4 citations · 4 across the 5 of their papers we have counts for
5 papers
Improving noisy student training for low-resource languages in End-to-End ASR using CycleGAN and inter-domain losses
Chia-Yu Li, Ngoc Thang Vu
Training a semi-supervised end-to-end speech recognition system using noisy student training has significantly improved performance. However, this approach requires a substantial a…
Oh, Jeez! or Uh-huh? A Listener-aware Backchannel Predictor on ASR Transcriptions
Daniel Ortega, Chia-Yu Li, Ngoc Thang Vu
This paper presents our latest investigation on modeling backchannel in conversations. Motivated by a proactive backchanneling theory, we aim at developing a system which acts as a…
Integrating Knowledge in End-to-End Automatic Speech Recognition for Mandarin-English Code-Switching
Chia-Yu Li, Ngoc Thang Vu
Code-Switching (CS) is a common linguistic phenomenon in multilingual communities that consists of switching between languages while speaking. This paper presents our investigation…
Improving Code-switching Language Modeling with Artificially Generated Texts using Cycle-consistent Adversarial Networks
Chia-Yu Li, Ngoc Thang Vu
This paper presents our latest effort on improving Code-switching language models that suffer from data scarcity. We investigate methods to augment Code-switching training text dat…
Improving Speech Recognition on Noisy Speech via Speech Enhancement with Multi-Discriminators CycleGAN
Chia-Yu Li, Ngoc Thang Vu
This paper presents our latest investigations on improving automatic speech recognition for noisy speech via speech enhancement. We propose a novel method named Multi-discriminator…