13 papers
Bridging the Sim-to-Real Gap in Semiconductor Visual Program Synthesis via Input Binarization
Yusuke Ohtsubo, Kota Dohi, Koichiro Yawata +2
Precise parametric control over circuit geometry is essential for semiconductor inspection, yet obtaining sufficient real training data remains costly. Although generative models s…
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…
Synthetic Data Domain Adaptation for ASR via LLM-based Text and Phonetic Respelling Augmentation
Natsuo Yamashita, Koichi Nagatsuka, Hiroaki Kokubo +2
End-to-end automatic speech recognition often degrades on domain-specific data due to scarce in-domain resources. We propose a synthetic-data-based domain adaptation framework with…
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…