L3DAS22 Challenge: Learning 3D Audio Sources in a Real Office Environment
원문 초록
The L3DAS22 Challenge is aimed at encouraging the development of machine learning strategies for 3D speech enhancement and 3D sound localization and detection in office-like environments. This challenge improves and extends the tasks of the L3DAS21 edition. We generated a new dataset, which maintains the same general characteristics of L3DAS21 datasets, but with an extended number of data points and adding constrains that improve the baseline model's efficiency and overcome the major difficulties encountered by the participants of the previous challenge. We updated the baseline model of Task 1, using the architecture that ranked first in the previous challenge edition. We wrote a new supporting API, improving its clarity and ease-of-use. In the end, we present and discuss the results submitted by all participants. L3DAS22 Challenge website: www.l3das.com/icassp2022.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Overview of the L3DAS23 Challenge on Audio-Visual Extended Reality
Robust One-step Speech Enhancement via Consistency Distillation
MambAttention: Mamba with Multi-Head Attention for Generalizable Single-Channel Speech Enhancement
Efficient Speech Enhancement via Embeddings from Pre-trained Generative Audioencoders
Lessons Learned from the URGENT 2024 Speech Enhancement Challenge
FlowSE: Efficient and High-Quality Speech Enhancement via Flow Matching
토론
이 논문과 연결된 포럼 글이 아직 없습니다.