360 citations · 489 across the 21 of their papers we have counts for
8 papers · 1 filter
Improve Query Focused Abstractive Summarization by Incorporating Answer Relevance
Dan Su, Tiezheng Yu, Pascale Fung
Query focused summarization (QFS) models aim to generate summaries from source documents that can answer the given query. Most previous work on QFS only considers the query relevan…
Retrieval-Free Knowledge-Grounded Dialogue Response Generation with Adapters
Yan Xu, Etsuko Ishii, Samuel Cahyawijaya +5
To diversify and enrich generated dialogue responses, knowledge-grounded dialogue has been investigated in recent years. The existing methods tackle the knowledge grounding challen…
Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation
Max W. Y. Lam, Jun Wang, Dan Su +1
One of the leading single-channel speech separation (SS) models is based on a TasNet with a dual-path segmentation technique, where the size of each segment remains unchanged throu…
Tune-In: Training Under Negative Environments with Interference for Attention Networks Simulating Cocktail Party Effect
Jun Wang, Max W. Y. Lam, Dan Su +1
We study the cocktail party problem and propose a novel attention network called Tune-In, abbreviated for training under negative environments with interference. It firstly learns…
TeCANet: Temporal-Contextual Attention Network for Environment-Aware Speech Dereverberation
Helin Wang, Bo Wu, Lianwu Chen +7
In this paper, we exploit the effective way to leverage contextual information to improve the speech dereverberation performance in real-world reverberant environments. We propose…
Contrastive Separative Coding for Self-supervised Representation Learning
Jun Wang, Max W. Y. Lam, Dan Su +1
To extract robust deep representations from long sequential modeling of speech data, we propose a self-supervised learning approach, namely Contrastive Separative Coding (CSC). Our…