{"ID":2895470,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.09350","arxiv_id":"2507.09350","title":"Microphone Occlusion Mitigation for Own-Voice Enhancement in Head-Worn Microphone Arrays Using Switching-Adaptive Beamforming","abstract":"Enhancing the user's own-voice for head-worn microphone arrays is an important task in noisy environments to allow for easier speech communication and user-device interaction. However, a rarely addressed challenge is the change of the microphones' transfer functions when one or more of the microphones gets occluded by skin, clothes or hair. The underlying problem for beamforming-based speech enhancement is the (potentially rapidly) changing transfer functions of both the own-voice and the noise component that have to be accounted for to achieve optimal performance. In this paper, we address the problem of an occluded microphone in a head-worn microphone array. We investigate three alternative mitigation approaches by means of (i) conventional adaptive beamforming, (ii) switching between a-priori estimates of the beamformer coefficients for the occluded and unoccluded state, and (iii) a hybrid approach using a switching-adaptive beamformer. In an evaluation with real-world recordings and simulated occlusion, we demonstrate the advantages of the different approaches in terms of noise reduction, own-voice distortion and robustness against voice activity detection errors.","short_abstract":"Enhancing the user's own-voice for head-worn microphone arrays is an important task in noisy environments to allow for easier speech communication and user-device interaction. However, a rarely addressed challenge is the change of the microphones' transfer functions when one or more of the microphones gets occluded by...","url_abs":"https://arxiv.org/abs/2507.09350","url_pdf":"https://arxiv.org/pdf/2507.09350v1","authors":"[\"Wiebke Middelberg\",\"Jung-Suk Lee\",\"Saeed Bagheri Sereshki\",\"Ali Aroudi\",\"Vladimir Tourbabin\",\"Daniel D. E. Wong\"]","published":"2025-07-12T17:00:18Z","proceeding":"eess.AS","tasks":"[\"eess.AS\"]","methods":"[]","has_code":false}