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eess.AS2026

Description and Discussion on DCASE 2026 Challenge Task 2: Noise-aware Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

Tomoya Nishida, Noboru Harada, Daiki Takeuchi +6

This paper presents an overview of DCASE 2026 Challenge Task 2, titled "Noise-aware unsupervised anomalous sound detection (UASD) for machine condition monitoring." The task aims t…

eess.AS2026

Description and Discussion on DCASE 2026 Challenge Task 4: Spatial Semantic Segmentation of Sound Scenes

Binh Thien Nguyen, Masahiro Yasuda, Noboru Harada +8

This paper presents an overview of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2026 Challenge Task 4, Spatial Semantic Segmentation of Sound Scenes (S5).…

eess.AS2026

Rethinking Masking Strategies for Masked Prediction-based Audio Self-supervised Learning

Daisuke Niizumi, Daiki Takeuchi, Masahiro Yasuda +3

Since the introduction of Masked Autoencoders, various improvements to masking techniques have been explored. In this paper, we rethink masking strategies for audio representation…

eess.AS2026

Class-Aware Permutation-Invariant Signal-to-Distortion Ratio for Semantic Segmentation of Sound Scene with Same-Class Sources

Binh Thien Nguyen, Masahiro Yasuda, Daiki Takeuchi +2

To advance immersive communication, the Detection and Classification of Acoustic Scenes and Events (DCASE) 2025 Challenge recently introduced Task 4 on Spatial Semantic Segmentatio…

eess.AS2025

M2D-CLAP: Exploring General-purpose Audio-Language Representations Beyond CLAP

Daisuke Niizumi, Daiki Takeuchi, Masahiro Yasuda +3

Contrastive language-audio pre-training (CLAP), which learns audio-language representations by aligning audio and text in a common feature space, has become popular for solving aud…

eess.AS2025

Baseline Systems and Evaluation Metrics for Spatial Semantic Segmentation of Sound Scenes

Binh Thien Nguyen, Masahiro Yasuda, Daiki Takeuchi +3

Immersive communication has made significant advancements, especially with the release of the codec for Immersive Voice and Audio Services. Aiming at its further realization, the D…