303 citations · 424 across the 14 of their papers we have counts for
11 papers
Exploring Retraining-Free Speech Recognition for Intra-sentential Code-Switching
Zhen Huang, Xiaodan Zhuang, Daben Liu +3
In this paper, we present our initial efforts for building a code-switching (CS) speech recognition system leveraging existing acoustic models (AMs) and language models (LMs), i.e.…
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…
Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation
Hu Hu, Chao-Han Huck Yang, Xianjun Xia +13
In this technical report, we present a joint effort of four groups, namely GT, USTC, Tencent, and UKE, to tackle Task 1 - Acoustic Scene Classification (ASC) in the DCASE 2020 Chal…
On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression
Jun Qi, Jun Du, Sabato Marco Siniscalchi +2
In this paper, we exploit the properties of mean absolute error (MAE) as a loss function for the deep neural network (DNN) based vector-to-vector regression. The goal of this work…