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Da-Xin Tan

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Preprint Aug 2026

NormToken: Speaker- and Duration-Normalized Semantic Speech Tokens via Iterative S2U-T2U Refinement

Semantic speech tokens should preserve linguistic content while suppressing utterance-specific acoustic and duration variation. However, existing speech-to-unit (S2U) tokenizers often retain speaker-related acoustic characteristics and duration information. To address this issue, we propose NormToken, an iterative sema...

Han-Lin Zhang, Da-Xin Tan, De-Hua Tao et al. · 0 citations

#natural language process... Preprint Sep 2026

Reducing the Output-Mode Gap in Speech Language Models via Joint-Output On-Policy Distillation

Joint-Output On-Policy Distillation (JO-OPD) is proposed, which distills the model's stronger S2T policy into joint generation using student-generated S2TS trajectories, which reduces OMG across two interleaved generation architectures.

Da-Xin Tan, De-Hua Tao, Chen-Xi Deng et al. · 0 citations

Preprint Aug 2026

Speaker-Normalized Semantic Speech Tokens via Iterative S2U-T2U Refinement

Independently trained de-tokenizers show that the refined S2U and T2U tokens retain sufficient content for high-intelligibility voice conversion and text-to-speech synthesis and exhibit substantially improved cross-speaker consistency and reduced probe-recoverable speaker information.

Hanlin Zhang, Da-Xin Tan, De-Hua Tao et al. · 0 citations