Classroom Lecture Recognition | Zendy

Isabel Trancoso | Zendy; Ricardo Rodrigues Nunes | Zendy; Luí­s Neves | Zendy

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Classroom Lecture Recognition

Author(s) -

Isabel Trancoso,

Ricardo Rodrigues Nunes,

Luís Neves

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-34045-9

DOI - 10.1007/11751984_20

Subject(s) - computer science , word error rate , adaptation (eye) , speech recognition , domain adaptation , error analysis , natural language processing , word (group theory) , domain (mathematical analysis) , artificial intelligence , linguistics , psychology , mathematical analysis , philosophy , mathematics , neuroscience , classifier (uml)

The main goal of this work is to provide automatic transcriptions of classroom lectures for e-learning and e-inclusion applications. The first experi- ments using a recognition system trained for Broadcast News resulted in word error rates near 60%, clearly confirming the need for adaptation to the specific topic of the lectures, on one hand, and for better strategies for handling spon- taneous speech. This paper describes the different domain adaptation steps that lowered the error rate to 45%, with very little transcribed adaptation material. It also includes a qualitative analysis of the different types of error, focusing on the ones related to a very high rate of disfluencies.

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