A Framework of Directional-Gain Beamforming and a White-Noise-Gain-Controlled Solution

Chao Pan, Jingdong Chen

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

It is well known that an adaptive beamformer can be decomposed as a fixed beamformer followed by a post filter. This decomposition gives a much flexible way to design robust adaptive beamformers with high array gain and consequently it has become a popular approach to speech enhancement. In such a framework, the most critical problem is to estimate the post filter, which is studied in this paper. We present a multistage approach to the design of the post filter, which consists of a primary beamformer, a secondary beamformer and several auxiliary beamformers. Since the designed post filter is a function of source incidence angle by nature, we call it a directional gain. To evaluate the directivity of the beamformers in computing the directional gain, we introduce a modified beampattern, which is a function of both the source incidence angle and the point-source-to-background-noise ratio (PBR). To validate the presented approach, we analyze the principles of the primary, secondary and auxiliary beamformers, and then present a way to design these beamformers under the constraint of minimum white-noise-gain (WNG). Finally, we evaluate the performance of the directional gain and compare it with the traditional beamformers. The results show that the proposed directional gain can help achieve higher directivity factors (DFs), and better point-source-noise attenuation.

Original languageEnglish
Pages (from-to)2875-2887
Number of pages13
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Volume30
DOIs
StatePublished - 2022

Keywords

  • Directional gain
  • post filter
  • superdirective beamformer

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