Chao-Han Huck Yang

Orcid: 0000-0003-2879-8811

According to our database1, Chao-Han Huck Yang authored at least 94 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Perturbation Approach to Differential Privacy for Deep Learning based Speech Processing.
PhD thesis, 2024

Developing Instruction-Following Speech Language Model Without Speech Instruction-Tuning Data.
CoRR, 2024

Revise, Reason, and Recognize: LLM-Based Emotion Recognition via Emotion-Specific Prompts and ASR Error Correction.
CoRR, 2024

Chain-of-Thought Prompting for Speech Translation.
CoRR, 2024

Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition.
CoRR, 2024

Benchmarking Japanese Speech Recognition on ASR-LLM Setups with Multi-Pass Augmented Generative Error Correction.
CoRR, 2024

Evolutionary Prompt Design for LLM-Based Post-ASR Error Correction.
CoRR, 2024

Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation Models.
CoRR, 2024

An Investigation of Incorporating Mamba for Speech Enhancement.
CoRR, 2024

GenTranslate: Large Language Models are Generative Multilingual Speech and Machine Translators.
CoRR, 2024

Investigating Training Strategies and Model Robustness of Low-Rank Adaptation for Language Modeling in Speech Recognition.
CoRR, 2024

Large Language Models are Efficient Learners of Noise-Robust Speech Recognition.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

It's Never Too Late: Fusing Acoustic Information into Large Language Models for Automatic Speech Recognition.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Can Whisper Perform Speech-Based In-Context Learning?
Proceedings of the IEEE International Conference on Acoustics, 2024

Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification.
Proceedings of the IEEE International Conference on Acoustics, 2024

Paralinguistics-Enhanced Large Language Modeling of Spoken Dialogue.
Proceedings of the IEEE International Conference on Acoustics, 2024

Hot-Fixing Wake Word Recognition for End-to-End ASR Via Neural Model Reprogramming.
Proceedings of the IEEE International Conference on Acoustics, 2024

Exploiting A Quantum Multiple Kernel Learning Approach For Low-Resource Spoken Command Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2024

Towards ASR Robust Spoken Language Understanding Through in-Context Learning with Word Confusion Networks.
Proceedings of the IEEE International Conference on Acoustics, 2024

Bayesian Example Selection Improves In-Context Learning for Speech, Text and Visual Modalities.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

From Descriptive Richness to Bias: Unveiling the Dark Side of Generative Image Caption Enrichment.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

GenTranslate: Large Language Models are Generative Multilingual Speech and Machine Translators.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Exploiting Low-Rank Tensor-Train Deep Neural Networks Based on Riemannian Gradient Descent With Illustrations of Speech Processing.
IEEE ACM Trans. Audio Speech Lang. Process., 2023

Conditional Modeling Based Automatic Video Summarization.
CoRR, 2023

Generative error correction for code-switching speech recognition using large language models.
CoRR, 2023

A Neural State-Space Model Approach to Efficient Speech Separation.
CoRR, 2023

Treatment Learning Causal Transformer for Noisy Image Classification.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Pessimistic Model Selection for Offline Deep Reinforcement Learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Inference and Denoise: Causal Inference-Based Neural Speech Enhancement.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command Recognition.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Parameter-Efficient Learning for Text-to-Speech Accent Adaptation.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

A Parameter-Efficient Learning Approach to Arabic Dialect Identification with Pre-Trained General-Purpose Speech Model.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

A Multi-dimensional Deep Structured State Space Approach to Speech Enhancement Using Small-footprint Models.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

Differentially Private Adapters for Parameter Efficient Acoustic Modeling.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

How to Estimate Model Transferability of Pre-Trained Speech Models?
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

A Neural State-Space Modeling Approach to Efficient Speech Separation.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

A Quantum Kernel Learning Approach to Acoustic Modeling for Spoken Command Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2023

From English to More Languages: Parameter-Efficient Model Reprogramming for Cross-Lingual Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2023

Low-Resource Music Genre Classification with Cross-Modal Neural Model Reprogramming.
Proceedings of the IEEE International Conference on Acoustics, 2023

Certified Robustness of Quantum Classifiers Against Adversarial Examples Through Quantum Noise.
Proceedings of the IEEE International Conference on Acoustics, 2023

Whispering LLaMA: A Cross-Modal Generative Error Correction Framework for Speech Recognition.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Causalainer: Causal Explainer for Automatic Video Summarization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Low-Rank Adaptation of Large Language Model Rescoring for Parameter-Efficient Speech Recognition.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

Generative Speech Recognition Error Correction With Large Language Models and Task-Activating Prompting.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

Enhancing Privacy Preservation with Quantum Computing for Word-Level Audio-Visual Speech Recognition.
Proceedings of the Asia Pacific Signal and Information Processing Association Annual Summit and Conference, 2023

