Learnable Classifier-Free Guidance Null Embeddings for Enhanced Controllable Speech Synthesis
Classifier-free Guidance (CFG) is widely adopted in text-to-speech (TTS) systems to enhance generation quality and conditioning fidelity by interpolating between conditioned and unconditioned predictions. A common unconditional technique is to use an empty representation, in the form of a fixed null vector. In this work, we propose replacing this representation with a learnable unconditional embedding, optimized to represent a meaningful unconditional state. Objective and subjective evaluations demonstrate that learnable null embeddings consistently outperform fixed null embeddings across speaker similarity, speech stability, and expressiveness, while exhibiting greater robustness to larg...
| Authors | Biel Tura Vecino, Yoach Lacombe, Julian Weber et al. |
|---|---|
| Primary category | eess.AS |
| Published | 21 September 2026 |
| Last updated at source | 21 September 2026 |
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