3 papers
cs.CL2025
Transforming Questions and Documents for Semantically Aligned Retrieval-Augmented Generation
Seokgi Lee
We introduce a novel retrieval-augmented generation (RAG) framework tailored for multihop question answering. First, our system uses large language model (LLM) to decompose complex…
cs.CL2025
GSA-TTS : Toward Zero-Shot Speech Synthesis based on Gradual Style Adaptor
Seokgi Lee, Jungjun Kim
We present the gradual style adaptor TTS (GSA-TTS) with a novel style encoder that gradually encodes speaking styles from an acoustic reference for zero-shot speech synthesis. GSA…
eess.AS2025
Improving Robustness of Diffusion-Based Zero-Shot Speech Synthesis via Stable Formant Generation
Changjin Han, Seokgi Lee, Gyuhyeon Nam +1
Diffusion models have achieved remarkable success in text-to-speech (TTS), even in zero-shot scenarios. Recent efforts aim to address the trade-off between inference speed and soun…