26 citations · 43 across the 8 of their papers we have counts for
8 papers
What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model
Mu Yang, Ram C. M. C. Shekar, Okim Kang +1
This study is focused on understanding and quantifying the change in phoneme and prosody information encoded in the Self-Supervised Learning (SSL) model, brought by an accent ident…
CTC-based Non-autoregressive Speech Translation
Chen Xu, Xiaoqian Liu, Xiaowen Liu +9
Combining end-to-end speech translation (ST) and non-autoregressive (NAR) generation is promising in language and speech processing for their advantages of less error propagation a…
Learning ASR pathways: A sparse multilingual ASR model
Mu Yang, Andros Tjandra, Chunxi Liu +3
Neural network pruning compresses automatic speech recognition (ASR) models effectively. However, in multilingual ASR, language-agnostic pruning may lead to severe performance drop…
Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment
Mu Yang, Kevin Hirschi, Stephen D. Looney +2
Current leading mispronunciation detection and diagnosis (MDD) systems achieve promising performance via end-to-end phoneme recognition. One challenge of such end-to-end solutions…
Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis
Mu Yang, Shaojin Ding, Tianlong Chen +2
This work presents a lifelong learning approach to train a multilingual Text-To-Speech (TTS) system, where each language was seen as an individual task and was learned sequentially…
EventPlus: A Temporal Event Understanding Pipeline
Mingyu Derek Ma, Jiao Sun, Mu Yang +5
We present EventPlus, a temporal event understanding pipeline that integrates various state-of-the-art event understanding components including event trigger and type detection, ev…
Deep Structured Neural Network for Event Temporal Relation Extraction
Rujun Han, I-Hung Hsu, Mu Yang +3
We propose a novel deep structured learning framework for event temporal relation extraction. The model consists of 1) a recurrent neural network (RNN) to learn scoring functions f…
Spoken Language Intent Detection using Confusion2Vec
Prashanth Gurunath Shivakumar, Mu Yang, Panayiotis Georgiou
Decoding speaker's intent is a crucial part of spoken language understanding (SLU). The presence of noise or errors in the text transcriptions, in real life scenarios make the task…