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Deep Audio Zooming: Beamwidth-Controllable Neural Beamformer

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arxiv 2311.13075 v1 pith:7HKOR4GL submitted 2023-11-22 eess.AS

classification eess.AS
keywords fielddirectionalfeaturesoundangularaudiobeamformingcapture
verification ladder T0 review T1 audit T2 compute T3 formal
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Audio zooming, a signal processing technique, enables selective focusing and enhancement of sound signals from a specified region, attenuating others. While traditional beamforming and neural beamforming techniques, centered on creating a directional array, necessitate the designation of a singular target direction, they often overlook the concept of a field of view (FOV), that defines an angular area. In this paper, we proposed a simple yet effective FOV feature, amalgamating all directional attributes within the user-defined field. In conjunction, we've introduced a counter FOV feature capturing directional aspects outside the desired field. Such advancements ensure refined sound capture, particularly emphasizing the FOV's boundaries, and guarantee the enhanced capture of all desired sound sources inside the user-defined field. The results from the experiment demonstrate the efficacy of the introduced angular FOV feature and its seamless incorporation into a low-power subband model suited for real-time applica?tions.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Neural Directional Filtering with Configurable Directivity Pattern at Inference

    eess.AS 2025-10 conditional novelty 6.0 of 10

    A user-defined directivity pattern can be fed to a FiLM-conditioned neural spatial filter at run time, and the system approximates unseen, higher-order, scaled, and steered patterns without retraining.

  2. Region-Specific Audio Tagging for Spatial Sound

    eess.AS 2025-09 conditional novelty 6.0 of 10

    Region-specific audio tagging: a model trained to tag sound events within a specified angular or distance region, tested on a new simulated benchmark and STARSS23.

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