23 citations · 84 across the 24 of their papers we have counts for
7 papers · 1 filter
Large-Scale Text-to-Image Model with Inpainting is a Zero-Shot Subject-Driven Image Generator
Chaehun Shin, Jooyoung Choi, Heeseung Kim +1
Subject-driven text-to-image generation aims to produce images of a new subject within a desired context by accurately capturing both the visual characteristics of the subject and…
Style-Friendly SNR Sampler for Style-Driven Generation
Jooyoung Choi, Chaehun Shin, Yeongtak Oh +3
Recent text-to-image diffusion models generate high-quality images but struggle to learn new, personalized styles, which limits the creation of unique style templates. In style-dri…
NanoVoice: Efficient Speaker-Adaptive Text-to-Speech for Multiple Speakers
Nohil Park, Heeseung Kim, Che Hyun Lee +3
We present NanoVoice, a personalized text-to-speech model that efficiently constructs voice adapters for multiple speakers simultaneously. NanoVoice introduces a batch-wise speaker…
VoiceGuider: Enhancing Out-of-Domain Performance in Parameter-Efficient Speaker-Adaptive Text-to-Speech via Autoguidance
Jiheum Yeom, Heeseung Kim, Jooyoung Choi +3
When applying parameter-efficient finetuning via LoRA onto speaker adaptive text-to-speech models, adaptation performance may decline compared to full-finetuned counterparts, espec…
VoiceTailor: Lightweight Plug-In Adapter for Diffusion-Based Personalized Text-to-Speech
Heeseung Kim, Sang-gil Lee, Jiheum Yeom +3
We propose VoiceTailor, a parameter-efficient speaker-adaptive text-to-speech (TTS) system, by equipping a pre-trained diffusion-based TTS model with a personalized adapter. VoiceT…
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…
Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation
Heeseung Kim, Soonshin Seo, Kyeongseok Jeong +9
Recent work shows promising results in expanding the capabilities of large language models (LLM) to directly understand and synthesize speech. However, an LLM-based strategy for mo…