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20212026
most citedExploring Speech Recognition, Translation, and Understanding with Discrete Speech Units: A Comparative Study

2 citations · 4 across the 8 of their papers we have counts for

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8 papers

q-fin.ST2026

Generalized Stock Price Prediction for Multiple Stocks Combined with News Fusion

Pei-Jun Liao, Hung-Shin Lee, Yao-Fei Cheng +3

Predicting stock prices presents challenges in financial forecasting. While traditional approaches such as ARIMA and RNNs are prevalent, recent developments in Large Language Model…

cs.CL2024★ 1 cited

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…

cs.CL2023★ 2 cited

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…

cs.SD2022★ 1 cited

CasNet: Investigating Channel Robustness for Speech Separation

Fan-Lin Wang, Yao-Fei Cheng, Hung-Shin Lee +2

Recording channel mismatch between training and testing conditions has been shown to be a serious problem for speech separation. This situation greatly reduces the separation perfo…

cs.SD2022

A Training and Inference Strategy Using Noisy and Enhanced Speech as Target for Speech Enhancement without Clean Speech

Li-Wei Chen, Yao-Fei Cheng, Hung-Shin Lee +2

The lack of clean speech is a practical challenge to the development of speech enhancement systems, which means that there is an inevitable mismatch between their training criterio…

cs.SD2022

Speech-enhanced and Noise-aware Networks for Robust Speech Recognition

Hung-Shin Lee, Pin-Yuan Chen, Yao-Fei Cheng +2

Compensation for channel mismatch and noise interference is essential for robust automatic speech recognition. Enhanced speech has been introduced into the multi-condition training…

cs.SD2022

Chain-based Discriminative Autoencoders for Speech Recognition

Hung-Shin Lee, Pin-Tuan Huang, Yao-Fei Cheng +1

In our previous work, we proposed a discriminative autoencoder (DcAE) for speech recognition. DcAE combines two training schemes into one. First, since DcAE aims to learn encoder-d…

cs.CL2021

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…