X2-NativeCursor: Native-Token Text Progress Tracking for Incremental-Text Streaming Codec TTS
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Abstract (arXiv)
Incremental-text streaming text-to-speech (TTS) needs online text progress tracking for synchronized highlighting, interruption handling, and dialogue-history updates. Input text arrives before it is spoken, so text arrival alone cannot indicate speech progress. Existing waveform-based alignment requires complete audio or adds acoustic processing during streaming. We propose X2-NativeCursor, a lightweight observer that tracks progress from native speech tokens before waveform decoding without changing the TTS generator. Its normalization plan links spoken labels to their original-text spans. Text and native-token encoders feed a local matcher that estimates the current label position. A separate output rule converts revisable position estimates into a cursor that never moves backward. Mean absolute error against an automatic reference is 0.151 Chinese characters with 80-ms lookahead, versus 1.253 characters with 320-ms lookahead for an online waveform baseline. Alignment real-time factor also decreases from 0.3598 to 0.0180 relative to this baseline. Lower tracking error is retained under a second automatic alignment reference. We evaluate X2-NativeCursor on Qwen3-TTS and validate its adaptation to CosyVoice2 by training a separate observer for each backbone. Code is publicly available at https://github.com/X-Square-Robot/X2Streaming-TTS.
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References · 17
- 2024Moshi: a speech-text foundation model for real-time dialoguecited by 536
- 2023Scaling Speech Technology to 1,000+ Languagescited by 401
- 2024CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Modelscited by 282
- 2026Qwen3-TTS Technical Reportcited by 106
- 2026Qwen3-ASR Technical Reportcited by 105
- 2023FunASR: A Fundamental End-to-End Speech Recognition Toolkitcited by 92
- 2020CTC-Segmentation of Large Corpora for German End-to-end Speech Recognitioncited by 75
- 2024ELLA-V: Stable Neural Codec Language Modeling with Alignment-guided Sequence Reorderingcited by 50
- 2019Incremental Text-to-Speech Synthesis with Prefix-to-Prefix Frameworkcited by 15
- 2020What the Future Brings: Investigating the Impact of Lookahead for Incremental Neural TTScited by 9
- 2023Achieving Timestamp Prediction While Recognizing with Non-Autoregressive End-to-End ASR Modelcited by 9
- 2026LLM-ForcedAligner: A Non-Autoregressive and Accurate LLM-Based Forced Aligner for Multilingual and Long-Form Speechcited by 8
5 more
- 2025VoXtream: Full-Stream Text-to-Speech with Extremely Low Latencycited by 5
- 2025BFA: Real-time Multilingual Text-to-speech Forced Alignmentcited by 5
- 2026CTC-TTS: LLM-based dual-streaming text-to-speech with CTC alignmentcited by 3
- 2026Montreal Forced Aligner and the state of speech-to-text alignment in 2026cited by 3
- 2023End-to-End real time tracking of children's reading with pointer networkcited by 2
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