Kalman filter based stereo system identification with auto- and cross-decorrelation

Kühl, Stefan; Antweiler, Christiane; Hubschen, Tobias; Jax, Peter

doi:10.1109/hscma.2017.7895586

Cited by 4 publications

(1 citation statement)

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“…Additionally, the time-variance index (TVI) is depicted in Fig. 3 as a measure of time-variance between consecutive HRIRs [39], i.e., TVI (k) = 10 log 10 h k,s − h k−1,s 2 / h k−1,s 2 . Near the socalled bright spot [35], the changes between adjacent HRIRs are minor, and the TVI falls steeply below −60 dB.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Towards Faster Continuous Multi-Channel HRTF Measurements Based on Learning System Models

Kabzinski,

Jax

2021

Preprint

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Measuring personal head-related transfer functions (HRTFs) is essential in binaural audio. Personal HRTFs are not only required for binaural rendering and for loudspeaker-based binaural reproduction using crosstalk cancellation, but they also serve as a basis for data-driven HRTF individualization techniques and psychoacoustic experiments. Although many attempts have been made to expedite HRTF measurements, the rotational velocities in today's measurement systems remain lower than those in natural head movements. To cope with faster rotations, we present a novel continuous HRTF measurement method. This method estimates the HRTFs offline using a Kalman smoother and learns state-space parameters, including the system model, on short signal segments, utilizing the expectation maximization algorithm. We evaluated our method in simulated single-channel and multi-channel measurements using a rigid sphere HRTF model. Comparing with conventional methods, we found that the system distances are improved by up to 30 dB.

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Section: Experiments and Resultsmentioning

confidence: 99%