# DualSpeech: Enhancing Speaker-Fidelity and Text-Intelligibility Through Dual Classifier-Free Guidance

arXiv: https://arxiv.org/abs/2408.14423 · HTML: https://mlsanity.com/paper/2408.14423/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Aug 2024.

## Built on by (most cited first, 11 of 11)

- [MegaTTS 3: Sparse Alignment Enhanced Latent Diffusion Transformer for Zero-Shot Speech Synthesis](https://mlsanity.com/paper/2502.18924/) (2025)
- [ViSAGe: Video-to-Spatial Audio Generation](https://mlsanity.com/paper/2506.12199/) (2025)
- [Selective Classifier-free Guidance for Zero-shot Text-to-speech](https://mlsanity.com/paper/2509.19668/) (2025)
- [SupertonicTTS: Towards Highly Efficient and Streamlined Text-to-Speech System](https://mlsanity.com/paper/2503.23108/) (2025)
- [Length-Aware Rotary Position Embedding for Text-Speech Alignment](https://mlsanity.com/paper/2509.11084/) (2025)
- [MaskVCT: Masked Voice Codec Transformer for Zero-Shot Voice Conversion With Increased Controllability via Multiple Guidances](https://mlsanity.com/paper/2509.17143/) (2025)
- [Joint Residual Reweighting for Classifier Free Guidance in Flow-Matching Zero-Shot TTS](https://mlsanity.com/paper/2606.25672/) (2026)
- [Super Monotonic Alignment Search](https://mlsanity.com/paper/2409.07704/) (2024)
- [RobustSpeechFlow: Learning Robust Text-to-Speech Trajectories via Augmentation-based Contrastive Flow Matching](https://mlsanity.com/paper/2605.22083/) (2026)
- [Learnable Classifier-Free Guidance Null Embeddings for Enhanced Controllable Speech Synthesis](https://mlsanity.com/paper/2609.25411/) (2026)
- [Accent Analogy Guidance: More Speaker Similarity at Equal Accent in Cross-Lingual Voice Cloning](https://mlsanity.com/paper/2609.29123/) (2026)

## Abstract (arXiv)

Text-to-Speech (TTS) models have advanced significantly, aiming to accurately replicate human speech's diversity, including unique speaker identities and linguistic nuances. Despite these advancements, achieving an optimal balance between speaker-fidelity and text-intelligibility remains a challenge, particularly when diverse control demands are considered. Addressing this, we introduce DualSpeech, a TTS model that integrates phoneme-level latent diffusion with dual classifier-free guidance. This approach enables exceptional control over speaker-fidelity and text-intelligibility. Experimental results demonstrate that by utilizing the sophisticated control, DualSpeech surpasses existing state-of-the-art TTS models in performance. Demos are available at https://bit.ly/48Ewoib.