arXiv:2211.02289
공식 코드 · Papers with Code
CochlScene: Acquisition of acoustic scene data using crowdsourcing
원문 초록
This paper describes a pipeline for collecting acoustic scene data by using crowdsourcing. The detailed process of crowdsourcing is explained, including planning, validation criteria, and actual user interfaces. As a result of data collection, we present CochlScene, a novel dataset for acoustic scene classification. Our dataset consists of 76k samples collected from 831 participants in 13 acoustic scenes. We also propose a manual data split of training, validation, and test sets to increase the reliability of the evaluation results. Finally, we provide a baseline system for future research.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Low-Complexity Acoustic Scene Classification with Device Information in the DCASE 2025 Challenge
Low-Complexity Acoustic Scene Classification Using Parallel Attention-Convolution Network
Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge
Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift
AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning
Audio Event-Relational Graph Representation Learning for Acoustic Scene Classification
토론
이 논문과 연결된 포럼 글이 아직 없습니다.