565 citations · 1.1k across the 41 of their papers we have counts for
6 papers · 1 filter
Towards End-to-end Automatic Code-Switching Speech Recognition
Genta Indra Winata, Andrea Madotto, Chien-Sheng Wu +1
Speech recognition in mixed language has difficulties to adapt end-to-end framework due to the lack of data and overlapping phone sets, for example in words such as "one" in Englis…
Learn to Code-Switch: Data Augmentation using Copy Mechanism on Language Modeling
Genta Indra Winata, Andrea Madotto, Chien-Sheng Wu +1
Building large-scale datasets for training code-switching language models is challenging and very expensive. To alleviate this problem using parallel corpus has been a major workar…
Emo2Vec: Learning Generalized Emotion Representation by Multi-task Training
Peng Xu, Andrea Madotto, Chien-Sheng Wu +2
In this paper, we propose Emo2Vec which encodes emotional semantics into vectors. We train Emo2Vec by multi-task learning six different emotion-related tasks, including emotion/sen…
Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems
Andrea Madotto, Chien-Sheng Wu, Pascale Fung
End-to-end task-oriented dialog systems usually suffer from the challenge of incorporating knowledge bases. In this paper, we propose a novel yet simple end-to-end differentiable m…
Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning
Genta Indra Winata, Andrea Madotto, Chien-Sheng Wu +1
Lack of text data has been the major issue on code-switching language modeling. In this paper, we introduce multi-task learning based language model which shares syntax representat…
Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition
Genta Indra Winata, Chien-Sheng Wu, Andrea Madotto +1
We propose an LSTM-based model with hierarchical architecture on named entity recognition from code-switching Twitter data. Our model uses bilingual character representation and tr…