2 citations · 2 across the 4 of their papers we have counts for
4 papers
LV-CTC: Non-autoregressive ASR with CTC and latent variable models
Yuya Fujita, Shinji Watanabe, Xuankai Chang +1
Non-autoregressive (NAR) models for automatic speech recognition (ASR) aim to achieve high accuracy and fast inference by simplifying the autoregressive (AR) generation process of…
HuBERTopic: Enhancing Semantic Representation of HuBERT through Self-supervision Utilizing Topic Model
Takashi Maekaku, Jiatong Shi, Xuankai Chang +2
Recently, the usefulness of self-supervised representation learning (SSRL) methods has been confirmed in various downstream tasks. Many of these models, as exemplified by HuBERT 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…
Exploration of Efficient End-to-End ASR using Discretized Input from Self-Supervised Learning
Xuankai Chang, Brian Yan, Yuya Fujita +2
Self-supervised learning (SSL) of speech has shown impressive results in speech-related tasks, particularly in automatic speech recognition (ASR). While most methods employ the out…