t)) for generating an Ambisonics representation (Anm(t)), where the pressure distribution on the surface of the sphere is sampled by the capsules of the array. The impact of the microphones on the captured sound field is removed using the inverse microphone transfer function. The equalisation of the transfer function of the microphone array is a big problem because the reciprocal of the transfer function causes high gains for small values in the transfer function and these small values are affected by transducer noise. The invention minimises that noise by using a Wiener filter processing in the frequency domain, which processing is automatically controlled per wave number by the signal-to-noise ratio of the microphone array.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.