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cs.SD2026
Revise-TTS: A Non-Masking Refinement Framework for Masked Diffusion Models in Text-to-Speech
Wanli Sun, Dan Su, Anton Ragni
Text-to-speech (TTS) based on masked diffusion models (MDMs) achieves competitive zero-shot speech synthesis performance. Unlike autoregressive (AR) models, MDMs define a corruptio…
eess.AS2026
Beyond Two-stage Diffusion TTS: Joint Structure and Content Refinement via Jump Diffusion
Jiabao Ai, Minghui Zhao, Anton Ragni
Diffusion and flow matching TTS faces a tension between discrete temporal structure and continuous spectral modeling. Two-stage models diffuse on fixed alignments, often collapsing…
eess.AS2026
Beyond the Utterance: An Empirical Study of Very Long Context Speech Recognition
Robert Flynn, Anton Ragni
Automatic speech recognition (ASR) models are normally trained to operate over single utterances, with a short duration of less than 30 seconds. This choice has been made in part d…