A Novel Lecture Browser Using Key Phrases and Stream Graphs

  • We present a novel lecture browser that utilizes ranked key phrases displayed on a stream graph to overcome the shortcomings of traditional extractive (query-based) summaries. The system extracts key phrases from the ASR transcripts, performs an unsupervised ranking, and displays an initial number of phrases on the stream graph. This graph gives an intuition of when which key phrase is spoken, and how dominant it is throughout the lecture. The user can select the phrases to be displayed and furthermore adjust the ranking of the all phrases. All user interactions are logged to a server to improve the ranking algorithms and provide user specific rankings.

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Author:Korbinian Riedhammer, Martin Gropp, Elmar Nöth
Parent Title (German):Lehrstuhl für Mustererkennung, Universität Erlangen-Nürnberg
Document Type:Conference Proceeding
Publication Year:2011
Tag:Speech Recognition
faculties / departments:Fakultät für Informatik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke