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The SENSEI Project 
Conversational interaction is the most natural and persistent paradigm for business relations with customers. In contact centres millions of calls are handled daily. On social media platforms millions of blog posts are exchanged amongst users. 
Can we make sense of such conversations and help create assets and value for private and public organizations’ decision makers? And indeed for anyone interested in conversational content?
The overall goals of the SENSEI project are twofold. First, SENSEI will develop summarization/analytics technology to help users make sense of human conversation streams from diverse media channels. Second, SENSEI will design and evaluate its summarization technology in real-world environments, aiming to improve task performance and productivity of end-users.

Target User Groups 
SENSEI’s end-user groups are from the contact center and social and news media application domains. In the contact centre domain, the end-users of summarization analytics will be data analysts, quality control professionals and managers. In the media domain, the end-users of summarization analytics will be news comment readers, news comment authors, journalists and editors/media analysts.

Objectives and Outcomes
SENSEI’s scientific and technological objectives are to develop new technologies that will empower users to make sense of conversations through the following advances:
- Parse human conversations for both content, affect and other behavioural traits.
- Create adaptive technology to address the diversity and velocity of the media sources. 
 - Automatically generate human-readable multimedia, graphical and tabular summaries of dialogues and/or multiparty conversations.
- Evaluate technology where it is being used and not only in the lab. We will engage  end- users ranging from language data analysts to quality assurance professionals and news media analysts in real task settings . 
We expect SENSEI to advance the state-of-the-art in conversation understanding  towards the next-generation of analytics technology. SENSEI’s is committed to develop methodologies for professional conversation data analysts and create innovative analytics services from large scale data streams. Given the diverse target user groups, SENSEI will impact diverse industry sectors, such as contact centres, news and social media. 

Project Information

November  2013 – October 2016

University of Trento (Coordinator)   
Université d’Aix Marseille
University of Sheffield
University of Essex




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The research leading to these results has received funding from the European Union - Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 610916 – SENSEI.