2022
Low-Resource Music Genre Classification with Advanced Neural Model Reprogramming.
CoRR, 2022

Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional Regression.
CoRR, 2022

Treatment Learning Transformer for Noisy Image Classification.
CoRR, 2022

Non-local Attention Improves Description Generation for Retinal Images.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

An Experimental Study on Private Aggregation of Teacher Ensemble Learning for End-to-End Speech Recognition.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

An Ensemble Teacher-Student Learning Approach with Poisson Sub-sampling to Differential Privacy Preserving Speech Recognition.
Proceedings of the 13th International Symposium on Chinese Spoken Language Processing, 2022

A Study on Joint Modeling and Data Augmentation of Multi-Modalities for Audio-Visual Scene Classification.
Proceedings of the 13th International Symposium on Chinese Spoken Language Processing, 2022

Causal Video Summarizer for Video Exploration.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2022

A Study of Designing Compact Audio-Visual Wake Word Spotting System Based on Iterative Fine-Tuning in Neural Network Pruning.
Proceedings of the IEEE International Conference on Acoustics, 2022

When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing.
Proceedings of the IEEE International Conference on Acoustics, 2022

Mitigating Closed-Model Adversarial Examples with Bayesian Neural Modeling for Enhanced End-to-End Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2022

A Variational Bayesian Approach to Learning Latent Variables for Acoustic Knowledge Transfer.
Proceedings of the IEEE International Conference on Acoustics, 2022

Training a Resilient Q-network against Observational Interference.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Attention Based Bidirectional Convolutional LSTM for High-Resolution Radio Tomographic Imaging.
IEEE Trans. Circuits Syst. II Express Briefs, 2021

A Study of Low-Resource Speech Commands Recognition based on Adversarial Reprogramming.
CoRR, 2021

QTN-VQC: An End-to-End Learning framework for Quantum Neural Networks.
CoRR, 2021

A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification.
CoRR, 2021

Longer Version for "Deep Context-Encoding Network for Retinal Image Captioning".
CoRR, 2021

Causal Inference Q-Network: Toward Resilient Reinforcement Learning.
CoRR, 2021

DeepOpht: Medical Report Generation for Retinal Images via Deep Models and Visual Explanation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

PATE-AAE: Incorporating Adversarial Autoencoder into Private Aggregation of Teacher Ensembles for Spoken Command Classification.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Voice2Series: Reprogramming Acoustic Models for Time Series Classification.
Proceedings of the 38th International Conference on Machine Learning, 2021

Robust Unsupervised Multi-Object Tracking In Noisy Environments.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Deep Context-Encoding Network For Retinal Image Captioning.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2021

A Two-Stage Approach to Device-Robust Acoustic Scene Classification.
Proceedings of the IEEE International Conference on Acoustics, 2021

Multi-Task Language Modeling for Improving Speech Recognition of Rare Words.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2021

2020
Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation.
CoRR, 2020

Variational Quantum Circuits for Deep Reinforcement Learning.
IEEE Access, 2020

Exploring Deep Hybrid Tensor-to-Vector Network Architectures for Regression Based Speech Enhancement.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Wavelet Channel Attention Module With A Fusion Network For Single Image Deraining.
Proceedings of the IEEE International Conference on Image Processing, 2020

Y-Net: Multi-Scale Feature Aggregation Network With Wavelet Structure Similarity Loss Function For Single Image Dehazing.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Enhanced Adversarial Strategically-Timed Attacks Against Deep Reinforcement Learning.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Characterizing Speech Adversarial Examples Using Self-Attention U-Net Enhancement.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Submodular Rank Aggregation on Score-Based Permutations for Distributed Automatic Speech Recognition.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Tensor-To-Vector Regression for Multi-Channel Speech Enhancement Based on Tensor-Train Network.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Interpretable Self-Attention Temporal Reasoning for Driving Behavior Understanding.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Convolutional Neural Network Based Radio Tomographic Imaging.
Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020

Evolving Neural Networks through a Reverse Encoding Tree.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019
When Causal Intervention Meets Image Masking and Adversarial Perturbation for Deep Neural Networks.
CoRR, 2019

Reinforcement learning based interconnection routing for adaptive traffic optimization.
Proceedings of the 13th IEEE/ACM International Symposium on Networks-on-Chip, 2019

When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

2018
Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary Learning.
CoRR, 2018

Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model.
CoRR, 2018

Learning Functions in Large Networks requires Modularity and produces Multi-Agent Dynamics.
CoRR, 2018

A Novel Hybrid Machine Learning Model for Auto-Classification of Retinal Diseases.
CoRR, 2018

Auto-classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model.
Proceedings of the Computer Vision - ACCV 2018 Workshops, 2018

Synthesizing New Retinal Symptom Images by Multiple Generative Models.
Proceedings of the Computer Vision - ACCV 2018 Workshops, 2018


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