TY - GEN
T1 - Advances in Microphone Array Processing and Multichannel Speech Enhancement
AU - Huang, Gongping
AU - Jensen, Jesper R.
AU - Chen, Jingdong
AU - Benesty, Jacob
AU - Christensen, Mads G.
AU - Sugiyama, Akihiko
AU - Elko, Gary
AU - Gaensler, Tomas
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - beamforming
KW - Microphone arrays
KW - multichannel speech enhancement
UR - http://www.scopus.com/inward/record.url?scp=105003864320&partnerID=8YFLogxK
U2 - 10.1109/ICASSP49660.2025.10888510
DO - 10.1109/ICASSP49660.2025.10888510
M3 - 会议稿件
AN - SCOPUS:105003864320
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
BT - 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025 - Proceedings
A2 - Rao, Bhaskar D
A2 - Trancoso, Isabel
A2 - Sharma, Gaurav
A2 - Mehta, Neelesh B.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025
Y2 - 6 April 2025 through 11 April 2025
ER -