6 papers
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…
LaSTR: Language-Driven Time-Series Segment Retrieval
Kota Dohi, Harsh Purohit, Tomoya Nishida +6
Effectively searching time-series data is essential for system analysis, but existing methods often require expert-designed similarity criteria or rely on global, series-level desc…
Retaining Mixture Representations for Domain Generalized Anomalous Sound Detection
Phurich Saengthong, Tomoya Nishida, Kota Dohi +2
Anomalous sound detection (ASD) in the wild requires robustness to distribution shifts such as unseen low-SNR input mixtures of machine and noise types. State-of-the-art systems ex…
Can VLM Pseudo-Labels Train a Time-Series QA Model That Outperforms the VLM?
Takuya Fujimura, Kota Dohi, Natsuo Yamashita +1
Time-series question answering (TSQA) tasks face significant challenges due to the lack of labeled data. Alternatively, with recent advancements in large-scale models, vision-langu…
Model-free Speculative Decoding for Transformer-based ASR with Token Map Drafting
Tuan Vu Ho, Hiroaki Kokubo, Masaaki Yamamoto +1
End-to-end automatic speech recognition (ASR) systems based on transformer architectures, such as Whisper, offer high transcription accuracy and robustness. However, their autoregr…
LLM-based Generative Error Correction for Rare Words with Synthetic Data and Phonetic Context
Natsuo Yamashita, Masaaki Yamamoto, Hiroaki Kokubo +1
Generative error correction (GER) with large language models (LLMs) has emerged as an effective post-processing approach to improve automatic speech recognition (ASR) performance.…