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Exploring Features and Classifiers for Dialogue Act Segmentation

Full Citation:

Harm op den Akker and Christian Schulz, “Exploring Features and Classifiers for Dialogue Act Segmentation“, in Lecture Notes in Computer Science – Proceedings of the 5th International Workshop on Machine Learning for Multimodal Interaction (MLMI2008), Utrecht, the Netherlands, pages 196-207, September 2008.

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Cited By:

  1. (Reidsma, 2008) Annotations and Subjective Machines (PhD Thesis)
  2. (Germesin et al., 2008) Determining Latency for On-line Dialogue Act Classification
  3. (Germesin et al., 2009) Agreement Detection in Multi-Party Conversation
  4. (op den Akker et al., 2009) Supporting Engagement and Floor Control in Hybrid Meetings
  5. (Navarretta et al., 2010) Classification of Feedback Expressions in Multimodal Data
  6. [(Paggio and Navarretta, 2011) Learning to classify the feedback function of head movements in a Danish corpus of first encounters
  7. (Paggio and Navarretta, 2012) Head movements, facial expressions and feedback in conversations: empirical evidence from Danish multimodal data
  8. (Kleinbauer, 2012) Generating automated meeting summaries (PhD Thesis)
  9. (Visser et al., 2014) A model for incremental grounding in spoken dialogue systems
  10. (Görgel et al., 2014) Computer-aided classification of breast masses in mammogram images based on spherical wavelet transform and support vector machines
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