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Paper Detail

Presentation #11
Session:Dialogue
Session Time:Thursday, December 20, 10:00 - 12:00
Presentation Time:Thursday, December 20, 10:00 - 12:00
Presentation: Poster
Topic: Spoken dialog systems:
Paper Title: Contextual Topic Modeling for Dialog Systems
Authors: Chandra Khatri; Amazon Alexa 
 Rahul Goel; Amazon Alexa 
 Behnam Hedayatnia; Amazon Alexa 
 Angeliki Metanillou; Amazon Alexa 
 Anushree Venkatesh; Amazon Alexa 
 Raefer Gabriel; Amazon Alexa 
 Arindam Mandal; Amazon Alexa 
Abstract: Accurate prediction of conversation topics can be a valuable signal for creating coherent and engaging dialog systems. In this work, we focus on context-aware topic classification methods for identifying topics in free-form human-chatbot dialogs. We extend previous work on neural topic classification and unsupervised topic keyword detection by incorporating conversational context and dialog act features. On annotated data, we show that incorporating context and dialog acts leads to relative gains in topic classification accuracy by 35% and on unsupervised keyword detection recall by 11% for conversational interactions where topics frequently span multiple utterances. We show that topical metrics such as topical depth is highly correlated with dialog evaluation metrics such as coherence and engagement implying that conversational topic models can predict user satisfaction. Our work for detecting conversation topics and keywords can be used to guide chatbots towards coherent dialog.