98 citations · 254 across the 14 of their papers we have counts for
6 papers · 1 filter
Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
Junwen Bai, Weiran Wang, Yingbo Zhou +1
We propose Deep Autoencoding Predictive Components (DAPC) -- a self-supervised representation learning method for sequence data, based on the intuition that useful representations…
An investigation of phone-based subword units for end-to-end speech recognition
Weiran Wang, Guangsen Wang, Aadyot Bhatnagar +3
Phones and their context-dependent variants have been the standard modeling units for conventional speech recognition systems, while characters and subwords have demonstrated their…
A Comparison of Pooling Methods on LSTM Models for Rare Acoustic Event Classification
Chieh-Chi Kao, Ming Sun, Weiran Wang +1
Acoustic event classification (AEC) and acoustic event detection (AED) refer to the task of detecting whether specific target events occur in audios. As long short-term memory (LST…
Unsupervised Pre-training of Bidirectional Speech Encoders via Masked Reconstruction
Weiran Wang, Qingming Tang, Karen Livescu
We propose an approach for pre-training speech representations via a masked reconstruction loss. Our pre-trained encoder networks are bidirectional and can therefore be used direct…
Data Techniques For Online End-to-end Speech Recognition
Yang Chen, Weiran Wang, I-Fan Chen +1
Practitioners often need to build ASR systems for new use cases in a short amount of time, given limited in-domain data. While recently developed end-to-end methods largely simplif…
Semi-supervised ASR by End-to-end Self-training
Yang Chen, Weiran Wang, Chao Wang
While deep learning based end-to-end automatic speech recognition (ASR) systems have greatly simplified modeling pipelines, they suffer from the data sparsity issue. In this work,…