Yu-An Chung

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Fault diagnosis of railway point machines using dynamic time warping

Hee-Cheul Kim, João Sá, Yu-An Chung, Dong-Hwan Park, Sang-Hee Yoon
2016

Techset Com A practical condition monitoring method is proposed for the fault diagnosis of railway point machines (RPMs) by considering the difficulty of obtaining in-field failure data. Failures in… (More)

Audio Word2Vec: Unsupervised Learning of Audio Segment Representations using Sequence-to-sequence Autoencoder

Yu-An Chung, Chao-Chung Wu, Chia-Hao Shen, Hung-yi Lee, Lin-Shan Lee
INTERSPEECH
2016

using Sequence-to-sequence Autoencoder Yu-An Chung, Chao-Chung Wu, Chia-Hao Shen, Hung-Yi Lee, Lin-Shan Lee College of Electrical Engineering and Computer Science, National Taiwan University, Taipei,… (More)

Cost-aware Pre-training for Multiclass Cost-sensitive Deep Learning

Yu-An Chung, Hsuan-Tien Lin, Shao-Wen Yang
IJCAI
2016

Deep learning has been one of the most prominent machine learning techniques nowadays, being the state-of-the-art on a broad range of applications where automatic feature extraction is needed. Many… (More)

Unsupervised Learning of Audio Segment Representations using Sequence-to-sequence Recurrent Neural Networks

Yu-An Chung, Chao-Chung Wu, Chia-Hao Shen, Hung-Yi Lee
2016

Representing audio segments expressed with variablelength acoustic feature sequences as fixed-length feature vectors is usually needed in many speech applications, including speaker identification,… (More)

Learning Word Embeddings from Speech

In this paper, we propose a novel deep neural network architecture, Sequence-toSequence Audio2Vec, for unsupervised learning of fixed-length vector representations of audio segments excised from a… (More)

libact: Pool-based Active Learning in Python

Yao-Yuan Yang, Shao-Chuan Lee, Yu-An Chung, Tung-En Wu, Si-An Chen, Hsuan-Tien Lin
ArXiv
2017

libact is a Python package designed to make active learning easier for general users. The package not only implements several popular active learning strategies, but also features the… (More)

Supervised and Unsupervised Transfer Learning for Question Answering

Yu-An Chung, Hung-yi Lee, James R. Glass
NAACL-HLT
2018

l A large quantity of mismatched training examples is better than a small training set. Results of our transfer learning approach, the previous best models, and several baselines that did not use… (More)

Speech2Vec: A Sequence-to-Sequence Framework for Learning Word Embeddings from Speech

Yu-An Chung, James R. Glass
Interspeech
2018

In this paper, we propose a novel deep neural network architecture, Speech2Vec, for learning fixed-length vector representations of audio segments excised from a speech corpus, where the vectors… (More)

Learning Deep Representations of Medical Images using Siamese CNNs with Application to Content-Based Image Retrieval

Deep neural networks have been investigated in learning latent representations of medical images, yet most of the studies limit their approach in a single supervised convolutional neural network… (More)

Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces

Yu-An Chung, Wei-Hung Weng, Schrasing Tong, James R. Glass
ArXiv
2018

Recent research has shown that word embedding spaces learned from text corpora of different languages can be aligned without any parallel data supervision. Inspired by the success in unsupervised… (More)

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