371 citations · 2.1k across the 193 of their papers we have counts for
11 papers · 1 filter
Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs
Guan-Ting Liu, En-Pei Hu, Pu-Jen Cheng +2
Aiming to produce reinforcement learning (RL) policies that are human-interpretable and can generalize better to novel scenarios, Trivedi et al. (2021) present a method (LEAPS) tha…
Silence is Sweeter Than Speech: Self-Supervised Model Using Silence to Store Speaker Information
Chi-Luen Feng, Po-chun Hsu, Hung-yi Lee
Self-Supervised Learning (SSL) has made great strides recently. SSL speech models achieve decent performance on a wide range of downstream tasks, suggesting that they extract diffe…
Searching for the Essence of Adversarial Perturbations
Dennis Y. Menn, Tzu-hsun Feng, Hung-yi Lee
Neural networks have demonstrated state-of-the-art performance in various machine learning fields. However, the introduction of malicious perturbations in input data, known as adve…
On the Efficiency of Integrating Self-supervised Learning and Meta-learning for User-defined Few-shot Keyword Spotting
Wei-Tsung Kao, Yuan-Kuei Wu, Chia-Ping Chen +3
User-defined keyword spotting is a task to detect new spoken terms defined by users. This can be viewed as a few-shot learning problem since it is unreasonable for users to define…
Parallelized Reverse Curriculum Generation
Zih-Yun Chiu, Yi-Lin Tuan, Hung-yi Lee +1
For reinforcement learning (RL), it is challenging for an agent to master a task that requires a specific series of actions due to sparse rewards. To solve this problem, reverse cu…
Voting for the right answer: Adversarial defense for speaker verification
Haibin Wu, Yang Zhang, Zhiyong Wu +2
Automatic speaker verification (ASV) is a well developed technology for biometric identification, and has been ubiquitous implemented in security-critic applications, such as banki…
Order-free Learning Alleviating Exposure Bias in Multi-label Classification
Che-Ping Tsai, Hung-Yi Lee
Multi-label classification (MLC) assigns multiple labels to each sample. Prior studies show that MLC can be transformed to a sequence prediction problem with a recurrent neural net…
One-shot Voice Conversion by Separating Speaker and Content Representations with Instance Normalization
Ju-chieh Chou, Cheng-chieh Yeh, Hung-yi Lee
Recently, voice conversion (VC) without parallel data has been successfully adapted to multi-target scenario in which a single model is trained to convert the input voice to many d…
Adversarial Learning of Label Dependency: A Novel Framework for Multi-class Classification
Che-Ping Tsai, Hung-Yi Lee
Recent work has shown that exploiting relations between labels improves the performance of multi-label classification. We propose a novel framework based on generative adversarial…
Temporal Pattern Attention for Multivariate Time Series Forecasting
Shun-Yao Shih, Fan-Keng Sun, Hung-yi Lee
Forecasting multivariate time series data, such as prediction of electricity consumption, solar power production, and polyphonic piano pieces, has numerous valuable applications. H…
Towards Structured Deep Neural Network for Automatic Speech Recognition
Yi-Hsiu Liao, Hung-Yi Lee, Lin-shan Lee
In this paper we propose the Structured Deep Neural Network (Structured DNN) as a structured and deep learning algorithm, learning to find the best structured object (such as a lab…