- Authors:
-
Fleischhauer,
E.
,
Nagel,
S.
,
Balachanthiran,
A.
,
Jax,
P.
- Book Title:
- Proceedings of German Annual Conference on Acoustics (DAGA)
- Organization:
- DEGA
- Status:
- accepted for publication
- Date:
-
2024
- Language:
- English
Abstract
Binaural cue adaptation (BCA) is a signal processing technique for modifying the position of sound sources in a binaural audio signal. In combination with a head-tracking device, it can be used to compensate a listener’s head movements, thus enabling a more immersive reproduction of binaural recordings. Previous BCA algorithms were based on a signal model that assumed an input signal containing directional components and temporally uncorrelated ambient components. To modify only those components containing directional information, BCA algorithms decompose binaural recordings using a primary-ambient decomposition (PAD). However, this signal model is not well suited for reverberant environments. Therefore, this contribution extends the signal model to include temporally correlated reverberation components. Building upon this signal model, we propose a novel BCA algorithm that incorporates the weighted prediction error (WPE) dereverberation algorithm into the PAD. The results of a MUSHRA listening test show that the WPE-based BCA approach outperforms the PAD-based BCA in highly reverberant environments in terms of perceived quality.
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