5 papers
MemNMF: Memory-Augmented NMF on LPC Spectra for Anomalous Sound Detection
Phurich Saengthong, Takahiro Shinozaki
Autoencoder-based anomalous sound detection is attractive for machine condition monitoring because it can be trained using only normal recordings and yields an interpretable anomal…
Sub-Band Spectral Matching with Localized Score Aggregation for Robust Anomalous Sound Detection
Phurich Saengthong, Takahiro Shinozaki
Detecting subtle deviations in noisy acoustic environments is central to anomalous sound detection (ASD). A common training-free ASD pipeline temporally pools frame-level represent…
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…
A Unified Speech LLM for Diarization and Speech Recognition in Multilingual Conversations
Phurich Saengthong, Boonnithi Jiaramaneepinit, Sheng Li +2
Speech Large Language Models (Speech LLMs) have emerged as a crucial paradigm in recent years, extending the capabilities of traditional LLMs to speech tasks such as automatic spee…
Deep Generic Representations for Domain-Generalized Anomalous Sound Detection
Phurich Saengthong, Takahiro Shinozaki
Developing a reliable anomalous sound detection (ASD) system requires robustness to noise, adaptation to domain shifts, and effective performance with limited training data. Curren…