activity
20162019
most citedFine Grained Knowledge Transfer for Personalized Task-oriented Dialogue Systems

14 citations · 15 across the 4 of their papers we have counts for

collaborators

19 papers

cs.CL2019

CAiRE_HKUST at SemEval-2019 Task 3: Hierarchical Attention for Dialogue Emotion Classification

Genta Indra Winata, Andrea Madotto, Zhaojiang Lin +4

Detecting emotion from dialogue is a challenge that has not yet been extensively surveyed. One could consider the emotion of each dialogue turn to be independent, but in this paper…

cs.CL2019

A novel repetition normalized adversarial reward for headline generation

Peng Xu, Pascale Fung

While reinforcement learning can effectively improve language generation models, it often suffers from generating incoherent and repetitive phrases \cite{paulus2017deep}. In this p…

cs.CL20191 cited

Towards Universal End-to-End Affect Recognition from Multilingual Speech by ConvNets

Dario Bertero, Onno Kampman, Pascale Fung

We propose an end-to-end affect recognition approach using a Convolutional Neural Network (CNN) that handles multiple languages, with applications to emotion and personality recogn…

cs.CL2018

GlobalTrait: Personality Alignment of Multilingual Word Embeddings

Farhad Bin Siddique, Dario Bertero, Pascale Fung

We propose a multilingual model to recognize Big Five Personality traits from text data in four different languages: English, Spanish, Dutch and Italian. Our analysis shows that wo…

cs.CL2018

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…

cs.CL2018

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…