Using machine learning to cope with imbalanced classes in natural speech: Evidence from sentence boundary and disfluency detection

8th International Conference on Spoken Language Processing, ICSLP 2004

Volumn , Issue , 2004, Pages 1525-1528

  Liu, Yang ^a,c   Shriberg, Elizabeth ^a,b   Stolcke, Andreas ^a,b   Harper, Mary ^c  

^a INTERNATIONAL COMPUTER SCIENCE INSTITUTE   (United States)

^b SRI INTERNATIONAL   (United States)

^c PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECISION TREES; SPEECH PROCESSING; TREES (MATHEMATICS);

DISFLUENCY DETECTIONS; LANGUAGE PROCESSING; LEARNING METHODS; MACHINE LEARNING TECHNIQUES; SENTENCE BOUNDARIES; SKEWED CLASS DISTRIBUTIONS; SPONTANEOUS SPEECH; STRUCTURAL INFORMATION;

LEARNING SYSTEMS;

EID: 85009142186     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

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6. Y. Liu, N. Chawla, E. Shriberg, A. Stolcke, and M. Harper, "Resampling Techniques for Sentence Boundary Detection: A Case Study in Machine Learning from Imbalanced Data for Spoken Language Processing", Technical Report, ICSI, 2003.
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