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Found 8 papers, 4 papers with code
EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators
These neural models annotate the emotion corpora with dialogue act labels, and an ensemble annotator extracts the final dialogue act label.
A Context-based Approach for Dialogue Act Recognition using Simple Recurrent Neural Networks
Dialogue act recognition is an important part of natural language understanding.
Ranked #10 on
Dialogue Act Classification
on Switchboard corpus
Conversational Analysis using Utterance-level Attention-based Bidirectional Recurrent Neural Networks
Recent approaches for dialogue act recognition have shown that context from preceding utterances is important to classify the subsequent one.
Ranked #9 on
Dialogue Act Classification
on Switchboard corpus
Discourse-Wizard: Discovering Deep Discourse Structure in your Conversation with RNNs
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.
GradAscent at EmoInt-2017: Character- and Word-Level Recurrent Neural Network Models for Tweet Emotion Intensity Detection
Given the text of a tweet and its emotion category (anger, joy, fear, and sadness), the participants were asked to build a system that assigns emotion intensity values.
Towards Dialogue-based Navigation with Multivariate Adaptation driven by Intention and Politeness for Social Robots
Service robots need to show appropriate social behaviour in order to be deployed in social environments such as healthcare, education, retail, etc.
Polite Emotional Dialogue Acts for Conversational Analysis in Daily Dialog Data
Many socio-linguistic cues are used in the conversational analysis, such as emotion, sentiment, and dialogue acts.
Conversational Analysis of Daily Dialog Data using Polite Emotional Dialogue Acts
One of the fundamental cues is politeness, which linguistically possesses properties such as social manners useful in conversational analysis.
