Automatic Indexing of Lecture Presentations Using Unsupervised Learning of Presumed Discourse Markers
Autor: | M. Hasegawa, T. Kitade, Tatsuya Kawahara, Hiroaki Nanjo, Kazuya Shitaoka |
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Jazyk: | angličtina |
Rok vydání: | 2004 |
Předmět: |
Acoustics and Ultrasonics
Computer science business.industry Speech recognition Word processing Search engine indexing computer.software_genre Information extraction Automatic indexing ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Unsupervised learning Computer Vision and Pattern Recognition Language model Artificial intelligence Electrical and Electronic Engineering business computer Software Natural language processing Sentence Natural language |
Zdroj: | IEEE Transactions on Speech and Audio Processing. 12(4):409-419 |
ISSN: | 1063-6676 |
Popis: | A new method for automatic detection of section boundaries and extraction of key sentences from lecture audio archives is proposed. The method makes use of 'discourse markers' (DMs), which are characteristic expressions used in initial utterances of sections, together with pause and language model information. The DMs are derived in a totally unsupervised manner based on word statistics. An experimental evaluation using the Corpus of Spontaneous Japanese (CSJ) demonstrates that the proposed method provides better indexing of section boundaries compared with a simple baseline method using pause information only, and that it is robust against speech recognition errors. The method is also applied to extraction of key sentences that can index the section topics. The statistics of the presumed DMs are used to define the importance of sentences, which favors potentially section-initial ones. The measure is also combined with the conventional tf-idf measure based on content words. Experimental results confirm the effectiveness of using the DMs in combination with the keyword-based method. The paper also describes a statistical framework for transforming raw speech transcriptions into the document style for defining appropriate sentence units and improving readability. |
Databáze: | OpenAIRE |
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