4 papers
UniverSR: Unified and Versatile Audio Super-Resolution via Vocoder-Free Flow Matching
Woongjib Choi, Sangmin Lee, Hyungseob Lim +1
In this paper, we present a vocoder-free framework for audio super-resolution that employs a flow matching generative model to capture the conditional distribution of complex-value…
SAGE-LD: Towards Scalable and Generalizable End-to-End Language Diarization via Simulated Data Augmentation
Sangmin Lee, Woongjib Choi, Jihyun Kim +1
In this paper, we present a neural spoken language diarization model that supports an unconstrained span of languages within a single framework. Our approach integrates a learnable…
UniCoM: A Universal Code-Switching Speech Generator
Sangmin Lee, Woojin Chung, Seyun Um +1
Code-switching (CS), the alternation between two or more languages within a single speaker's utterances, is common in real-world conversations and poses significant challenges for…
LAMA-UT: Language Agnostic Multilingual ASR through Orthography Unification and Language-Specific Transliteration
Sangmin Lee, Woo-Jin Chung, Hong-Goo Kang
Building a universal multilingual automatic speech recognition (ASR) model that performs equitably across languages has long been a challenge due to its inherent difficulties. To a…