15 citations · 16 across the 13 of their papers we have counts for
4 papers · 1 filter
NeKo: Cross-Modality Post-Recognition Error Correction with Tasks-Guided Mixture-of-Experts Language Model
Yen-Ting Lin, Zhehuai Chen, Piotr Zelasko +11
Construction of a general-purpose post-recognition error corrector poses a crucial question: how can we most effectively train a model on a large mixture of domain datasets? The an…
DeSTA2: Developing Instruction-Following Speech Language Model Without Speech Instruction-Tuning Data
Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +5
Recent end-to-end speech language models (SLMs) have expanded upon the capabilities of large language models (LLMs) by incorporating pre-trained speech models. However, these SLMs…
DeSTA: Enhancing Speech Language Models through Descriptive Speech-Text Alignment
Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +4
Recent speech language models (SLMs) typically incorporate pre-trained speech models to extend the capabilities from large language models (LLMs). In this paper, we propose a Descr…
Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech
Szu-Wei Fu, Kuo-Hsuan Hung, Yu Tsao +1
Speech quality estimation has recently undergone a paradigm shift from human-hearing expert designs to machine-learning models. However, current models rely mainly on supervised le…