6 papers
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators
Chandrakant Bothe, Cornelius Weber, Sven Magg +1
The recognition of emotion and dialogue acts enriches conversational analysis and help to build natural dialogue systems. Emotion interpretation makes us understand feelings and di…
Towards Dialogue-based Navigation with Multivariate Adaptation driven by Intention and Politeness for Social Robots
Chandrakant Bothe, Fernando Garcia, Arturo Cruz Maya +2
Service robots need to show appropriate social behaviour in order to be deployed in social environments such as healthcare, education, retail, etc. Some of the main capabilities th…
Discourse-Wizard: Discovering Deep Discourse Structure in your Conversation with RNNs
Chandrakant Bothe, Sven Magg, Cornelius Weber +1
Spoken language understanding is one of the key factors in a dialogue system, and a context in a conversation plays an important role to understand the current utterance. In this w…
Conversational Analysis using Utterance-level Attention-based Bidirectional Recurrent Neural Networks
Chandrakant Bothe, Sven Magg, Cornelius Weber +1
Recent approaches for dialogue act recognition have shown that context from preceding utterances is important to classify the subsequent one. It was shown that the performance impr…
A Context-based Approach for Dialogue Act Recognition using Simple Recurrent Neural Networks
Chandrakant Bothe, Cornelius Weber, Sven Magg +1
Dialogue act recognition is an important part of natural language understanding. We investigate the way dialogue act corpora are annotated and the learning approaches used so far.…
GradAscent at EmoInt-2017: Character- and Word-Level Recurrent Neural Network Models for Tweet Emotion Intensity Detection
Egor Lakomkin, Chandrakant Bothe, Stefan Wermter
The WASSA 2017 EmoInt shared task has the goal to predict emotion intensity values of tweet messages. Given the text of a tweet and its emotion category (anger, joy, fear, and sadn…