3 papers
cs.SD2026
MixProLAP: Mixture-Induced Uncertainty Modeling for Probabilistic Language-Audio Pretraining
Yu Nakagome, Jaesong Lee, Soo-Whan Chung
Acoustic environments often contain multiple overlapping sound events, and the same acoustic scene can be described using diverse textual expressions, making audio-text alignment i…
cs.CL2025
WCTC-Biasing: Retraining-free Contextual Biasing ASR with Wildcard CTC-based Keyword Spotting and Inter-layer Biasing
Yu Nakagome, Michael Hentschel
Despite recent advances in end-to-end speech recognition methods, the output tends to be biased to the training data's vocabulary, resulting in inaccurate recognition of proper nou…
cs.CL2024
InterBiasing: Boost Unseen Word Recognition through Biasing Intermediate Predictions
Yu Nakagome, Michael Hentschel
Despite recent advances in end-to-end speech recognition methods, their output is biased to the training data's vocabulary, resulting in inaccurate recognition of unknown terms or…