Advances in Microphone Array Processing and Multichannel Speech Enhancement

TL;DR

This paper provides a comprehensive review of microphone array processing and multichannel speech enhancement, covering historical developments, recent advancements including deep learning integration, and future research directions to improve speech quality in noisy environments.

Contribution

It offers an extensive overview of foundational and recent innovations, highlighting the integration of deep learning techniques like all-neural beamformers in speech enhancement.

Findings

Advancements in array design improved sound acquisition.

Deep learning techniques enhanced speech intelligibility.

Future challenges include real-time processing and robustness.

Abstract

This paper reviews pioneering works in microphone array processing and multichannel speech enhancement, highlighting historical achievements, technological evolution, commercialization aspects, and key challenges. It provides valuable insights into the progression and future direction of these areas. The paper examines foundational developments in microphone array design and optimization, showcasing innovations that improved sound acquisition and enhanced speech intelligibility in noisy and reverberant environments. It then introduces recent advancements and cutting-edge research in the field, particularly the integration of deep learning techniques such as all-neural beamformers. The paper also explores critical applications, discussing their evolution and current state-of-the-art technologies that significantly impact user experience. Finally, the paper outlines future research directions, identifying challenges and potential solutions that could drive further innovation in these fields. By providing a comprehensive overview and forward-looking perspective, this paper aims to inspire ongoing research and contribute to the sustained growth and development of microphone arrays and multichannel speech enhancement.