2 citations · 4 across the 8 of their papers we have counts for
3 papers · 1 filter
Exploring the Impact of Data Quantity on ASR in Extremely Low-resource Languages
Yao-Fei Cheng, Li-Wei Chen, Hung-Shin Lee +1
This study investigates the efficacy of data augmentation techniques for low-resource automatic speech recognition (ASR), focusing on two endangered Austronesian languages, Amis an…
Exploring Speech Recognition, Translation, and Understanding with Discrete Speech Units: A Comparative Study
Xuankai Chang, Brian Yan, Kwanghee Choi +14
Speech signals, typically sampled at rates in the tens of thousands per second, contain redundancies, evoking inefficiencies in sequence modeling. High-dimensional speech features…
AlloST: Low-resource Speech Translation without Source Transcription
Yao-Fei Cheng, Hung-Shin Lee, Hsin-Min Wang
The end-to-end architecture has made promising progress in speech translation (ST). However, the ST task is still challenging under low-resource conditions. Most ST models have sho…