16 citations · 28 across the 10 of their papers we have counts for
8 papers · 1 filter
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…
KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos
Egor Lakomkin, Sven Magg, Cornelius Weber +1
In this paper, we describe KT-Speech-Crawler: an approach for automatic dataset construction for speech recognition by crawling YouTube videos. We outline several filtering and pos…
Incorporating End-to-End Speech Recognition Models for Sentiment Analysis
Egor Lakomkin, Mohammad Ali Zamani, Cornelius Weber +2
Previous work on emotion recognition demonstrated a synergistic effect of combining several modalities such as auditory, visual, and transcribed text to estimate the affective stat…
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.…