Augmenting conversational dialogue by means of latent semantic googling

This paper presents Latent Semantic Googling, a variant of Landauer’s Latent Semantic Indexing that uses the Google search engine to judge the semantic closeness of sets of words and phrases. This concept is implemented via Ambient Google, a system for augmenting conversations through the classification of discussed topics. Ambient Google uses a speech recognition engine to generate Google keyphrase queries directly from conversations. These queries are used to analyze the semantics of the conversation, and infer related topics that have been discussed. Conversations are visualized using a spring-model algorithm representing common topics. This allows users to browse their conversation as a contextual relationship between discussed topics, and augment their discussion through the use of related websites discovered by Google. An evaluation of Ambient Google is presented, discussing user reaction to the system. Categories and Subject Descriptors H.3 [Information Systems]: Information ...

• Type: Conference
• Year: 2005
• Where: ICMI
• Authors: Robin Senior, Roel Vertegaal
• Keywords: Ambient Google, ICMI 2005, Latent Semantic Indexing, Semantic