Search Results for author: Yi-Chieh Liu

Found 10 papers, 4 papers with code

Generative Speech Recognition Error Correction with Large Language Models and Task-Activating Prompting

no code implementations27 Sep 2023 Chao-Han Huck Yang, Yile Gu, Yi-Chieh Liu, Shalini Ghosh, Ivan Bulyko, Andreas Stolcke

We explore the ability of large language models (LLMs) to act as speech recognition post-processors that perform rescoring and error correction.

Ranked #3 on Speech Recognition on WSJ eval92 (using extra training data)

In-Context Learning speech-recognition +1

Adversarial Reweighting for Speaker Verification Fairness

no code implementations15 Jul 2022 Minho Jin, Chelsea J. -T. Ju, Zeya Chen, Yi-Chieh Liu, Jasha Droppo, Andreas Stolcke

Results show that the pairwise weighting method can achieve 1. 08% overall EER, 1. 25% for male and 0. 67% for female speakers, with relative EER reductions of 7. 7%, 10. 1% and 3. 0%, respectively.

Fairness Metric Learning +1

Treatment Learning Causal Transformer for Noisy Image Classification

no code implementations29 Mar 2022 Chao-Han Huck Yang, I-Te Danny Hung, Yi-Chieh Liu, Pin-Yu Chen

In this work, we incorporate this binary information of "existence of noise" as treatment into image classification tasks to improve prediction accuracy by jointly estimating their treatment effects.

Benchmarking Classification +3

Ensemble-based Transfer Learning for Low-resource Machine Translation Quality Estimation

no code implementations17 May 2021 Ting-Wei Wu, Yung-An Hsieh, Yi-Chieh Liu

Quality Estimation (QE) of Machine Translation (MT) is a task to estimate the quality scores for given translation outputs from an unknown MT system.

Machine Translation Miscellaneous +3

When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks

1 code implementation9 Feb 2019 Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen, Xiaoli Ma, Yi-Chang James Tsai

To study the intervention effects on pixel-level features for causal reasoning, we introduce pixel-wise masking and adversarial perturbation.

Causal Inference Visual Reasoning

Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model

1 code implementation16 Aug 2018 C. -H. Huck Yang, Fangyu Liu, Jia-Hong Huang, Meng Tian, Hiromasa Morikawa, I-Hung Lin, Yi-Chieh Liu, Hao-Hsiang Yang, Jesper Tegner

Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists.

General Classification

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