SCIC: Scope- and Codebook-Aware Instruction Conditioning for Speaker-Adapted Expressive TTS
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Abstract (arXiv)
Long-form live-streaming TTS requires context-dependent prosody and paragraph-level coherence. However, many existing instruction-based TTS systems use global or uniform conditions, providing limited explicit control over clause-level relative prosodic changes. We introduce Speaker-Relative Inline Prosody Control, where each Pitch, Energy, or Speed instruction targets a clause relative to the preceding clause from the same speaker, while Pause uses an absolute duration interval. In codec-based TTS, Speed and Pause affect sequence length, whereas Pitch and Energy rely on residual codebooks. By analyzing Qwen3-TTS RVQ codebooks, we find that Energy concentrates in early residual codebooks, whereas Pitch accumulates across a deeper prefix. We therefore propose Scope- and Codebook-Aware Instruction Conditioning (SCIC), combining a Temporal Instruction Router for frame-level tag activation with Tag-Specific Codebook Weighting over residual codebooks. SCIC improves speaker-relative Pitch and Energy control over standard instruction fine-tuning using text-token tags. We further apply multi-reward GDPO post-training to jointly optimize control and quality, improving control accuracy while preserving CER and speaker similarity. In long-form synthesis, SCIC produces a more distinct paragraph-level expressive hierarchy than speaker-adapted SFT without instructions. Audio demos are available at: https://taoliveaigc.github.io/SCIC/
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 23 of its 25 references that are in the map. First posted on arXiv 30 Sep 2026.
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References · 23
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
- 2026GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimizationcited by 193
- 2025CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-trainingcited by 150
- 2026Qwen3-TTS Technical Reportcited by 118
- 2026Qwen3-ASR Technical Reportcited by 118
- 2025Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokenscited by 113
- 2022PromptTTS: Controllable Text-to-Speech with Text Descriptionscited by 110
- 2022Wespeaker: A Research and Production oriented Speaker Embedding Learning Toolkitcited by 97
- 2023InstructTTS: Modelling Expressive TTS in Discrete Latent Space with Natural Language Style Promptcited by 92
- 2023PromptTTS 2: Describing and Generating Voices with Text Promptcited by 48
- 2023PromptStyle: Controllable Style Transfer for Text-to-Speech with Natural Language Descriptionscited by 34
- 2026Fish Audio S2 Technical Reportcited by 9
11 more
- 2026OV-InstructTTS: Towards Open-Vocabulary Instruct Text-to-Speechcited by 6
- 2026FlexiVoice: Enabling Flexible Style Control in Zero-Shot TTS with Natural Language Instructionscited by 6
- 2025FleSpeech: Flexibly Controllable Speech Generation with Various Promptscited by 5
- 2026ReStyle-TTS: Relative and Continuous Style Control for Zero-Shot Speech Synthesiscited by 5
- 2026Qwen-Audio-3.0-TTS: Freely Controllable and Highly Robust Speech Synthesis with Multi-Stage Training Paradigmcited by 5
- 2025HD-PPT: Hierarchical Decoding of Content- and Prompt-Preference Tokens for Instruction-based TTScited by 4
- 2026VoXtream2: Full-stream TTS with dynamic speaking rate controlcited by 3
- 2026MAGIC-TTS: Fine-Grained Controllable Speech Synthesis with Explicit Local Duration and Pause Controlcited by 3
- 2026EmoTra-TTS: Smooth Intra-Utterance Emotion Transitions for Speech Synthesiscited by 3
- 2026Bagpiper-TTS: Natural Language Guided Universal Speech Synthesiscited by 1
- 2026WordVoice: Explicit and Decoupled Multi-Dimensional Word-Level Control for LLM-Based TTScited by 1
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