Assessing the Ability of Neural TTS Systems to Model Consonant-Induced F0 Perturbation
This study proposes a segmental-level prosodic probing framework to evaluate neural TTS models' ability to reproduce consonant-induced f0 perturbation, a fine-grained segmental-prosodic effect that reflects local articulatory mechanisms. We compare synthetic and natural speech realizations for thousands of words, stratified by lexical frequency, using Tacotron 2 and FastSpeech 2 trained on the same speech corpus (LJ Speech). These controlled analyses are then complemented by a large-scale evaluation spanning multiple advanced TTS systems. Results show accurate reproduction for high-frequency words but poor generalization to low-frequency items, suggesting that the examined TTS architectur...
| Authors | Tianle Yang, Chengzhe Sun, Phil Rose et al. |
|---|---|
| Primary category | cs.CL |
| Published | 22 March 2026 |
| Last updated at source | 22 March 2026 |
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