Language-based Audio Retrieval Task in DCASE 2022 Challenge
Language-based audio retrieval is a task, where natural language textual captions are used as queries to retrieve audio signals from a dataset. It has been first introduced into DCASE 2022 Challenge as Subtask 6B of task 6, which aims at developing computational systems to model relationships between audio signals and free-form textual descriptions. Compared with audio captioning (Subtask 6A), which is about generating audio captions for audio signals, language-based audio retrieval (Subtask 6B) focuses on ranking audio signals according to their relevance to natural language textual captions. In DCASE 2022 Challenge, the provided baseline system for Subtask 6B was significantly outperformed, with top performance being 0.276 in mAP@10. This paper presents the outcome of Subtask 6B in terms of submitted systems' performance and analysis.
Code (1)
Tasks
Audio captioningRetrievalSimilar Papers 제목 키워드 기반
Language-based Audio Retrieval Task in DCASE 2022 Challenge
Language-based audio retrieval is a task, where natural language textual captions are used as queries to retrieve audio signals from a dataset. It has been first introduced into DCASE 2022 Challenge as Subtask 6B of task…
Audio captioningRetrievalAISTAT lab system for DCASE2025 Task6: Language-based audio retrieval
This report presents the AISTAT team's submission to the language-based audio retrieval task in DCASE 2025 Task 6. Our proposed system employs dual encoder architecture, where audio and text modalities are encoded separa…
Contrastive LearningData AugmentationExpanding on EnCLAP with Auxiliary Retrieval Model for Automated Audio Captioning
In this technical report, we describe our submission to DCASE2024 Challenge Task6 (Automated Audio Captioning) and Task8 (Language-based Audio Retrieval). We develop our approach building upon the EnCLAP audio captioning…
Audio captioningRerankingRetrievalImproving Natural-Language-based Audio Retrieval with Transfer Learning and Audio & Text Augmentations
The absence of large labeled datasets remains a significant challenge in many application areas of deep learning. Researchers and practitioners typically resort to transfer learning and data augmentation to alleviate thi…
Data AugmentationNatural Language QueriesRetrievalTransfer LearningAutomated Audio Captioning and Language-Based Audio Retrieval
This project involved participation in the DCASE 2022 Competition (Task 6) which had two subtasks: (1) Automated Audio Captioning and (2) Language-Based Audio Retrieval. The first subtask involved the generation of a tex…
Audio captioningRetrieval