Academic Journal
A Beam Shape Definable and Low Computing Cost Adaptive Audio Beamformer.
| Τίτλος: | A Beam Shape Definable and Low Computing Cost Adaptive Audio Beamformer. |
|---|---|
| Συγγραφείς: | Wang, Weiqin1 (AUTHOR) wangweiqin@xiaomi.com, Zhang, Jinhui1 (AUTHOR) zhangjinhui1@xiaomi.com |
| Πηγή: | International Journal of Pattern Recognition & Artificial Intelligence. Feb2026, Vol. 40 Issue 2, p1-18. 18p. |
| Θεματικοί όροι: | *Real-time computing, *Cross correlation, Microphone arrays, Adaptive signal processing, Signal-to-noise ratio, Interference (Sound), Acoustic localization, Signal separation |
| Περίληψη: | Audio beamformer utilizes a microphone array to pick up sounds from a designated direction while suppressing sounds from other directions as much as possible. It has a wide range of applications in areas such as anti-interference recording, zone recording, private calls, and audio zooming. The adaptive beamformer can automatically adjust its coefficients according to the spatial distribution of the signal, thus having much better performance than the fixed beamformer. This paper proposes a beam shape definable and low computing cost adaptive audio beamformer, which first uses the generalized cross-correlation (GCC) method to calculate the spatial spectrum distribution of the audio, and then uses this spatial spectrum distribution information to guide the generalized eigenvalue decomposition (GEVD) based method to perform beamforming with maximum signal-to-distortion ratio (SDR). In addition to definable beam shape and low computing cost, the proposed method also has the characteristics of fast convergence (good real-time performance), insensitivity to array shape, and no nonlinear distortion. This paper experimentally verified the algorithm's ability to perform directional speech pickup and speech separation. In the simulation test, the proposed method can improve the SDR of the speech signal in the target direction by 11.33 dB, and in the real-device test, it achieves the same level of results. It also performs well in noisy and reverberant conditions. We have provided samples of processing results for the readers' listening experience. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Pattern Recognition & Artificial Intelligence is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Items | – Name: Title Label: Title Group: Ti Data: A Beam Shape Definable and Low Computing Cost Adaptive Audio Beamformer. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Weiqin%22">Wang, Weiqin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wangweiqin@xiaomi.com</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Jinhui%22">Zhang, Jinhui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zhangjinhui1@xiaomi.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Pattern+Recognition+%26+Artificial+Intelligence%22">International Journal of Pattern Recognition & Artificial Intelligence</searchLink>. Feb2026, Vol. 40 Issue 2, p1-18. 18p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Real-time+computing%22">Real-time computing</searchLink><br />*<searchLink fieldCode="DE" term="%22Cross+correlation%22">Cross correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Microphone+arrays%22">Microphone arrays</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+signal+processing%22">Adaptive signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Signal-to-noise+ratio%22">Signal-to-noise ratio</searchLink><br /><searchLink fieldCode="DE" term="%22Interference+%28Sound%29%22">Interference (Sound)</searchLink><br /><searchLink fieldCode="DE" term="%22Acoustic+localization%22">Acoustic localization</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+separation%22">Signal separation</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Audio beamformer utilizes a microphone array to pick up sounds from a designated direction while suppressing sounds from other directions as much as possible. It has a wide range of applications in areas such as anti-interference recording, zone recording, private calls, and audio zooming. The adaptive beamformer can automatically adjust its coefficients according to the spatial distribution of the signal, thus having much better performance than the fixed beamformer. This paper proposes a beam shape definable and low computing cost adaptive audio beamformer, which first uses the generalized cross-correlation (GCC) method to calculate the spatial spectrum distribution of the audio, and then uses this spatial spectrum distribution information to guide the generalized eigenvalue decomposition (GEVD) based method to perform beamforming with maximum signal-to-distortion ratio (SDR). In addition to definable beam shape and low computing cost, the proposed method also has the characteristics of fast convergence (good real-time performance), insensitivity to array shape, and no nonlinear distortion. This paper experimentally verified the algorithm's ability to perform directional speech pickup and speech separation. In the simulation test, the proposed method can improve the SDR of the speech signal in the target direction by 11.33 dB, and in the real-device test, it achieves the same level of results. It also performs well in noisy and reverberant conditions. We have provided samples of processing results for the readers' listening experience. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Pattern Recognition & Artificial Intelligence is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1142/S0218001425510206 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 1 Subjects: – SubjectFull: Real-time computing Type: general – SubjectFull: Cross correlation Type: general – SubjectFull: Microphone arrays Type: general – SubjectFull: Adaptive signal processing Type: general – SubjectFull: Signal-to-noise ratio Type: general – SubjectFull: Interference (Sound) Type: general – SubjectFull: Acoustic localization Type: general – SubjectFull: Signal separation Type: general Titles: – TitleFull: A Beam Shape Definable and Low Computing Cost Adaptive Audio Beamformer. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Weiqin – PersonEntity: Name: NameFull: Zhang, Jinhui IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 02180014 Numbering: – Type: volume Value: 40 – Type: issue Value: 2 Titles: – TitleFull: International Journal of Pattern Recognition & Artificial Intelligence Type: main |
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