Imitation Learning for Elder-Facing Speech Synthesis
Recent advances in text-to-speech (TTS) synthesis have achieved highly natural and expressive speech generation. However, these systems are designed for general adults and overlook older adults' speech comprehension needs due to age-related sensory and cognitive decline. Prior work involves older adults by collecting preference feedback to tune model parameters. However, obtaining sufficient preference data is costly and difficult, as older adults quickly become fatigued during collection. In this paper, we propose a novel imitation learning (IL) framework to learn TTS models from expert demonstrations. We further improve Group Relative Policy Optimization (GRPO) with two-stage on-policy ...
| Authors | Dongrui Han, Weidong Chen, Jiawen Kang et al. |
|---|---|
| Primary category | cs.SD |
| Published | 19 June 2026 |
| Last updated at source | 19 June 2026 |
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