62 citations · 449 across the 49 of their papers we have counts for
8 papers · 1 filter
From English to More Languages: Parameter-Efficient Model Reprogramming for Cross-Lingual Speech Recognition
Chao-Han Huck Yang, Bo Li, Yu Zhang +4
In this work, we propose a new parameter-efficient learning framework based on neural model reprogramming for cross-lingual speech recognition, which can \textbf{re-purpose} well-t…
A Quantum Kernel Learning Approach to Acoustic Modeling for Spoken Command Recognition
Chao-Han Huck Yang, Bo Li, Yu Zhang +4
We propose a quantum kernel learning (QKL) framework to address the inherent data sparsity issues often encountered in training large-scare acoustic models in low-resource scenario…
Low-Resource Music Genre Classification with Cross-Modal Neural Model Reprogramming
Yun-Ning Hung, Chao-Han Huck Yang, Pin-Yu Chen +1
Transfer learning (TL) approaches have shown promising results when handling tasks with limited training data. However, considerable memory and computational resources are often re…
A Study of Designing Compact Audio-Visual Wake Word Spotting System Based on Iterative Fine-Tuning in Neural Network Pruning
Hengshun Zhou, Jun Du, Chao-Han Huck Yang +2
Audio-only-based wake word spotting (WWS) is challenging under noisy conditions due to environmental interference in signal transmission. In this paper, we investigate on designing…
A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification
Hao Yen, Chao-Han Huck Yang, Hu Hu +9
We propose a novel neural model compression strategy combining data augmentation, knowledge transfer, pruning, and quantization for device-robust acoustic scene classification (ASC…
PATE-AAE: Incorporating Adversarial Autoencoder into Private Aggregation of Teacher Ensembles for Spoken Command Classification
Chao-Han Huck Yang, Sabato Marco Siniscalchi, Chin-Hui Lee
We propose using an adversarial autoencoder (AAE) to replace generative adversarial network (GAN) in the private aggregation of teacher ensembles (PATE), a solution for ensuring di…
A Two-Stage Approach to Device-Robust Acoustic Scene Classification
Hu Hu, Chao-Han Huck Yang, Xianjun Xia +13
To improve device robustness, a highly desirable key feature of a competitive data-driven acoustic scene classification (ASC) system, a novel two-stage system based on fully convol…
Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition
Chao-Han Huck Yang, Jun Qi, Samuel Yen-Chi Chen +4
We propose a novel decentralized feature extraction approach in federated learning to address privacy-preservation issues for speech recognition. It is built upon a quantum convolu…