7 citations · 7 across the 6 of their papers we have counts for
6 papers
LLM-Based Multi-Reference Evaluation for Efficient and Robust Assessment of Phrase Break Annotations
Younghan Park, Hoyeon Lee, Hawon Jeong +1
Reliable evaluation of phrase break annotations is crucial, as subtle variations in prosodic boundaries directly affect the clarity and naturalness of speech. However, existing app…
Synthetic Data Generation for Phrase Break Prediction with Large Language Model
Hoyeon Lee, Sejung Son, Ye-Eun Kang +1
Current approaches to phrase break prediction address crucial prosodic aspects of text-to-speech systems but heavily rely on vast human annotations from audio or text, incurring si…
A Two-Step Approach for Data-Efficient French Pronunciation Learning
Hoyeon Lee, Hyeeun Jang, Jong-Hwan Kim +1
Recent studies have addressed intricate phonological phenomena in French, relying on either extensive linguistic knowledge or a significant amount of sentence-level pronunciation d…
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…
Video Multimodal Emotion Recognition System for Real World Applications
Sun-Kyung Lee, Jong-Hwan Kim
This paper proposes a system capable of recognizing a speaker's utterance-level emotion through multimodal cues in a video. The system seamlessly integrates multiple AI models to f…
Cross-Lingual Transfer Learning for Phrase Break Prediction with Multilingual Language Model
Hoyeon Lee, Hyun-Wook Yoon, Jong-Hwan Kim +1
Phrase break prediction is a crucial task for improving the prosody naturalness of a text-to-speech (TTS) system. However, most proposed phrase break prediction models are monoling…