Riccardi, Giuseppe and Bechet, Frederic and Danieli, Morena and Favre, Benoit and Gaizauskas, Robert and Kruschwitz, Udo and Poesio, Massimo (2016) The SENSEI Project: Making Sense of Human Conversations. In: UNSPECIFIED, ? - ?.
Riccardi, Giuseppe and Bechet, Frederic and Danieli, Morena and Favre, Benoit and Gaizauskas, Robert and Kruschwitz, Udo and Poesio, Massimo (2016) The SENSEI Project: Making Sense of Human Conversations. In: UNSPECIFIED, ? - ?.
Riccardi, Giuseppe and Bechet, Frederic and Danieli, Morena and Favre, Benoit and Gaizauskas, Robert and Kruschwitz, Udo and Poesio, Massimo (2016) The SENSEI Project: Making Sense of Human Conversations. In: UNSPECIFIED, ? - ?.
Abstract
Conversational interaction is the most natural and persistent paradigm for personal and business relations. In contact centres customer spoken conversations are handled daily. On social media platforms conversations are delivered in different forms, lengths and for different purposes. In both cases, conversations have little impact on the intended target listeners, due to the volume, velocity and diversity (media, style, social context) of the document streams (spoken conversations and blog posts). Most language analytics technology is limited in that it performs keyword search, which does not provide automatic descriptions of what happened, who said what, which opinions are held on what subject, in a coherent, readable and executable form. In the SENSEI project we plan to go beyond keyword search and sentence-based analysis of conversations. We adapt lightweight and large coverage linguistic models of semantic and discourse resources to learn a layered model of conversations. SENSEI addresses the issue of multidimensional textual, spoken and metadata descriptors in terms of semantic, para-semantic and discourse structures. Automated generation of readable analytics documents (summaries) will support end-users in the context of large data analysis tasks. Summarization technology developed in SENSEI has been evaluated with respect to users’ task requirements and performances in the context of contact centre and social media conversations.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
---|---|
Additional Information: | Published proceedings: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Uncontrolled Keywords: | Summarization; Spoken dialogue; Social media; Language analytics |
Subjects: | P Language and Literature > P Philology. Linguistics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 13 Dec 2016 15:57 |
Last Modified: | 30 Oct 2024 20:02 |
URI: | http://repository.essex.ac.uk/id/eprint/18487 |