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eess.AS2026
CTC-Seeded Token Edit Refinement for Non-Autoregressive Speech Recognition
Wanting Huang, Weiran Wang
Non-autoregressive automatic speech recognition (ASR) enables parallel decoding, but many refinement-based methods begin from random, fully masked, or fixed-length token sequences,…
eess.AS2026
Align-Consistency: Improving Non-autoregressive and Semi-supervised ASR with Consistency Regularization
Wanting Huang, Weiran Wang
Consistency regularization (CR) improves the robustness and accuracy of Connectionist Temporal Classification (CTC) by ensuring predictions remain stable across input perturbations…
eess.AS2025
A Neural Model for Contextual Biasing Score Learning and Filtering
Wanting Huang, Weiran Wang
Contextual biasing improves automatic speech recognition (ASR) by integrating external knowledge, such as user-specific phrases or entities, during decoding. In this work, we use a…