Robust DOA estimation using deep acoustic imaging
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910299359019008 |
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| author | Roman, Adrian S. Roman, Iran R. Bello, Juan P. |
| author_facet | Roman, Adrian S. Roman, Iran R. Bello, Juan P. |
| contents | Direction of arrival estimation (DoAE) aims at tracking a sound in azimuth and elevation. Recent advancements include data-driven models with inputs derived from ambisonics intensity vectors or correlations between channels in a microphone array. A spherical intensity map (SIM), or acoustic image, is an alternative input representation that remains underexplored. SIMs benefit from high-resolution microphone arrays, yet most DoAE datasets use low-resolution ones. Therefore, we first propose a super-resolution method to upsample low-resolution microphones. Next, we benchmark DoAE models that use SIMs as input. We arrive to a model that uses SIMs for DoAE estimation and outperforms a baseline and a state-of-the-art model. Our study highlights the relevance of acoustic imaging for DoAE tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_08717 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Robust DOA estimation using deep acoustic imaging Roman, Adrian S. Roman, Iran R. Bello, Juan P. Sound Audio and Speech Processing Direction of arrival estimation (DoAE) aims at tracking a sound in azimuth and elevation. Recent advancements include data-driven models with inputs derived from ambisonics intensity vectors or correlations between channels in a microphone array. A spherical intensity map (SIM), or acoustic image, is an alternative input representation that remains underexplored. SIMs benefit from high-resolution microphone arrays, yet most DoAE datasets use low-resolution ones. Therefore, we first propose a super-resolution method to upsample low-resolution microphones. Next, we benchmark DoAE models that use SIMs as input. We arrive to a model that uses SIMs for DoAE estimation and outperforms a baseline and a state-of-the-art model. Our study highlights the relevance of acoustic imaging for DoAE tasks. |
| title | Robust DOA estimation using deep acoustic imaging |
| topic | Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2401.08717 |