Buchumschlag

LEAD Dataset: How Can Labels for Sound Event Detection Vary Depending on Annotators?

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Koga, Naoki, Bando, Yoshiaki, Imoto, Keisuke
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Sound Audio and Speech Processing
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Joint Analysis of Acoustic Scenes and Sound Events Based on Semi-Supervised Training of Sound Events With Partial Labels
von: Imoto, Keisuke
Veröffentlicht: (2025)

DOA-Aware Audio-Visual Self-Supervised Learning for Sound Event Localization and Detection
von: Fujita, Yoto, et al.
Veröffentlicht: (2024)

How Much Does Machine Identity Matter in Anomalous Sound Detection at Test Time?
von: Wilkinghoff, Kevin, et al.
Veröffentlicht: (2026)

Construction and Analysis of Impression Caption Dataset for Environmental Sounds
von: Okamoto, Yuki, et al.
Veröffentlicht: (2024)

Infrastructure-less Localization from Indoor Environmental Sounds Based on Spectral Decomposition and Spatial Likelihood Model
von: Ogiso, Satoki, et al.
Veröffentlicht: (2024)

Context-Aware Query Refinement for Target Sound Extraction: Handling Partially Matched Queries
von: Sato, Ryo, et al.
Veröffentlicht: (2025)

Handling Domain Shifts for Anomalous Sound Detection: A Review of DCASE-Related Work
von: Wilkinghoff, Kevin, et al.
Veröffentlicht: (2025)

Towards Understanding of Frequency Dependence on Sound Event Detection
von: Nam, Hyeonuk, et al.
Veröffentlicht: (2025)

Hierarchical Pooling Structure for Weakly Labeled Sound Event Detection
von: He, Ke-Xin, et al.
Veröffentlicht: (2019)

Trainingless Adaptation of Pretrained Models for Environmental Sound Classification
von: Tonami, Noriyuki, et al.
Veröffentlicht: (2024)

FMSG-JLESS Submission for DCASE 2024 Task4 on Sound Event Detection with Heterogeneous Training Dataset and Potentially Missing Labels
von: Xiao, Yang, et al.
Veröffentlicht: (2024)

Description and Discussion on DCASE 2026 Challenge Task 2: Noise-aware Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
von: Nishida, Tomoya, et al.
Veröffentlicht: (2026)

DCASE 2024 Task 4: Sound Event Detection with Heterogeneous Data and Missing Labels
von: Cornell, Samuele, et al.
Veröffentlicht: (2024)

Correlation of Fréchet Audio Distance With Human Perception of Environmental Audio Is Embedding Dependant
von: Tailleur, Modan, et al.
Veröffentlicht: (2024)

Learning How to Listen: A Temporal-Frequential Attention Model for Sound Event Detection
von: Shen, Yu-Han, et al.
Veröffentlicht: (2018)

WildDESED: An LLM-Powered Dataset for Wild Domestic Environment Sound Event Detection System
von: Xiao, Yang, et al.
Veröffentlicht: (2024)

Description and Discussion on DCASE 2025 Challenge Task 2: First-shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
von: Nishida, Tomoya, et al.
Veröffentlicht: (2025)

Frequency Dynamic Convolutions for Sound Event Detection
von: Nam, Hyeonuk
Veröffentlicht: (2025)

Discrete Tokens Exhibit Interlanguage Speech Intelligibility Benefit: an Analytical Study Towards Accent-robust ASR Only with Native Speech Data
von: Onda, Kentaro, et al.
Veröffentlicht: (2025)

Prosodically Enhanced Foreign Accent Simulation by Discrete Token-based Resynthesis Only with Native Speech Corpora
von: Onda, Kentaro, et al.
Veröffentlicht: (2025)

PSELDNets: Pre-trained Neural Networks on a Large-scale Synthetic Dataset for Sound Event Localization and Detection
von: Hu, Jinbo, et al.
Veröffentlicht: (2024)

Zero- and Few-shot Sound Event Localization and Detection
von: Shimada, Kazuki, et al.
Veröffentlicht: (2023)

Sound Event Detection with Boundary-Aware Optimization and Inference
von: Schmid, Florian, et al.
Veröffentlicht: (2026)

Noise-Robust Sound Event Detection and Counting via Language-Queried Sound Separation
von: Chen, Yuanjian, et al.
Veröffentlicht: (2025)

Effective Pre-Training of Audio Transformers for Sound Event Detection
von: Schmid, Florian, et al.
Veröffentlicht: (2024)

Ensemble Confidence Calibration for Sound Event Detection in Open-environment
von: Chen, Yuanjian, et al.
Veröffentlicht: (2025)

Enhance Temporal Relations in Audio Captioning with Sound Event Detection
von: Xie, Zeyu, et al.
Veröffentlicht: (2023)

Refining Knowledge Transfer on Audio-Image Temporal Agreement for Audio-Text Cross Retrieval
von: Tsubaki, Shunsuke, et al.
Veröffentlicht: (2024)

SONAR: Self-Distilled Continual Pre-training for Domain Adaptive Audio Representation
von: Zhang, Yizhou, et al.
Veröffentlicht: (2025)

JiTTER: Jigsaw Temporal Transformer for Event Reconstruction for Self-Supervised Sound Event Detection
von: Nam, Hyeonuk, et al.
Veröffentlicht: (2025)

Diversifying and Expanding Frequency-Adaptive Convolution Kernels for Sound Event Detection
von: Nam, Hyeonuk, et al.
Veröffentlicht: (2024)

UCIL: An Unsupervised Class Incremental Learning Approach for Sound Event Detection
von: Xiao, Yang, et al.
Veröffentlicht: (2024)

Exploring Text-Queried Sound Event Detection with Audio Source Separation
von: Yin, Han, et al.
Veröffentlicht: (2024)

Temporal Attention Pooling for Frequency Dynamic Convolution in Sound Event Detection
von: Nam, Hyeonuk, et al.
Veröffentlicht: (2025)

Enhancing Stereo Sound Event Detection with BiMamba and Pretrained PSELDnet
von: Gao, Wenmiao, et al.
Veröffentlicht: (2025)

The Sounds of Home: A Speech-Removed Residential Audio Dataset for Sound Event Detection
von: Bibbó, Gabriel, et al.
Veröffentlicht: (2024)

Self Training and Ensembling Frequency Dependent Networks with Coarse Prediction Pooling and Sound Event Bounding Boxes
von: Nam, Hyeonuk, et al.
Veröffentlicht: (2024)

Sound Event Bounding Boxes
von: Ebbers, Janek, et al.
Veröffentlicht: (2024)

Fine-Grained Engine Fault Sound Event Detection Using Multimodal Signals
von: Fedorishin, Dennis, et al.
Veröffentlicht: (2024)

Leveraging LLM and Text-Queried Separation for Noise-Robust Sound Event Detection
von: Yin, Han, et al.
Veröffentlicht: (2024)