Ambisonics Encoding For Arbitrary Microphone Arrays Incorporating Residual Channels For Binaural Reproduction
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Abstract (arXiv)
In the rapidly evolving fields of virtual and augmented reality, accurate spatial audio capture and reproduction are essential. For these applications, Ambisonics has emerged as a standard format. However, existing methods for encoding Ambisonics signals from arbitrary microphone arrays face challenges, such as errors due to the irregular array configurations and limited spatial resolution resulting from a typically small number of microphones. To address these limitations and challenges, a mathematical framework for studying Ambisonics encoding is presented, highlighting the importance of incorporating the full steering function, and providing a novel measure for predicting the accuracy of encoding each Ambisonics channel from the steering functions alone. Furthermore, novel residual channels are formulated supplementing the Ambisonics channels. A simulation study for several array configurations demonstrates a reduction in binaural error for this approach.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Feb 2024.
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Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2026PhaseCoder: Microphone Geometry-Agnostic Spatial Audio Understanding for Multimodal LLMscited by 6
- 2025SoundSculpt: Direction and Semantics Driven Ambisonic Target Sound Extractioncited by 2
- 2026Generative Learning for Ambisonic Upscalingcited by 0
- 2026SEA-LM: Egocentric Spatial Audio Understanding for Wearable Microphone Arrayscited by 0
- 2026SEA-LM: Egocentric Spatial Audio Understanding for Wearable Microphone Arrays4 Oct 2026
- 2026Generative Learning for Ambisonic Upscaling20 Sep 2026
- 2026PhaseCoder: Microphone Geometry-Agnostic Spatial Audio Understanding for Multimodal LLMs28 Jan 2026
- 2025SoundSculpt: Direction and Semantics Driven Ambisonic Target Sound Extraction30 May 2025