Author

Hao Shi

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#artificial intelligence Review Oct 2026

Can LLM Agents Automate Reinforcement Learning for Text-to-Speech?

Although reinforcement learning (RL) post-training repairs the localized segmental errors of zero-shot text-to-speech (TTS), arriving at a working recipe still relies on tedious manual tuning, and whether LLM agents can take over this research pipeline is unclear. We investigate this question with AgenticTTS-Forge, a c...

Xuan-Jun Chen, Zi-Xiong Su, Hao Shi et al. · 0 citations

#natural language process... Mar 2026

Streaming Translation and Transcription Through Speech-to-Text Causal Alignment

This work proposes Hikari, a policy-free, end-to-end model for simultaneous speech-to-text translation and streaming transcription, and presents a supervised fine-tuning strategy that trains the model to recover from delays, significantly improving the quality-latency trade-off.

Roman Koshkin, Haesung Jeon, Lian-Bo Liu et al. · arXiv.org · 2 citations