A reconstruction-based rendering approach is explored for the task of imposing the spatial characteristics of a measured space onto a monophonic signal while also reproducing it over a target playback setup. The foundation of this study is a parametric rendering framework, which can operate either on arbitrary microphone array room impulse responses (RIRs) or Ambisonic RIRs. Spatial filtering techniques are used to decompose the input RIR into individual reflections and anisotropic diffuse reverberation, which are reproduced using dedicated rendering strategies. The proposed approach operates by considering several hypotheses involving different rendering configurations and thereafter determining which hypothesis reconstructs the input RIR most faithfully.With regard to the present study, these hypotheses involved considering different potential reflection numbers. Once the optimal number of reflections to render has been determined over time and frequency, the array directional responses used to reconstruct the input RIR are substituted with spatialization gains for the target playback setup. The results of formal listening experiments suggest that the proposed approach produces renderings that are perceptually more similar to reference responses, when compared with the use of an established subspace-based detection algorithm. The proposed approach also demonstrates similar or better performance than that achieved with existing state-of-the-art methods.
McCormack, Leo; Meyer-Kahlen, Nils; Politis, Archontis
Affiliations: Department of Information and Communications Engineering, Aalto University, Espoo, Finland; Department of Information and Communications Engineering, Aalto University, Espoo, Finland; Faculty of Information Technology and Communication Sciences, Tampere University, Finland(See document for exact affiliation information.)
JAES Volume 71 Issue 5 pp. 267-280; May 2023
Publication Date: May 9, 2023
Download Now (670 KB)
This paper is Open Access which means you can download it for free.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.